"""“’9’!4Ti.T-.‘ OUTDOOR RECREATIONAL LAND USE» ‘ SELECTION MODEL Dissertation for the Degree of PITT D MICHIGAN STATE UNIVERSITY. ’ Francis Martin Domoy 1973 * ' 5' LIBRARY Michigan State University T, -.. '. .l' ‘ _ . "-5. .’ W “mt/3'5... 4.‘_..:-._. . ' ~, - 'n '- . 1 l__ N' ' 'J'THET:':{~I ABSTRACT OUTDOOR RECREATIONAL LAND USE SELECTION MODEL by Francis Martin Domoy The problem presented within this research project concerns the location of feasible outdoor recreational sites; those which are in phase with community priorities. Community prior- ities are based upon the concerns for the economic, physical, and aesthetic resource characteristics within a planning area. The problem therefore, is to locate feasible outdoor recrea- tional sites supporting community preferences. The objective of this research project was to provide an outdoor recreational planning tool integrating the economic, physical, and aesthetic resource characteristics of a region and the incorporation of community objectives. Orleans County, New York was selected as a county commun- ity for the formulation of the outdoor recreational planninn model. This county was chosen since research indicated a need for an outdoor recreational facility, specifically, a full season campground. Simulation techniques were utilized by mathematically transposing community priorities into single and multiple objective functions. These objective functions represented community concerns for the economic, physical, and aesthetic Francis Martin Domoy resource characteristics. A single objective function, such as the minimization of development cost, may be the community pri- ority in the selection of a feasible site. Multiple objective functions which incorporate a number of single objective func- tions in the selection procedure rank and present numerous alternatives for site selection. Computer mapping routines are utilized to visually represent alternative sites based upon the objective functions. The computer maps are displayed at three levels of intensity to represent low, medium, and high values corresponding to single and multiple objective functions. From the preliminary selection of feasible sites, each individual site may be further analyzed by reviewing the original data file for each site or by mapping cells of 2h?.l acres. It is the conclusion of this research project that those cells satisfying the multiple objective function combination of low property tax revenue loss, low development cost, and high aesthetic index shall be selected as feasible sites for public campground development. Furthermore, a specific site should be chosen from the seventeen cells selected from the total of 1056 possible cells within Orleans County. With the seventeen cell array isolated, the decision-maker may further analyze each cell by returning to the original data file representing all of the county's cells, from which the computer maps were produced. OUTDOOR RECREATIONAL LAND USE SELECTION MODEL BY Francis Martin Domoy A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Resource Development 1973 ACKNOWLEDGEMENTS I wish to thank my major professor, Dr. Daniel E. Chappelle for directing my graduate program, and for providing both financial and academic assistance in the completion of my degree. It was his stimulation for research which influenced the formulation of this dissertation. The planning of this study and model development was conducted on McIntire-Stennis funding under the Michigan Experiment Station research project entitled, "Computer Models in the Spatial Analysis of Natural Resource Economic Data." In addition, my graduate committee, including Dr. Milton Steinmueller, Dr. Robert Marty, Dr. Lewis Moncreif, and Dr. Jay Harman generated a composite force which influenced my phil- osophies and learning at Michigan State University. Appreciation is also extended to Mr. Larry Stid, Genesee/ Finger Lakes Regional Planning Board, for preparation of the computer maps which are an important part of the dissertation work. I would also like to thank Mr. Sidney Cleveland, Coopera- tive Extension Service of Orleans County, New York, in pro- viding valuable information for the development of the planning model. Most of all, I wish to thank my wife, Dianne, in her 11 supportive role for the completion of my graduate career. It was her encouragement, her willingness to assist in typing, and listening, and her interest which promoted the completion of my work. TABLE OF CONTENTS ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . LIST OF TABLES I I I I I I I I I I I I I I I O O I I LIST OF ILLUSTRATIONSI I I I I I I I I I I I I I I I LIST OF APPENDIX TABLES. . . . . . . . . . . . . . . Chapter I. INTRODUCTION Importance . . . . . . . . . . . . . . . . Objectives I I I I I I O I I I I I I I I I II. RECREATIONAL PLANNING III. IV. VI. Previous Planning Methods and Models . Proposed Outdoor Recreational Land Use Selection Model . . . . . . . . . . . . Identification of Land Resource Components A PHYSICAL, ECONOMIC AND DEMOGRAPHIC PROFILE OF THE SELECTED STUDY AREA: ORLEANS COUNTY, NEW YORK . . . . . . . . . . . . . APPLICATION OF THE OUTDOOR RECREATIONAL SELECTION MODEL WITHIN ORLEANS COUNTY, NEw YORK I O I U C I U I O I O I 0 O O O I RESULTS C O I C D I I I O I O C O O Q I O U I SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS summary I I I I I I I I I I I I I I I I I Conclusions . . . . . . . . . . . . . . . Recommendations . . . . . . . . . . . . . iv Page ii vi viii ix 33 46 75 94 133 147 150 16l~ TABLE OF CONTENTS (con't) BIBLIOGRAPHY o a o a o o o o o o o a o o o I o o o 163 APPENDIX 0 o o a o a o o o o a o o o o I o o o o 0 17o Table 1. Property Tax Revenue Loss. . . . . . . . 2. Development Cost . . . . . . . . . . . . 3. Total 0081: o O I I I I I I I I I O I I I 4. Aesthetic Index Based Upon Physical Factors . . . . . . . . . . 5. Amount of Forested Land. , . . . . . . . 6. Water to Land Relationship Aesthetic Indicator. . . . . . . . . 7. Contour Differential . . . . . . . . . . 8. Forest Color Contrast Aesthetic Indicator. . . . . . . . . . . . . . 9. Percentage Distribution of Employment Within Orleans County, and Its Rank in the Neighboring Eight-County Area: 10. Measures of Agricultural Activity Orleans County, 1964 . . . . . . . . 11. Comparisons of Land Uses of Orleans County, 1964 . . . . . . . . 12. Tiling Costs of Soil Associations Within Orleans County. . . . . . . . 13. Transportation Construction Cost Scale . 1U. Combinations of Ranked Objective Functions A. Property Tax Revenue Loss vs. Development Costs B. Property Tax Revenue Loss and Development Costs vs. Aesthetic Index Levels 15. Frequency of Cells Mapped at Three Levels of LIST OF TABLES ' I Intensity for Three Objective Functions. . vi Page 47 52 56 57 69 70 72 73 84 86 87 111 113 128 130 Table Page 16. Economic, Physical and Aesthetic Data for Orleans County's LLH Cells. . . . . . . . 141 17. Economic, Physical and Aesthetic Data for Orleans County's HHL Cells. . . . . . . . 14A vii LIST OF ILLUSTRATIONS O I Figure 1. Model Solution Sequence for Outdoor Recreational Iand Use Selection Model. 2. Location of Orleans County Within New York State . . . . . . . . 3. Map of Physiographic Regions and Drainage Systems of Orleans County, New York. a. Per Acre Iand Value and Per Acre Land Value With Improvements for Farms (A,B,C,D). . 5. Location of Sample Cell, 783,226, Within Orleans County, New York . . . 6. Deciduous Forest Cover Class, Orleans County, New York . . . 7. Coniferous Forest Cover Class, Orleans County, New York . . . 8. Mixed Deciduous—coniferous Forest Class, Orleans County, New York . . . 9. Swampland-brushland Forest Class, Orleans County, New York . . viii Page u1-u5 76 79 98 102 121 121 122 122 LIST OF APPENDIX TABLES 0 Table 1. Mean Per Acre Assessed Land Value, Orleans county, N. Y0 . o c o o I 0 0 o a O O 2. Mean Per Acre Assessed Land Value With Improvements, Orleans County, N. Y. . 3. Property Tax Revenue Per Cell, Orleans County, N. Y. . . . . . . . . 4. Acquisition Cost Per Cell Orleans County, N. Y. . . . . . . . . 5. Development Cost, Orleans County, N. Y. . . . . . . . . 6. Total Cost, Orleans County, N. Y. . . . . . . . . 7. Aesthetic Index, Orleans County, N. Y. . . . . . . . . 8. Low Property Tax Revenue Loss, Low Development Cost, and Low Aesthetic Index . . . . 9. Low Property Tax Revenue Loss, Low Development Cost, and Medium Aesthetic Index. . . 10. Low Property Tax Revenue Loss, Low Development Cost, and High Aesthetic Index . . . 11. Low Property Tax Revenue Loss, Medium Development Cost, and Low Aesthetic Index 12. Low Property Tax Revenue Loss, Medium Development Cost, and Medium Aesthetic Index, 13. Low Property Tax Revenue Loss, Medium Development Cost, and High Aesthetic Index 1h. Low Property Tax Revenue Loss, High Development Cost, and Low Aesthetic Index . . . . 15. Low Property Tax Revenue Loss, High Development Cost, and Medium Aesthetic Index. . ix Page 170 17a 178 182 186 190 194 198 202 206 214 218 222 226 Table 16. Low Property Tax Revenue Loss, High Development Cost, and High Aesthetic Index . . , , , , , 17. Medium Property Tax Revenue Loss, Low Development Cost, and Low Aesthetic Index . 18. Medium Property Tax Revenue Loss, Low Development Cost, and Medium Aesthetic Index 19. Medium Property Tax Revenue Loss, Low Development Cost, and High Aesthetic Index , 20. Medium Property Tax Revenue Loss, Medium Development Cost, and Low Aesthetic Index. . 21. Medium Property Tax Revenue Loss, Medium Development Cost, and Medium Aesthetic Index 22. Medium Property Tax Revenue Loss, Medium Development Cost, and High Aesthetic Index . 23. Medium Property Tax Revenue Loss, High Development Cost, and Low Aesthetic Index . 2h. Medium Property Tax Revenue Loss, High Development Cost, and Medium Aesthetic Index 25. Medium Property Tax Revenue Loss, High Development Cost, and High Aesthetic Index . 26. High Property Tax Revenue Loss, Low Development Cost, and Low Aesthetic Index. . 27. High Property Tax Revenue Loss, Low Development Cost, and Medium Aesthetic Index 28. High Property Tax Revenue Loss, Low Development Cost, and Hiih Aesthetic Index , 29. High Property Tax Revenue Loss, Medium Development Cost, and Low Aesthetic Index . 30. High Property Tax Revenue Loss, Medium Development Cost, and Medium Aesthetic Index 31. High Property Tax Revenue Loss, Medium Development Cost, and High Aesthetic Index . 3?. Hiflh PrOperty Tax Revenue Loss, High Development Cost, and Low Aesthetic Index. . 33. High Property Tax Revenue Loss, High Development Cost, and Medium Aesthetic Index Page 230 23# 238 2H2 2&6 250 254 258 262 266 270 274 278 282 286 290 294 298 Table Page 34. High Property Tax Revenue Loss, High Development Cost, and High Aesthetic Index . . 302 xi CHAPTER I INTRODUCTION Orleans County, New York has experienced increased demands for land utilization, thus keeping pace with state and national trends. Specific pressures influencing the demand for individual land uses include: need for residential homes, desire for recreational space, fluctuation of domestic and foreign food supplies, and the expansion of industrial and commercial enterprises. A contemporary problem is the wise selection of feasible outdoor recreational sites. The objectives of this study, which will be further expanded upon later, are to develop a decision-making tool for feasible outdoor recrea- tion site selections and to select areas which optimize the aesthetic, economic, and physical resources within the county. Problems are derived when local planning officials try to optimize all site characteristics within an area. In a land use planning sense, optimization refers to the maximization, or minimization of an objective function including one or more characteristics for one or more land parcels. As a result, the decision-maker is faced with a situation which forces him to establish priorities or specific objective functions. If we wish to select land parcels which provide the most aesthetically pleasing outdoor recreation facility for public 1 use, it may require either a high development and acquisition cost or high property tax loss to county tax revenue. On the other hand, if we wish to minimize property tax loss to the county, in providing public recreational facilities, the most marginal low value areas for agricultural and forestry production, may be selected. However, as a result of this decision, the development and maintenance costs may be high and the aesthetics of the site may be lacking. There- fore, economic, physical and aesthetic trade-offs are evaluated by the decision-maker in choosing an outdoor re- creational site. Impgrtance The importance of this research is to provide the decision-maker with a planning tool, which wil enable him to: l) inventory selected land and water resource characteristics, 2) establish community-priorities in the form of objective functions, and 3) select feasible sites which match the objectives of the community with the available resource characteristics. By examining available physical, economic, and aesthetic trade-offs for a geographic locale, it is hoped that the decision—maker can develop solutions which will optimally use the land and water resources of his area. The recreational land use selection model developed in this dissertation will first examine several physical and 3 economical traits which characterize the one-thousand-fifty- six cells within Orleans County. An aesthetic index based upon geographical and geophysical data will then be developed as an indicator of the aesthetic appeal of each cell for a potential campground. The model is designed to classify each land unit, one-square-kilometer cell, within Orleans County, based upon its individual economic data (property tax revenue loss or opportunity cost, development cost, and total cost), and based upon its generated aesthetic attractiveness (dependent upon water to land ratio , contour differential, type of color contrast within forested areas, and the amount of land which was forested). Using economic and aesthetic data, the selection model will then rank each cell at three levels of achievement, (low, medium, and high) for four individual objective functions, and then for combinations of three objective functions. The objective functions which will be used in combination include: 1) property tax revenue loss from the acquisi- tion of private land by the public sector, 2) the development cost of the facility, and 3) the aesthetic attractiveness of the cell for a year—round camping facility. Each classification pattern will appear as a computer map of Orleans County, showing a given objective function or multi- objective functions at either a low, medium, or high level of achievement for each cell. It will then be the decision- maker's prerogative to use the computer maps to aid in L; his selection of the feasible sites for the proposed camping facility. Objectives The primary objective of this research project was to develop a land use selection model for outdoor recreational planning which will assist public decision-makers in locating feasible recreational sites. In this study, a single activity, camping, was selected, since other activities may have specific characteristics and site attributes necessary in their site requirements. In order to stress the operations and utiliza- tion of the model as a planning tool, emphasis will be placed upon the model rather than upon the requirements of various outdoor recreational activities. However, further applications of the model to other outdoor recreational activities would be a logical extension of this research project, and will be discussed in the conclusions of this work. It has been decided that a full season outdoor camping facility will be the focal point of this model. An outdoor camping facility was chosen as the single activity within the study area because of its suitability to Orleans County land characteristics. The research centered around the development of a full season camping facility as a result of increased us- age and demand for year-round outdoor recreational facilities, (i.e. winter — snowmobiling, cross-country skiing; spring — fishing; summer — picnicking and swimming; autumn - hunting and fishing). As a result, the output of the model will be the selection of feasible camping facility sites within Orleans County. Therefore, the specific characteristics of full season outdoor recreational camping will be identified. The model will be calibrated to spatially analyze the economic value, the physical characteristics, and the aesthetic attributes of land within the county for such a facility. The model is a planning framework and is a tool to be utilized by local decision—makers to assist them in selecting feasible sites. Furthermore, it is hoped that in assisting them by spatially identifyinq and analyzinv the land characteristics, that decisions can be made to approach, if not obtain, optimality. As stated earlier, optimality can be derived by either maximizing a civen factor, or by minimizing a related factor, assuming specific goals. Therefore, optimality can be realized only when a Specific objective function is prescribed by the decision-maker. In other words, local planning agencies must isolate qoals, and then define related objective functions to reflect these goals. It is therefore imperative to state specific objective functions and simulate the spatial variations of location for an outdoor recreational facility. Community priorities become the specific objective functions and these are the important representative goals of the decision-maker. With the discussion of the primary objective presented as the development of a land use selection model for outdoor recreation planning, identifiable secondary objectives can be realized as by-products from the above-stated primary objective. Since the planning model is designed for county planning aqen- cies, the application of this model to similar counties to solve outdoor recreational land use selection problems is feasible. The utility of this planning model is greatly in- creased since its application to other counties or multi-county units is possible. Hopefully, further work can be initiated by other researchers and planning bodies to develop its utility. Outdoor recreational consumption has increased over the past decade, and is reflected in the high participation and l Increases in recreational visitation at recreational sites. demand have been projected into the future based upon current participation or visitation rates and socio-economic character- istics in our society. Shifts in demand have been predicted based on changes in per capita income, occupations, tastes and preferences, transportation accessibility, outdoor recreational 2 As a supplies, advertising, management, and population. result of shifts in the demand curve, influenced by the above factors, we may infer that outdoor recreational demand is increasing. With this phenomenon occurring, it is necesSary that the decision-maker be prepared to fulfill these desires both on a local level and in conjunction with adjacent regional population centers, affecting a county unit. It is assumed that, the source of revenue for the recreational facility indi- cates the clientele to be served within a local community. Therefore, a decision-making framework is necessary for the allocation of recreational lands, if we are willing to supply goods and services to meet either existing or future demands. lU.S. Outdoor Recreation Resources Review Commission, Outdoor Recreation for America (Washington, D.C.: U.S. Government Printing Office, January, 1962), p. 25. 2Marion Clawson and Jack L. Knetsch, Economics of Outdoor Recreation (Baltimore, Md.: John Hopkins University Press, 19E6), pp. 137-140. In analyzing land use within counties, marginal land be- ing utilized for agriculture, or forestry, is being phased out of production because of its lower productivity. The contri- bution of this land to agricultural or forestry returns is low. Marginal land neither provides high profits nor can withstand the collection of substantial tax revenues. We may in this planning model analyze these lands and suggest other uses based upon specific valued attributes of recreation. Ry isolating recreational product attributes for specific activities, we may insure greater economic and social rent from low value marginal lands. Finally, to allocate outdoor recreational areas and open space within a county, it is necessary to construct recrea- tional land use selection models. Increased land use pressures have made planners aware of conflicts and externalities. With- out an analytical framework to inventory land use character- istics and reflect community priorities, community desired land uses may be jeopardized. From the above paragraphs there seems to be a need for an outdoor recreational planning and decision model. Further- more, a model which can simulate community priorities and analytically portray the trade-offs of each decision can approach optimality in resource allocation. CHAPTER II RECREATIONAL PLANNING Previous Planning Methods and Models Outdoor recreational land use planning models have been developed by various levels of government, by private con- sulting agencies, by university research institutions, and stimulated by the needs of the local communities. The out- puts of these individual organizations range from federal plans, to state comprehensive plans, and to municipal plans of large and small communities. Outdoor recreational land use planning, in the theoretical sense, has occurred mostly within universities, where research- ers strive to design integrated planning models. Federal and state agencies approach planning with a broader planning theme which supports general public needs. Private consulting firms tend to either support agency directions or are utilized to identify specific recreation needs and problems. In general, two dimensions have been analyzed by outdoor recreational planners. First the temporal aspects of recrea- tion have been identified as recreational needs which are ex- tended into the future. The forecasting of outdoor recreation- al demand has been promoted by federal and state agencies in order to determine appropriations for recreational facilities. 9 10 Second, the spatial dimension, or the locational distribution of outdoor recreation develOpments, has generated attention. A necessity exists to balance the recreational desires of a population with the recreational resources available. Recrea- tional resource inventories have assisted planners in evalua- ting the spatial dimension of outdoor recreation. Within this study the spatial dimension will be emphasized, to pro- mote recreational planning. Furthermore, the author wishes to incorporate decision rules dictating the selecting of sites from a spatial array. In the past, spatial analysis of recreational resource information has been investigated or researched mostly by university personnel, but state planning agencies have begun to analyze these topics more recently. One of the most recent operational inventory analysis systems was developed by the Center for Aerial Photographic Studies at Cornell University, which classifies various land use information.3 This system, entitled the LUNR System (Land Use and Natural Resource System), was directly utilized by the New York State Office of Planning Coordination and has generated a series of reports concerning existing natural resources and land use characteristics. The resource inventory system utilized the SYMAP mapping computer routine developed by the Laboratory of Computer Graphics, 3Ernest J. Cole, A Review othhe New York StategLand Use and Natural Resources Inventory, Center for Aerial Photographic Studies (Ithaca, N.Y.: Center for Aerial Photographic Studies, March, 1970), pp. 1-52. 11 Graduate School of Design at Harvard University.“ This system utilized aerial photographs, 7% minute U.S.G.S. quadrangle maps and ground truth points to inventory resource data, then the data was coded to Universal Transverse Mercator grid coordin- ates, and transposed onto data processing cards. The SYMAP com- puter routine was utilized to visually display information for the clients' review. Classification of data was based upon the use and need for state, regional, or local planning and development. Fifty land use areas and seventy items of point data were derived from the selected resource materials. However, the potential capacity to incorporate other land uses and point data items has not been reached in computer utilization. The computer outputs appear as tabular lists and summaries of data, or else in a graphic presentation. From these outputs, aid has been given to local planners, planning boards, and cooperative extension agents at a cost which is less expensive than if collected on an individual basis. Hence, economies ofscale de- rived from a large data bank are possible within the LUNR system. Further description of the LUNR system defines three major computer programs with specific uses: 1) DATALIST I, 2) PLANMAP II and 3) PLANMAP III. The DATALIST I computer program prints out a tabular listing of area or point land use data with supplemental or with combinations of data.5 DATALIST I “Howard T. Fisher, §2MAP Mappinngechnigue, A Report from the Laboratory for Computer Graphics at the Graduate School of Design, Harvard University (Cambridge, Mass.: Harvard University, 1967). 5N.Y., Office of Planning Services, New York State _d Use and Natural Resource Inventory: What It Is and How it Is Used (Albany, N.Y.: Office of Planning Services, September, 19715, P. 10. 12 minimizes inaccuracies since it records and displays specific point information. Application of this program has been util- ized by researchers at Cornell university to analyze watershed and land use characteristics adjacent to the Finger Lakes of New York State.6 From this information, environmental impacts resulting from land use changes can be measured and compared from point information along watersheds. The PLANMAP II computer program makes use of computer graphics as a device to display patterns and geographical interrelationships.7 Ten grouping levels of information can be derived and displayed. As a result of groupings, some detail and accuracy is lost; however, a decision rule may be employed to select desired cell characteristics. Hence, locational patterns of cells can be produced reflecting variate interaction. This is an important addition to land use planning since it allows the researcher to simulate specific guidelines and land use standards. Therefore, the spatial dimension of resource analysis has been strengthened by this pregram. Specific application of the PLANMAP II program to outdoor recreation problems has been conducted by the New York 8 State Office of Parks and Recreation. The major objective of 6David Child, Ray T. Oglesby, and Lyle S. Raymond, Jr., Land Use Data for the Finger Lakes Region of New York State, Report for the Water Resources and Marine Sciences Center, No. 33 (Ithaca, N.Y.: Cornell University, March, 1971), pp. 1-29. 7New York State Land Use andflgtural Reggurce Inventory: What It Is and How It Is Used, p. 13. 8Stephen 0. Wilson, et, a1. Potential Recreation and Qpen Space Areaspin New York State, N.Y., State Office of Parks and Recreation, Technical Paper No. 6 (Albany, N.Y.: Office of Parks and Recreation, July, 1970), pp. 16-18. 13 a specific study by the above agency was to indicate potential open space and recreation areas on a statewide basis. Indica- tor cells represented specific resource characteristic combin- ations yielding favorable sites for future sites. Finally, the PLANMAP III program is a refinement and extension of the existing PLANMAP II and DATALIST I programs.9 Its application and development has not been extensively used within the state, since experimental work is still occurring at this time. However, in general, PLANMAP III incorporates greater simulation potentials toward recreational land use planning strategies. An increased number of decision rules may be written as pregram statements, allowing the manipulation of more land use variables. As the PLANMAP programs become more sophisticated, we may approach optimum land use planning for outdoor recreation at the local, regional and state levels. Further development of resource information systems has occurred within the State of Illinois. The University of Il- linois at Champaign-Urbana has developed the Natural Resources Information System, (NARIS), under the ILLIAC IV Project and in conjunction with the Northeast Illinois Natural Resource Center.10 NARIS stores and retrieves information from forty- acre tracts or quarter-quarter sections in the rectangular sur- vey system. Data are collected for eight resources and land 9New York State Land Use and Natural Resources Inventory: What It Is and How It Is Used, p. 21. 10Daniel Slotnick, Natural Resources Ingprmation System, Report of ILLIAC Iv Project, (Champaign-Urbana, 111.: North- east Illinois Natural Resources Center, 1970). 1h characteristics: soils, geological features, ground water and surface water, forests, climate, water impoundments, topog- raphy and land use. The outputs of NARIS fall into three areas based on spe- cific clientele and intensity of utilization. The Inventory Listing is the first level of computer output. It simply lists the natural resource corresponding to specific identifiable 11 From this information tracts or quarter-quarter sections. listing, a simple description of the conditions related to the existing resources are presented to the user. Secondly, the Technical Description of the recorded re- source is provided in order that the user may become familiar with detailed characteristics of the resource.12 In essence, technical descriptions serve as a library file for the analysis of individual resources. Thirdly, the Report—Interpreter serves an interpretation function for the user of NARIS.13 The design of this program is oriented towards the layman who may be analyzing a site for development. Whereas the technical description program is directed to scientists familiar with the detailed character- istics of a selected resource, the Report-Interpreter assists user groups in the analysisenuiimpacts of the resource char- acteristics. Extension of NARIS to the National Environmental Data llThomas P.L. Dowell, Jr., NARIS: A Summary Report of the Natural Resource InventoryiSystem, (Champaign-Urbana, 111.: University of Illinois, July, 1970), p. 4. 12Ibid., p. U. 13Ibid., p. a. 15 Rank was proposed in June, 1970.14 According to this pro-' posal, the system structure would be expanded to a national level at an investment and Operations cost of seven to ten million dollars per year. Thus far, the proposal has not been accepted. Furthermore, budgetary problems within the State of Illinois have not allowed NARIS to advance rapidly. This sit- uation may be explained since the benefits of the system are not clearly defined to the political decision-makers. The State of Indiana has promoted the development of the Indiana Information Retrieval System (INDIRS).15 This is a statewide time-sharing information system consisting of socio- economic data files in conjunction with statistical and display programs. Socio-economic data are available for Indiana's ninety-two counties, two-hundred-and-seventeen selected com- munities, and eleven Standard Metropolitan Statistical Areas. Fourteen classes of information are available on a county basis which are derived from county census abstracts, retail trade, and Indiana school districts. The spatial dimension of the system is not uniform since information is generated from_ socio—economic modes such as communities, Standard Metropolitan Statistical Areas, and economic regions. The output of the information system is primarily a list of data or information statistically displayed for summary purposes. The output is primarily oriented towards users having specific training 1“Ibid” p. 4. 151ndiana Information Retrieval Systeg, Division of Research, Graduate School of Business (Bloomington, Ind.: University of Indiana, Graduate School of Business, 1970). 16 in associated resource information. Further capabilities of the system have not been identified since the initial impacts of the system have not been evaluated. The Canadian Governmentluusinitiated a spatial resource analysis for outdoor recreation oriented towards capability classification.16 The objectives of the land capability classification were to inventory, identify, classify in relation to type, and to provide information for policies and decisions to be made by national and local governmental units. The classification was derived from a stated premise by the Canadian Government as follows: Basis of Classification... is the intensity of use or average annual total quantity of user per unit area which could be generated under perfect market conditions and sustained by an area or recreation feature.17 On this basis, outdoor recreational activities were selected and potential outdoor recreational sites were evalu- ated in relationship to the activities requirements and in conjunction with market structure. ~Outdoor recreational capa- bilities based upon user intensity, are classified in seven classes ranging from very high capability to very low capabil- ity. Class 1 lands have natural capability to attract and sustain very intensive use. Class 7 on the other hand, classi- fies land with practically no natural capability for any 16G .A. Hills, The Ecological Basis for Land-Use Planning, Ontario, Ontario Department of Lands and Forests, Research Report No. 46, (Toronto Ontario: Department of Lands and Forests, December, 1961), pp. 1-204. 17Ibid., p. 123. 17 popular types of recreation activity due to an almost total lack of recreation features. Benchmarks and guidelines util- izing measurement units such as lineal and aerial miles of navigable water, water temperatures and ranking qualities, slope percentages, and forested land type percentages were objectively formulated in order to classify. Subjective inputs were integrated into the system in order to identify unique outdoor recreational features. Symbols indicate the classes, dominant recreation features, and a color coding indicated the classification in map form. Legends and a narrative of up to one thousand words may occur in providing supplementary user information. Federal agencies within the United States, specifically the Soil Conservation Service, has formulated a framework for appraising the potential of outdoor recreational developments. It has constructed guidelines based upon climate, scenery, and scenic areas, natural areas, historic areas, soils, water, wildlife, populations of people, proximity and access, and rural ownership and land-use patterns. Within each of the above areas, kinds of activities associated with each area were eval- uated and numerical weights assigned to each. A higher numer- ical weight was given to positive climatic characteristics or a site which provided greater utilization for vacation camp- grounds rather than sites which provided limited seasonal uses. The numerical rankings of the sites were accomplished through group judgement. The reliability and accuracy of site evalua- tion depends heavily on the knowledge of the natural resources of the area by the selected appraising panel. The composite 18 rankings for specific activities or area site evaluations are only indicative of the level of opportunity. Subjective anal- ysis was also a necessary component associated with the ordi- nal classification scale. Application of this technique to evaluate outdoor recreation potentials has been conducted in various counties in the country. The Soil Conservation Service of Jefferson County, New York has conducted an investigation into twelve kinds of outdoor recreational develOpments.18 The outputs of the study include improvements in a long-range V recreation program, information generating financial needs for recreational developments, and information identifying project proposals. The study area under investigation has been apprais- ed by the Soil Conservation Service framework. The Cooperative Extension Service of Orleans County has computed composite scores for the previously defined areas and recreational ac- 19 Identification of the recreational areas and tivities. their evaluation resulted. Air photo coverage assisted in identifying the recreational potentials and the existing activities being participated in within the county. Land use information systems have been proposed by govern- mental agencies and by university researchers. Generally their 18Donald J. White, An Appraisal of Potential Outdoor Re- creational Develgpments in Jefferson County, New York, U.S., Department of Agriculture, Soil Conservation Service and Co- operative Extension Service, (Nashington, D.C.: Government Printing Office, February, 1966), pp. 1-80. 19Orleans Recreation Committee, Appraisal of the Committee, Potential Outdoor Recreational Development in Orleans County, (Orleans County, N.Y.: Cooperative Extension Service, 1971), pp. 1-2u. I1 19 success has been limited by high costs resulting from data col- lection, computer hardware and low user demand. To verify this point, the Environmental Data Bank, proposed in the 91§E_Ses- sion of Congress, was designed to collect data relevant to the environment, and to analyze legislative proposals, executive proposals, and those submitted by states in order to determine their impact upon the environment. The comprehensive analysis of environmental data planned for this board was too large an undertaking. Its weaknesses included unnecessary collection and analysis of a complete data system, rather than the use of standardized techniques of sampling and analysis which would permit comparisons; duplication of information previously collected by the Council on Environmental Quality and the Office of Environmental Quality, dependence on other agencies for information and computer facilities; storage problems; time 0 This type of land use information system failed and cost.2 because of its massive size, its concern for over detail, and its costs in time, labor, and hardware. Suggested reasons for failure of land use information systems are based on low user demand.21 These include: 1) public skepticism, 2) irrelevance of the master plan to com- munity needs, 3) communications gap between the designer and ZOEnvironmentalQata Bank, Hearings, before the Subcommittee on Fisheries and Wildlife Conservation of the Committee on Mer- chant Marine and Fisheries, pp. 25-26. 21Dwight F. Bettie, "Plans Don't Work; PeOple Do," Elements of Outdoor Recreation Planning, edited by B.L. Driver, (Ann Arbor, Mich.: University Microfilms, 1970), pp. 299-307. 20 the community, and h) non-availability of the information designer for help in application of the plan. The data collection costs are often so high in these large land use information systems that the economies of scale obtained from high use is never realized. Political differences between governmental bodies have in- duced problems in data standardization and integration. The inefficiencies of the Environmental Data Bank in part resulted from this dependence, whereby all other legislative and execu- tive agencies had to supply their environmental facts and per- mit the board use of personnel and computer hardware in ana- lyzing the information received. Further analysis of recreational land use planning in- dicates that there are specific philosophies involved in individual planning methods. These philosophies may have ecologic, economic, or aesthetic themes directing land use decisions. The utilization of these philosophies has been extended to general land use models encompassing basically all types of land use. However, recreational land uses are an important portion of the general planning designs. In order to analyze recreational planning models, it is necessary to classify the models as related to the above philosophies. Ecological land use models are based upon a knowledge of the biological productivity of natural resources. The object- ive of the models is to correlate the ecological base of land with a correspondinr land use. From this relationship, an use—capacity can be determined which allows the renewable 21 resource to be in phase with the land use. In recreational land management, the physiographic and biologic features of an area must be maintained at a productive level in order to conserve the resource base. A "safe minimum standard" has to be determined in order to effectively plan recreational uses.22 Another facet of recreational land management is the aspect of man-management. Since the ecology of an area is an important criteria in planning, man's behavior affecting the environment is the important component of land use model analysis. Selected ecological land use models will be analyzed and their applica- tions to recreational planning investigated. One of the early ecological recreational land use models was designed by the Ontario Department of Lands and Forests.23 The model identified a step-wise procedure to assist in the allocation of land uses based upon ecological constraints. Eight steps have been formulated with the first step identi- fying the spatial pattern of the physical components; second step, presenting uses of the physical components; third step, establishing the use-capability ratings; fourth step, mapping of use-capability classes; fifth step, potential of land use; sixth step, recommendations for uses; seventh step, proposed scheduling of land uses; and eighth step,progress of land use planning recommendations. The recreational land use model 228.V. Ciriacy-Wantrup, Resource Conservation Economics and Policies, (Berkeley, Calif.: University of California Press, 1938), Chapter 18. 23G.A. Hills, The Ecological Basis_£or Land-Use Planning, p.123. 22 proposed by the Ontario Department of Lands and Forests can be understood from the above step-wise sequence of planning and site selection procedures. Further construction of ecologically based planning models have been produced at the University of Pennsylvania by Ian L. Mo Harg.2u The major objective of his model is to determine the degree of compatibility for multiple land uses based upon ecological impacts. The model identifies a matrix in which the physical requirements of land uses are aligned with the ecological constraints of the given study area. With this inventory completed, proposed land uses are compared with each other, and compatibility derived. From a matrix of compatibilities, suitable areas are located within a given study area. The matrix includes a correlation between urban, suburban residential, industrial, institutional, mining, quarrying, vacation settlement, agriculture, forestry, recre- ation and water management. The model identifies six recrea- tional uses: salt water oriented, freshwater-oriented, wild- erness, general recreation, cultural recreation and driving for pleasure. From this identification of recreational land uses, recreational activities are located within a study area based upon their ecological constraints and their compatibility to other land uses. Again, the physical landscape is the most influential element within the ecologically based planning models. zulan L. No Harg, Design With Nature, (Garden City, N.Y.: The Natural History Press, 1969), pp. 1-195. 23 Ecologically based models have been greatly supported in current times as a result of a recent insurgence for environ- mental quality. The Mc Harg model is the most recent ecological planning model. However, the Philip Lewis model, and the Angus Hills model also contribute to ecological base planning.25 Each method utilizes the natural physiographic unit as a planning base for land use decisions. The second philosophy is based upon economic factors concerning land use decisions. The economic objective involved in land use planning is based upon the maximization of social welfare and monetary returns from either public or private investments. This is accomplished through planning which seeks to minimize development costs, transportation costs, acquisition costs, management costs, public tax loss, or opportunity costs. Furthermore, monetary returns can be increased, by stimulating demand, providing a pricing structure which satisfies effective demand, and satisfying option demand for recreation. Generally, economic based land use models either tend to minimize distance to the market place or increase output at point of production, or minimize all transfer costs, or supply effective demand. Simulation has been utilized to determine effective demand areas for recreation in the State of Michigan in order to plan existing and future facilities. The BECSYS--SYMAP model at 25Belknap, and Furtado, , "The Natural Land Unit as a Planning Base," Landscape Architecture, LVIII, No. 2 (February, 1968), p. 136. 24 Michigan State University was utilized to simulate origins and destinations of recreationists.26 A system design utilizing electrical engineering principles helped simulate the gravitational interaction of recreationists, hence identifying potential demand areas.27 Econometric models have been derived to approximate re- creation demand in order to plan and budget recreation facil- ities.28 Given a number of predetermined variables during a given time period, economic theory is combined with statistical analysis to simulate a demand relationship for recreation. This demand relationship can then be applied to population distribution information indicating recreational planning needs. The results of this study can be applied to effectively ful- fill recreational demand since the study encompassed a pricing structure. Economic based recreational land use planning models have also been developed by the U.S. Forest Service. The economic concerns of recreational land use planning has become increas- ingly important since recreation is coming into conflict with other forest land uses. In a paper, George A. James stated 26Michael Chubb, Outdoor Recreation Planning in Michigan by_a Systems Analysis Approach, Part III, State Resources Planningfi Program, Technical Report No. 12, (December, 1967). 27John 8. Ellis, Outdoor Recreation Planning in Michigan by a Systems Analysis Approach, Part I, II, Technical Report of the State Resources Planning Program, No. l and 7, (East Lansing, Michigan, May, 1966). 28Robert J. Kalter and Lois E. Gosse, Outdoor Recreation in New York State. Projections of Demand, Economic Value and Pricinngffects For the Period 1970-1985, Special Cornell Series, No. 5, (Ithaca, N.Y.: New York State College of Agriculture, 1970). 25 that, The need to gather reliable information about our recreating public - the kind and amount of use that occurs and the places where this use occurs - is urgent and critical. It will never subside. The things that we need to know a great deal about are becoming more numer- ous and more complex because more people engage in more activities more frequently on more developed sites and more classified areas with more kinds of facilities cost- ing more money and occupying more land and more water under more intensive management while more stringent budgetary requirements demand more specific information to satisfy more public interest in more types of programs. coordinated with more agencies involved in more efforts.29 Hence, the economic impact of land use decisions affects the public and private sector, because recreation is produced by both. Recreational develOpments cause changes in a county's or community's infrastructure since it is necessary to supply services to an incoming transient population. As reflected by the above quotation, the adjective "more" seems to be a com- monplace term in recreational planning. The economic impact of this phenomenon has to be considered, hence, researchers have devoted energies towards investigating economic relation- ships. An earlier work written by Beasley concerns the optimizing of public forest recreational investment.30 He identified recreational values derived from public investment in forested areas. The values were related to greater physical health, better mental hygiene, education and cultural effects, and 29George A. James, "Inventorying Recreation Use," Recrea- tigngymposium Proceedings, State University of New York College of Forestry, (Syracuse, N.X., October, 1971). 30Ronald I. Beasley, "Some Considerations for Optimizing Public Forest Recreational Development and Value,“ Journal of Forestry, LIX, No. 9 (September, 1961). 26 31 the immediate satisfaction of consumption. In other words, utility value is generated from participation in the recrea- tional activities and expected future value may be realized. Further monetary benefits may be determined if prices can be attached to recreational products. If recreational products are priced, the public and private sector may be able to deliver those goods and services in which the public has truly expressed demand. Furthermore, the costs of producing recreational goods and services can be supported by the participating user groups. Consumer surplus, or the difference between total utility and total market value, gross dollar volume of business or income, monopoly revenue, or contrived scarcity, and visitor expenditure surveys all attempt to price recreation so that a monetary value can be estimated.32 The majority of the research directed towards recreational development have been brought to the forefront. It is necessary to ask the question, what does it cost the taxpayer to provide public recreation? In a case study conducted by Manthy and Tucker, the supply costs for public forest land recreation were analyzed.33 The researchers simulated a supply model identifying the production costs and the consumption costs Bllbid. 32Wendall Beardsley, "Economic value of Recreation Benefits Determined by Three Methods," U.S. Forest Service Research Note, RM-l76, (1970). 33Robert S. Manthy and Thomas L. Tucker, Supply_Costs for Public Forest Land Recreation, Michigan State Agricultural EXperiment Station, Report No. 158, East Lansing, Michigan, March, 1972, (East Lansing, Mich.: Michigan State University, 1972). 27 of recreation. The production costs were cost of capital improvements including land acquisition, facility construction, and improvement and major repair expenditures. Production costs also include operating expenditures which encompass maintenance, equipment, salaries, and other operating costs. The summation of the above costs are referred to as the direct costs to the producing agency. The consumption costs to the consumer of recreation are defined into two major areas: 1) associate cost and 2) threshold cost. The associate costs include user fees, equipment costs and trip expenditures; whereas, threshold costs indicate the minimum amount of equip- ment necessary to recreate. The study adds a needed dimension for recreational land use planning. However, this investigator feels that the direct costs are the major costs to be considered by the community when deciding the location of prospective recreational sites, since it comprises a higher proportion of total recreational develOpment costs. The third philosophy of recreational land use planning is aesthetically based. With this emphasis, recreational land values are identified and utility is derived from their existence. Specific plannin: models such as those derived by the Uhited States Forest Service have helped promote the aesthetic values important for the recreational experience. Recreational aesthetics derived from the landscape indeed provides utility to the consumer. Research has been conducted to measure landscape qualities which have provided recreation- ists the greatest satisfaction for a single recreational experience. Shafer and Mietz attempted to quantify scenic 28 photographs in order to predict preferences from recreation- ists.3“ A landscape-preference model was deve10ped and tested using recreationists in New York and Utah as subjects. Eight zones were defined within a landscape photograph and randomly selected day-users were asked to rank the photographs. Using this ranking procedure, landscape tastes were recorded and pre- ferences summarized. Thus study helped gain a statistically valid estimate for recreational landscape preferences. It allowed the consumer to select that recreation output that he valued the most. Visual analysis of the landscape becomes an important facet in evaluating aesthetic qualities. Twiss has identified six factors of observation and scenic composition which he ranked in descending order. The factors are: 1) distance 2) light 3) topographic form and contrast a) spatial definition 5) observer position and 6) sequence.35 Distance was divided into planes or grounds; light considered on a diurnal and . seasonal basis in conjunction with direction and intensity; topographic form and contrast related to visual focal points and areas of structural landscape framework; spatial defini- tion corresponding to a composite relationship; observer position concerning perspective; and sequence of observer positions in viewing the above factors. The research presents 3”Edward L. Shafer, Jr. and James Mietz, It Seems Possible to Quantify Scenic Beauty in Photographs, U. S., Department of Agriculture, U. 8. Forest Service, Forest Service Research Paper NE-l62, (Northeastern Forest Experiment Station, 1970). 35Robert H. Twiss and R.B. Litton, "Resource Use in the Regional Landscape," Natural Resources Journal, Vol 6, No. 1, (January, 1966), p. 212. 29 an abstract approach to visualizing scenery and can only be utilized as a framework for further classification and quantification. An attempt to quantify scenics was formulated by Leopold in an analysis of a river valley.36 Leopold's work was developed from a concern based upon environmental disputes in Congress. He stated that: The time has come when the argument of the environ- mentalist might best be presented by (l) separating facts from emotions in relation to the environment, and (2) by providing him with a means of quantifying his arguments: using numbers to talk about the landscape. While to some of us this may be a little like using a computer to de- scribe Shakespeare, it seems that society still has the right to have all aspects of any pr0posed development 37 represented in a way that is as objective as possible. From this basis, an analytical model was constructed evaluating the aesthetic qualities of sixteen river valleys from a forty- six factor checklist. Descriptive categories were utilized to include physical factors, such as river width; biologic and water quality factors, such as water color; and human use and interest factors, such as vistas. From the forty-six factor checklist, each river valley could be ranked by an ordinal scale to indicate relative aesthetic importance. A total uniqueness ratio was computed as the objective measure for further decision making. Hence, perceived aesthetic values viewed by recreationists gained objectivity and a definable dimension. Landscape descriptions and inventories have become im- 36Luna B. Leopold, "Landscape Esthetics," Natural History, (October, 1969), pp. 37-44. 37Ib1d.. p. 37. 30 portant components for land use planning and design. Litton and Twiss, in conjunction with the U.S. Forest Service, and with previous research as described earlier by Twiss, expanded upon the visual factors of scenery.38 The simulated pictorial examples describing the visual factors of a landscape so that designs could be utilized for future recreational sites. Scenic corridors were planned with corresponding zones based upon the selected factors. Application of the visual aesthe- tic qualities were taken into consideration in recreational land use planning design. The above studies have been reviewed in order to classify recreational planning land use models. In order to discuss these models it was necessary to classify them in a rational manner. However, it must be recognized that overlaps occur between models as philosophies are somewhat integrated. How- ever, it is the author's contention that the degree of inte- gration between philosophies has not reached a level to ap- proach optimal planning decisions with assumed goals. It can be inferred that each model still attaches itself to a specific discipline within the scientific structure of knowledge. In summarizing the preceeding analysis of outdoor recreational land use planning, the investigator has chosen to research the subject by: l) analyzing governmental and insti- tutional recreation planning, and 2) reviewing specific re- creation land use models. From this analysis, inferences are 38R.B. Litton and B.H. Twiss, "The Forest Landscape: Some Elements of Visual Analysis," Proceedings, Society of American Foresters, (Seattle, wash.: 1966)} 31 derived related to recreational land use planning in general. First, recreation models are not linked to a decision~ maker or do not allow the decision-maker to analyze tradeoffs between decisions. Although recreation models provide trade- offs for decision-makers, most local and federal planners can- not use this service. As a result, the application of valid models is reduced, since the decision-maker is excluded from the planning process. If the planning models do not take into consideration the decision-maker, it is difficult to transfer the strengths of a model to a given client. Therefore, the optimality expressed by a land use model cannot be realized or the model is discounted by the decision-maker because he does not understand its structure or its implementation. The researcher becomes frustrated since the decision-maker does not take into account a newly discovered planning device. Also, the decision-maker feels that the researcher's model has little application since it does not relate directly to his problems. Hence, a separation between agencies, universities, researchers, and communities occurs. It is the investigator's contention that recreation land use planning models should be designed to describe the trade- offs or consequences of alternative decisions, rather than make a specific decision for the decision-maker. It is a researcher's function to present information in such a way that will allow the decision—maker to make a better decision. In this context, a better decision is one which more nearly satisfies the objective function as contrasted to a "less better" decision. HOpefully, the decision-maker represents 32 the public and reflects their priorities and community goals. It is the researcher's job to reflect the impacts and trade- offs produced by land use decisions, or, to simulate community priorities and describe the trade-offs occurring between priorities. An attempt was made in the study described in this thesis to simulate community priorities and derive objective functions to express these priorities. The purpose of the model devel- oped in the study was not to select a specific priority, but to select a series of priorities and then analyze their spatial interaction. The model assists the decision-maker in selecting an optimal decision, based upon the community's objective function. Second, in order to seek an optimal solution in recrea- tional land use planning, an interdisciplinary analysis ap- proach must occur. In other words, it is necessary to inte- grate physical, economic, and aesthetic factors into an ana- lytical framework. In such an analytical framework, commun- ity priorities may be matched to the above factors and compar- isons made. An attempt to integrate these is made in the following model design. The following section of Chapter II I will explicate those components to be analyzed by the model, including the physical, economic and aesthetic characteristics of Orleans County, New York. It will spell out the simulated priorities of the community. In addition, the analytical design of the model will be outlined and explained. 33 Proposed Outdoor Recreational Land Use Selection Model The design of the proposed model is based upon specific assumptions as specified below. Since many recreational land uses occur and compete for space it is necessary to select a specific activity. Furthermore, various delivery systems sup- ply recreation for various clientele. Therefore, it is neces- sary to define the clientele, and to identify the delivery system's characteristics. However, the model has the capability to analyze other recreation activities by adjusting its parameters. For this investigation, the author has chosen a county government as the client. The study is designed to select areas for outdoor camping, and to have the facility developed using public revenues. It can be further stated that the output of the model is a presentation of computer maps displaying feasible sites for campground development.‘ These maps can be utilized by decision-makers in choosing the site for a local camping facility. The clientele of the new facility are the populus of Orleans County, which is repre- sented by county government. The sources of revenues include appropriations from the county, state or federal budgets, or combinations thereof. Given these assumptions, the objectives of the model may be outlined. Latertflkalogic used to deveIOp the analytical framework of the model will be reviewed, and its mechanism or workings identified. The model is based upon an objective statement, which states that in order to approach Optimal recreational land 34 use planning, it is necessary to simulate community objective functions and linkages to the decision-makers, and to integrate the physical, economic, and aesthetic factors of land resources. The first portion of the statement relates to the theoretical concept of optimality. It is the investigator's contention that optimality is related to the priorities of the community. There- fore, if a model seeks to fulfill community priorities, we indeed approach an optimal situation. Ne must assume that the decision-maker represents those community priorities and that he opts to fulfill them. The fulfillment of community priorities is considered to be the goal to be maximized in this study. Furthermore, we must also assume that the physical, eco; nomic and aesthetic elements are the resource components to be analyzed. It is from these components that the community wishes to select a product mix. Therefore, to approach optimality, an outdoor recreational land use planning model must allocate the above components in such a way that it yields an output which satisfies stated community priorities. The model expresses trade-offs between the components of land resources and community priorities. It must be understood that as we increase the utilization of one component we must decrease the utilization of another or substitute one for the other. Therefore, as community priorities shift to a different product mix, the combination of resource inputs adjusts accordingly. A community and decision-maker must accept the fact that it is necessary to give up derived values from one resource characteristic as the community's priorities change. 35 Ilence, in order for decisions to be made correctly, trade- c>ffs must be exnressed and weiihed analytically. The model identifies proposed community priorities as c>hjcctive functions. The objective functions are derived from sypecific variates measuring the physical, economic, and aesthe- t;ic components. The objective functions either minimize or zvmaximize a prescribed relationship. In order to spatially analyze the land resources of a grjsven area an inventory system must be constructed. Further— rncxre, a spatial analytical framework is necessary for solvins T>rwescribed objective functions and selecting recreational land Liane sites. In order to integrate the components of land re- EHDiirces, a simulation model must be constructed to present "blues objective function, integrate the components, and simulate <3GoUsmA aoHHom scape: soHQH< ”magnoo msmoapo manna: uncappmflp Hoonom Hmsdfi>aan moaado mcfipmcnesooo Noe mpcsoo mzmmaso momma do>opaafi so 03Hm> ummmomwm sow Hamo pom pseudosp pea mamaaom momma po>opgsfl no osHm> commommm you Haoo pom mpmHHom maaanBOp use mussoo pom menus xme mpCoEm>osmEH Spa: osam> mama pmmmmmm¢ mpacb moHQMapm> pom pcoaoLSwmoz mo oopsom wads: psosopdmmoz moanmanm> mmoq osmo>om was appomopm mo :oHpmNHEHsH; ”sowpocdm opapoonno mmoq szm>mm Xselect only those cells expressing low property tax revenue loss. The output of the model is a graphic display by the GRID mapping routine of those feasible cells. The output will be classi- fied into three cost levels of information representing low, medium, and high property tax loss. Those are mapped by com- puter shading techniques: low property tax loss darkest, 50 medium property tax loss intermediate, and high property tax loss lightest (see Table 3, p. 178 in the appendix). From this display specific cells may be pinpointed and located by Universal Transverse Mercator Grid ticks on United States Geological Survey maps or New Kork State Department of Transportation maps. Each cell can be identified by a latitude and longitude position. The southeast corner of the cell is represented by the latitude and longitude reference point. The second objective function states that in order to optimize it is necessary to minimize development costs associated with the initial support of the recreation facility. As mentioned earlier in Chapter II, the investigator identified land acquisition costs, drainage costs, and transportation construction costs as the major cost areas for deve10pment. Realizing that these costs vary spatially, the investigator determined feasible measurement units for each (Table 2). Iand acquisition costs varied with location and market demands; therefore, variations with the market place caused difficulty in selecting a model indicator. Sales information collected from lands which were purchased by public agencies for recreation deve10pment could be used to estimate acquisition costs. It was assumed that sales information would reflect true market value and hence, acquisition costs for similar land could be estimated. But when sales information was lacking, the investigator utilized an adjusted full assessed value for each cell. In analyzin: assessments, it was found that property was assessed at a proportion of its full value. This being the case, all assessed land alues were adjusted 51 pmmEupmmoQ mezzaam massoo msmoano Goflpm>aomsoo Hmpnmasohfl>sm mo unosupmmmm mumpm xnow zmz oofi>aom soapm>pmm .200 can godpmuaaapmpm HwnSpasoanaa mmpmpm amuse: ooa>aom :oHpm> -hmmeoo Haom ampsum omens: moaaao ashameaahooo xme mucsoo mammaao flame pea mmzsmax mgapmaxo umonmon on HHmo mo pounce Sosa umoo soHpOSLQmsoo cosmpch was: pom mamaaom soapmphoamcmpe HHmo pom soapmHOOmmm HflOm pom pmoo mcflafip mo mamaaom pmoo mammamnq Haoo pom gouomm pmoapmsnpm mmamm Haoo pom unoopmm SH mums Cofipmwflaasvm HHmo Log mpmoao>oaaEH :paz czam> pgma pmoo pmpmznpm pom mamaaoc sofipflwfisoom pmmq mean: my .EQEGLSWMQZ .HO ®OLSOW mmapmfipm> pom mpanz psosoaSmmmz mmapmflpm> pmoo pgoaaoao>om mo coflpmufisflgflz “soflposzm m>Huoonpo Bmoo Bzmzmoam>ma N mqm<9 52 by dividing the percentage of assessment, i.e. 70%, 50%, 40%, 60%. These full property values were then taken to be the acquisition cost which would have to be paid by public agencies in order to purchase property for public recreational develop- ment. Therefore, the average per acre full assessed value for each cell was multiplied by 247.1 and then divided by the appropriate percentage, thereby yielding acquisition cost. Within the model, drainage cost was utilized to determine part of deve10pment cost. Drainage cost indicated to initial physical condition of each cell under site consideration. It indicated the drainage improvements necessary in order to make possible the development of a recreational facility. Since water supplies and sewage systems for a campground may be inter- lactive with the natural drainage characteristics of the site, development costs tend to vary with drainage conditions. In poor— ly drained areas, sewage pump storage systems may have to be designed topreventeffluent from reaching streams. It is assumed therefore, that a spatial relationship occurs between the natural drainage characteristics and the investments in sewage systems. Furthermore, roads leading to and within campground areas may incur added construction costs if poor drainage occurs. Additional road fill, water sluice ways, tiling, and parallel road ditches also increase the development cost total. It is therefore assumed that drainage may be a proxy for determining one portion of development cost. Since physical factors such as soil characteristics, geo- logical characteristics, and parent materials affect drainage, V1 k0 variations occur within the study area. The evaluation of drainage costs is a complex undertaking; however, in order to investigate recreational development on a county basis it was necessary to seek out a feasible measurement unit. It was determined that tile drainaje costs would provide an appropriate drainage cost indicator. Therefore, an attempt was made to estimate tiling costs throughout the county, hoping to reflect the spatial variation of the physical factors. However, it was necessary to identify physical landscape units which could be classified by some physical criteria and correlated with tiling costs. It was decided that soil associations would be utilized to delineate areas and that tiling costs could be estimated for these soil associations. Once soil association boundaries were identified and aligned on county maps, tiling costs were estimated by analyzing tile drainage costs within each soil association. With assistance from United States Soil Conservation Service, agricultural drainage costs were reviewed and estimates formulated. Thus, drainage costs were assigned to each cell corresponding to a specific soil association. These values were utilized as a proxy in order to estimate recreation drainage costs since no specific costs were available for recreation on a county basis. Highway transportation construction cost is the final cost recognized in this study that is included in the category of initial development cost. It is generally recognized that highway construction cost is an important factor which may 54 influence the location of recreation facilities. In order to estimate highway construction costs specific criteria must be established as a measurement unit. The investigator realizes that highway construction costs vary as a result of physical factors affecting construction. However, to calibrate a model and measure the variation is a difficult undertaking. There— fore, the investigator sought to evaluate construction costs on a distance basis. It was decided that these costs would be estimated by determining the distance from the center of each cell to the nearest existing highway facility. Measured distance could be multiplied by the per mile cost estimate to yield the highway transportation construction cost per cell. The per mile cost estimate was formulated through correspond- ence and personal discussion with personnel of the Orleans County Highway Department and the Environmental Conservation Department of New York State. As stated previously in Chapter II, the third objective function analyzes the minimization of total cost as defined above. Therefore, a summation of property tax loss or opportunity costs, acquisition costs, drainage costs, and. transportation construction costs yield the total cost re- presented by each cell (Table 3). The total costs will be classified into three levels of variation. low, medium, and high cost levels will be identified within the resource in- ventory framework superimposed over the study area. As before, the GRID computer mapping routine was used to graphically dis- play spatial relationships. It can be inferred that the major costs have been defined for the selection and deve10pment 55 'of a recreation camping facility, although it is recognized that additional costs may occur during the planning and devel- Opment of such facilities. The above costs were selected to represent the economic component associated with land resource developments. The fourth objectuve function is based on the identifi- cation of aesthetic values in order to maximize socially re- ceived benefits derived from the physical component of land resources. In evaluating the aesthetic features within land resources we may be able to assign measurement units to each of the attributes so that a spatial analysis can be initiated. The investigator has isolated specific attributes which would yield a more aesthetically pleasing outdoor recreational ex- perience for most camping families. The aesthetic values of an outdoor recreational site are related to the physical and social factors contributing to the site. The physical factors reflect a visual quality which in turn yields an aesthetic experience. Consequently, those physical factors which provide the recreationist with a visual quality at the campsite, will be those analyzed in the aesthetic index (Table 4). mofipc>smmsoo Housmssopfl>sm mo uncappmacm mpmpm apow zmz moa>smm soflpm>amm Icoo use soflpmmflaabmpm Hawspaonsma mmpmpm amuse: oofippmm soflpmppmm taco Haomzmmpmpm embeds «cacao weapmcaesooo xme zpcsoo mammaao Hamcccg oHHH>Coosaq smaaom meadow 5 832 Hapcsoo mcmcapo Saguflz mpoflppmao Hooxom Hm5©H>H©CH meacao snapmcaewooo xme mpcsoo mammfimo mumoo Haoo boa mmmHHom acoaaodo>oa mmOH ®SC®>®L HHoo Log mamaaom xmp appoaoam mpHCb pCmEmLSmmmz go moazom mpacb pmoEmLSmmmz mepmHam> Low ma mean .pm> pmoo Hence mo ceapwmasficaz ”soapoezm mpapoompo emoo aaeoe m mamae xodzfi poemsompm m an oommmmg two Hamo mom used ompmomom ho emanamopom osma Uopmopom mam: mzpq mpmpm show 302 co pqzosa mwomazocx HMCOmAmm ago» 302 .mpqsoo mummaao mo mopoam Hmapo¢ mumpm snow :02 Ca mmpmoaom mo mme¢ mnommcmnu cacflm Hammad capmsummm an wcaxsmm News“ Hmofimoasz m an cmmmoaaxo .Haoo Lem soap 57 was: mZDq mumpm xpow zmz IdeamHmmmHo poHoo pmmaom . pmMLuCoo Loaoo mHGOm ompmspmpm mmHLom m an commmmaxo .Hamo mpstE m.m .mgmz mo>msm pom LSOpSoo pmmzoa one Hmflpnmpommfid Hmoflwofiooo mmpmpm ponds: pwmsmfls Coozpop poem LSOpsoo xmoca pepsmamz moaamm w mm pmmmmpaxm manna: m.m .mamz mm>psm Hamo pea puma on afixmsoflpmamp HmoHdoaomw mopMum capes: memz mo mumpzmopmm Usma op ampmz l’ mpac: moanmfipm> Low psoEoLSmmoz mo mopsom mpflcb psmsopzmmmz mmapmapmb woapmabopomsago capospmma co :oHumoHchcmeH map Eomm mpflmosom Um>Hmommm mHHmHoom 0:» go moflpmufiaaxmz ”Soaposzm m>apomfino mmOBoe Haoo mo mumpsooamm mSHm> mcflxfimm pxwflm? rd Gaga Qmemmmom mo BZDOE< m mamas 70 o 3 cos .0 : m cm .3. a a om .3 e s as .om @ 3 om .63 3 in Cm .om mbmpmeOmeD. COHPQHGW ozam> eoflxcmm aghast cmpmHOOmmg ocmq 0» amps: moemoHQzH DHHmzemmm mHmm7OHB mcflxcmm passes oopoHOOmme Mesozosoeefio ssoesoo adHezmmmmmHQ mDOHZOO a ma.ee 73 o m ocmfloemsm nessasmsss m.m m msoaoaasoo 0.m m moosofloom 0.0H m msoaoeHsQo one moosoflooo ooxfla osame msfixcmm panama oopmaoommm mama umosom l-’ ck- . facility. Prior to the application of the prorosed model, it will be necessary to analyze the physical and socio-economic char— acteristics of the study area. From this analysis, a profile can be constructed so that the reader car become familiar with the research area. Furthermore, the rationale determining the selection of resource component factors can be validated. Therefore, Chapter III will outline the Characteristics of Orleans County and prepare the reader for the application of the outdoor recreational planninv model. CHAPTER III A PHYSICAL, ECONOMIC, AND DEMOGRAPHIC PROFILE OF THE SELECTED STUDY AREA: ORLEANS COUNTY, NEW YORK As the invesigator proceeds with the construction and application of the planning model, it is necessary to analyze the existing land use, as well as the physical, and demographic characteristics within the selected study area. The selected study area, Orleans County, New York, is positioned within the northern portion of Western New York, bounded on the north by Lake Ontario, on the east by Monroe County, on the south by Genesee County, and on the west by Niagara County (Figure 2). The physical characteristics of Orleans County have been identified by various studies: U.S.D.A. Soil Conservation Services Soil Survey, technical reports concerning physio- graphy, climate and drainage gathered by the Genesee/Finger Lakes Regional Planning Board, U.S. Geological Survey Maps (7%-minute series). From a review of these studies, a physi- cal description can be presented. Orleans County lies within the Ontario Lowland which is underlain by Silurian rock strata. Within this lowland, two sub—regions separate the study area into two distinct regions. However,51third possible region can be defined which lies between the two distinct regions. This third region could be labeled as a transition zone since distinguishing characteristics are apparent. The trans- ition zone is characterized by the extension of the Niagara Escarpment which appears within the county. The rock outcrops 75 76 Figure 2 Location of Orleans County Within New York State 77 rbzaoo moczoz I 3 rhzaoo mmmwzuo I o rkzaoo <¢PZDOO mz >>wz Z_I._._>> >._.ZDOO m2 2imz .>FZDOO mzm moId 81 The lowlands are cut by six drainage systems: Oak Orchard Creek, Johnson Creek, Marsh Creek, Bald Eagle Creek, Yanty Creek, and Sandy Creek.48 The individual streams do not carry a large volume of water since differences in relief are moder- ate over the total stream system. The major stream, Oak Orchard Creek, shall be used as an illustrative example. The stream's gradient was calculated using U.S. Geological Survey Maps, 7é-Minute Series. It was found to have an average drop of 15.5 feet per mile. This relationship may clearly indicate that the flow of water within the major stream has a moderate water flowage. From an analysis of streams and rivers conducted by the New York State LUNR inventory system, it was estimated that there are 541.6 lineal miles of shoreline adjacent to the “9 This total represents streams and rivers of the study area. an important component in estimating the potential for recrea- tional development. However, it should also be pointed out that water quality of the streams and rivers may induce a constraining factor for development resulting from bacterial counts, sedimentation, and biochemical oxygen demands. The climate of the study area is moderated by Lake Ontario which influences the growing season. Mean annual temperatures range from a low of 23.6 degrees F. in January, to a high of 70.3 degrees F. in the month of July, with the annual average u80r1eans County Deve10pment Committee, Orleans County, New York: Overall Economic Development Program, (AlbIOn, N.Y.: Orleans County Development Committee, September, 1969), pp. 3-4. ugGenesee/Finger Lakes Regional Planning Board, Parks, Recreation and Open Space in Orleans County: Inventory and Analysis (Rochester, N.Y.: Genesee/Finger Lakes Regional Planning Board, 1971), p. 38. 82 temperature approximating 47 degrees F.50 As a result of Lake Ontario's moderation effect upon temperatures, the growing sea- son is extended to 160 frost—free days. This phenomenon has promoted specific types of agricultural land uses, mainly fruit and vegetable production. The mean annual precipitation data for Orleans County was recorded at one climatic station, Albion. It represents a ten-year period of rainfall observations. The average annual precipitation is 30.68 inches. From analysis of monthly means, it can be shown that the maximum periods of rainfall are Fall (September) and Spring (AprilmMay).51 The natural forest cover dominating the study area is divided into two major associations: 1) Elm-ash-red maple, and 2) maple-beech-birch. The associations occupy 20,500 and 20,600 acres respectively, within the county's total land area of 253,400 acres.52 However, other species are found within the county such as aspen, hemlock, sugar maple, white pine, red pine, oak, white cedar, black cherry, and basswood. Rem- anents of the original forest cover are found within farm wood- lots, which average 15 acres in size, as well as in swampland areas, which have never been successfully cleared nor developed. 50Orleans County Development Committee, Economic Develop- ment Program, p.5. 51Genesee/Finger Lakes Regional Planning Board, Ph%sio- graphic Features: Regional Inventory and Analysis, p. . 52Ronald R. Ferguson and Carl E. Mayor, Timber Resources of New York_§tate, U.S. Department of Agriculture, Forest Service, Resource Bulletin NE-20, (Northeast Forest Experiment Station, 1970). 83 These geographical characteristics have encouraged the develop- ment of anagriculturaleconomy, which began with the first settlers, and has continued to the present time. An analysis of the existing land use situation results in the identification of the major types. The following land use types have been classified by a land use inventory conducted by the New York State LUNR (Land Use and Natural Resource) System. Within the inventory, six types of land use were assigned and measure- ments were taken within each county. The following is an analysis of existing land uses with- in Orleans County. Categories included: 1) residential lands, 2) commercial lands, 3) industrial-extractive-transportation lands, 4) public-outdoor recreation lands, 5) agricultural- inactive lands, and 6) forestlands-water areas - wetlands.53 The representation of this information is presented in Table 9. Agricultural lands which are either extensive, intensive, or inactive comprise the greatest percentage of land use with— in the county, 69.6%. Forestlands, water areas, and wetlands make up the next major component of land within the county, constituting 26.7%. These combined land uses comprise 96.3% of Orleans County's land. As a result of this concentration, it was decided to utilize the above combined 1and,uses to evalu~ ate the county's resource components. In other words, those areas comprising either agricultural lands, inactive lands, 53Genesee/Finger Lakes Regional Planning Board, Orleans Count Land Use: An Inventory and Analysis, (Rochester, N.Y.: Genesee7Finger Lakes Regional Planning Board, 1970), pp. 4-16. 84 TABLE 9 COMPARISONS OF LAND USES OF ORLEANS COUNTY Land Classification Percent* Residential lands 1.7% Commercial lands 0.3% Industrial-extractive- transportation lands 0.8% Public-Outdoor Recreational lands . 0.9% Agricultural-Inactive lands 69.6% Forest Lands-Water Areas- Wetlands 26.7% Total 100.0% *Orleans County, New York State, LUNR System, 1970. 85 forested lands, water areas, and wetlands were analyzed with- in the outdoor recreational selection model. The remaining 3.7% was deleted from the model since the land categories in- volved were not conducive to a public recreational development such as camping because of their urban locations. As the study proceeds, it is necessary to analyze the economic sectors within the study area. The county has re- mained a leading producer of agricultural products within the region. Agricultural employment in Orleans County has shown the smallest decline over the past ten years, when compared with the decline in the surrounding seven-county region: Genesee, Livingston, Monroe, Ontario, Seneca, Wayne, and Yates. Farms have produced the highest average sales when compared With those in the surrounding seven-county area; and the county has become the leading vegetable producer in the region. From Table 10 various agricultural activities have been ranked by comparing Orleans County to the eight-county region. By comparing the distribution of employment within the eight-county region, employment seems to be concentrated in certain sectors of the economy. From Table 11, the importance of agriculture to Orleans County's economy is evident. There- fore, agricultural lands are an important resource input with- in the county's economy. It is on these lands that this anal- ysis concentrates in evaluating potential for public recrea- tional development. Therefore, as non-marginal changes of land use occur, we must be aware of theeconomicimpacts and tradeoffs. FiISEIIEIIF?~” 3 LTURAL ACTIVITY N Measurement UHltu Orleans County Rank in Eight County Region* Percent of land in farms Acres per farm Sales per farm Sales per rawita Employees and proprietors p6 r 1,000 ponule'jon Percent of income from farms (i9=7) c ’1‘ ,,V i\Cenesee/Pins-:er Ia {es Regional Summary and Orleans County Profile, Analysis: Regional ‘ -—~..——u-—-..,;-—. 12.0§ 2E K») l3 N 13 If: m ‘5 @ -- —-n ~... .- ._.-_-_-.. ......—. v-‘y Planning hoard, Economic Technical Report lo, 2 lakes Regional Definition: E Livingston, Nonro Yates Counties. Planning isht-county e, Ontario, (Rochesier, N.Y. October, Board, Orleans, region consists of: Seneca, . Cenesee/Finger 1969), p. 1. Genesee, Wayne, and 87 :‘WA ,v {fl ’ j 1 ”LE ll PERCENT DTITiInQ“IOR CE EMPLOINENT WITHIN ORLEANS COUNTY, AND ITS RANh IN T73 IIRLEORIPG JSIGhT—COUNTY AREA: 1968 Categorfe; o” fir_eans Rank in Eight— Iplfl“'9flb Coun,v county Region* ‘I Non—Agricu tural Nafie and Salary Workers (except do c“*jes, m_ Family worke_s, and Self~emnloyed§ EWarnxffacinxrlsi 311.5;2 7 tk1 ‘on-mar fact {QM’ #3/g1_ 7 th Domestics, Rani]: , Workers, an : Solfl 11'], g th emalv,e; A"'Tricul tural . 5 employment Persons Invol ed 0.0% iii IBJDOT‘l/IRINJCBE *uenesee/Fin er Lakes i. Winai -Iann1ng Lgard, Economic Analysis:‘ Regional Summary and Orleans County Profile, 1970. 88 The population of Orleans County is described as a domi- nantly white, lor‘rer-mmiddle class, rural society, About 67% of the people live on rural lands or farms; the remaining 33% find shelter in two urban centers, Medina and Albion. The 1967 pop- ulation density for Orleans County was eighty-six people per square mile?“ Negroes make up 4.3% of the population, and are the only racial minority in the area. The remaining 95.7% are white persons of native stock (77.6%) or of foreign stock (22.4%). The educational achievements of individuals vary widely. A minority (5.8531) competed less than five years of school. This group is most often represented. by migrant black farm laborers. More than one—third of“ the population (914.1%) have completed high school and/or advanced schooling. Nonetheless, the median school years completed by adults in Orleans County was 9.9 years. Closely aligned with these educational patterns are the average annual incomes of residents within the study area. The median income in 1967 was $5,608 per family. Nearly one- fifth of the people (18.575) earned less than $3,000 per annum. Thirteen percent of the population earned more than $10,000 per year. These two groups representing the extremes in income, SymbOIize the educational extremes, (low income group has a median of 5.8 school years, and the highest income group has completed high. school and additional college training). To assist those low income members of society, public assistance is Dr‘ovided 1,558 residents or “3% of the population. \ C 54County and City Data 300k, 1967, U.S. Department of 0mmerce, Bureau or Census, (Washington, D.C.: Government Printing Office, 1967), pp. 252-253. The demographic profile of the study area reveals that the urban population is located in two major centers posi- tioned along the Erie Barge Canal. The villages of Medina and Albion have total 1970 populations of 6,338 and 5,078 respectively.55 If we compare the total pepulation of the county, 34,588, with the urban population centers of Albion and Medina, 11,416, it is seen that approximately 23,172 people are distributed over a predominantly rural landscape. Therefore, Orleans County is basically a rural economy. In analyzing county population data from 19o0 to 1970, it can be concluded that the study area has experienced.a.slightgrowth rate of 1.26% or 56 #29 peOple. However, new job opportunities within all sec- tors of the economy have not kept pace even with the small population growth rate. Therefore, a net out—commutation of working people has occurred within Orleans County. This obser- vation can be supported by analyzing the commuting patterns of the study area. From commuting statistics within the eight- county region, 28.9% of the employed civilians traveled outside Orleans County for employment?7 This percentage was the high- est value within the eight-county region for out-commutation. Furthermore, the innout commutation ratio of 1:6 indicated that 55Buffalo Evening News Almanac and 1972 Fact Book, (Buffalo, N.Y.: Buffalo Evenin: Mews, l972), pp. 129-130. 56Genesee/Finger Lakes Regional Planning Board, Parks, Recreation and Open Space in Orleans County, pp. 20?22. 57Genesee/Finger Lakes Regional Planning Board, Economic Analysis: Regional Summary and Orleans County Profile, Technical Report No. 2IIRochester, N.Y.: Genesee/Finger Lakes Regional Planning Board, October, 1969), p. 107. 90 for every one person traveling into Orleans County for employment, six persons traveled outside the county for employ- ment.58 A major function of Orleans County is now to serve as a bedroom community. Only the agricultural sector has re- mained a viable industry within the area; however, as mechan- ization increases, the labor to capital ratio decreases, resulting in umemployment or labor shifts to other industries. Also contributing to this situation is the fact that gains in productivity of labor have also resulted in a reduction of the labor force in producing the same agricultural production. If Orleans County continues to serve a resident function for com- muters, the need for recreational planning and the preservation of open space may increase. Major transporation modes within the county include rail, highway, and water. Rail facilities located throughout the county do not have a mainnline status, since the Rochester— Niagara Falls link is only a freight branch-line. Highways provide the major mode of transportation within the county as well as important linkages to adjacent areas, including Roches— ter to the east, and Buffalo and Niagara Falls to the west. The principal eastnwest routes are State Route 31 and United States Route 104. State Routes 98 and 63 provide for north- south movements. The New York State Department of Transport- ation has recently completed the lake Ontario State Parkway paralleling Lake Ontario from Rochester west to Lakeside State Park. This parkway serves as a linkage for commuters traveling 581b1d., p. 108. 91 to and from Rochester, and to link a major population center with recreational facilities. Water tranportation is limited to recreational use of :he Erie Barge Canal. The competition of other modes has reduced the effectiveness of the canal as a major economic contributor to the study area. Recreational. Opportunities within the study area vary from small village parks to the federally owned Iroquois National Wildlife Refuge. New York State is currently developing two state public recreation areas named Oak Orchard State Park, a marina based recreation type, and the Lakeside Beach State Park, a water and land based recreation type. Swimming, camping and picnicking are common activities at Lakeside Beach State Park, on the shoreline of Lake Ontario. Neither park has been completed, so recreational opportunities to area residents have not reached their designed potential. The last link of the Lake Ontario State Parkway has been scheduled to Open Febru-‘ ary 16, 1973, which will enable greater utilization of the Lakeside Beach State Park during the 1973 season. Nature- oriented recreational activities are provided for by the Iro- quois National wildlife Refuge and the Oak Orchard Game Management Area. Private recreation enterpriseseareunequally distributed within the county and in conjunction with major population concentrations. Golf courses, conservation clubs, a few campgrounds, and rod and gun clubs dominate the private organiza- tion of recreational activities. However, the spatial arrange- ment of these enterprises does not allow equal access to these recreational services, for the residents of all communities. 92 In summarizing the major physical, economic and demo- graphic characteristics descriptive of Orleans County a brief list will suffice; l) Orleans County is located within the Ontario lowland, wherein three definable sub-regions exist: a) Lake Ontario Plain b) Southern Ontario Plain c) Niagara Escarpment Area 2) Each of the above sub-regions were formed by varying geologic processes (either lacustrine deposition in the north, or ilacial deposition of till and outwash in the south). The resulting physiographic differences in soil types, slepes of land and drainage patterns produced variations in land use withln Orleans County. 3) The climate of the study area is moderated by Lake Ontario's effects on temperatures and precipitation. As a result specific agricultural enterprises are located adjacent to the large water body. The moderation effect has increased the number of frost-free days within the growing season for that latitude to 160 days. 4) Aqricrltural land use dominates the land area within the county, occupying 69.6 percent of the total area. 5) Pepulation has grown at a rate of 1.26 percent over a ten year period. 6) Transportation within the county is based on highway surface capabilities for the supplying of production firms and the distribution of products to local and regional markets. 7) Recreation eppcrtunities within the study area are varied: however, an unequal distribution of these activities does not allow equal access to all residents. 8) Orleans County does not have a balanced economy, and as a result, a net outucommutation has occurred. This situation has induced a change in land use patterns and encouraged the development of bedroom communities. The outdoor recreation selection model for public camp- ing was designed and calibrated according to these physical and socio-economic characteristics of Orleans County. In Chapter IV, application oftflmamodel to a locational problem within the county, will be described. CHAPTER IV APPLICATION OF THE OUTDOOR RECREATIONAL SELECTION MODEL WITHIN ORLEANS COUNTY, NEW YORK After having outlined the planning model and described the study area, we can operationally apply the model. For the model's application, it is necessary to outline the community priorities and their associated objective functions, the vari- ables, measurement units, and data sources. Finally, the in- ventory system and the deveIOped land use decision rules must be placed in perspective in order hounderstand the planning procedural framework. Therefore, this chapter will discuss the application of the selection model and provide the reader with its output derived from an analysis of Orleans County, New York. A stepwise sequence will be presented to link the model's framework and output for community decision-making. One objective function of the community considered in this study was to select a campsite facility within Orleans County by minimizing the loss of revenue normally generated by property taxes. Three variables were considered for each of the privately owned land parcels within the study area: 1) assessed land value, 2) assessed land value with improvements and 3) both county and township tax rates. The sources of the assessed land values, with and without improvements, were the records available at the Orleans County Tax Coordinating Office, Court House, Albion, New York. To 94 95 obtain data on the third variable, each school district within the study area was contacted. From maps and tables forwarded from Albion, Holley, Kendall, Lyndonville, and Medina School Districts, the tax rates were identified, and mapped. The calculation of a per acre assessment on land, and on land with improvements was necessary for each private land parcel because their boundaries do not coincide with school district nor township boundaries. Both per acre values (land and improved land) for each farm were applied to a county map, where they were used to compute a mean assessed land value for each cell, and a mean assessed land value with improve- ments for each cell. A mean assessed land value per acre and assessed land value per acre with improvements was computed for each of the approximately 1056 cells of the study area in a five step method: 1) computation of per acre assessed values for land alone, and for improved land for each farm. 2) location and plotting of farm values on a gridded map of the area: total acres per farm; per acre assessed land value, (L); per acre assessed land value with improvements, (L.I.). 3) division of each cell into smaller units by placing a transparent 25 sub-cell aridwork overlay on it. 4) estimation of the number of sub-cells occupying each farm within a riven cell. 5) computation of a weivhted mean for improved and unimproved assessed land values for a given cell. By using the sample cell as the unit of analysis, the 96 sequences of computations used for each of the 1056 cells in the study area of Orleans County to achieve cell means can be explained in detail. First Step: 1) Computation of a per acre assessed land value, and per acre assessed improved land value for each farm in the cell: A. Record the acreage, total assessed land value and land value with improvements: Sample Design of Tax Record: Owner Acres Assessed land Assessed improved value land value Farm A 85 R 4,100.00 $ 4,100.00 Farm R 112 5,760.00 12,980.00 Farm C 175 8,510.00 14,000.00 Farm D 73 2,920.00 12,000.00 Compute a per acre assessed land value by division: (Figure 4). Per acre assessed 2 L = Assessed land valug of farm land value ‘(farm) Acres within farm Example: L(Farn B) = $ 5’760‘00 = $ 51.42 ‘ ' 112 Calculation of a per acre assessed land value with improvements: (Figure 4). Per acre assessed land 2 L I value with improvements ° '(farm) 3 115.89 ) = $ 12 80 L.I. (Farm B 12 The per acre assessed value of Farm B with its 97 improvements, as drainage, buildings, etc., is larger than the unimproved lands. The per acre values, L. and L.I., for farms A, C, and D were figured in a similar way to produce the values recorded on the sample cell (Figure 4). Second Step: The second step in the method was to locate the land parcel (farm) within the county, and to record the L. and the L.I. values, and total acreage in the appropriate cell. The tax record was the primary source of locational data, as each parcel was identified by its road name and direction (cg. Marshall Road, East). When a single owner held more than two farms on the same road, a secondary reference was used to help locate that farm. The Atlas and Plat Book of Orleans County, New York contained two indices that helped to identify the farms. By use of the Index of Owners and Index of Residences, as well as acreage of each farm listed on these plat maps, the researcher was able to locate all the land parcels on the gridded map of the study area. Third Step: The need for dividing each of the county's cells (one square kilometer each) into 25 equal-sized smaller sub-cells became evident once all the farms were plotted. Since most cells were a collection of farms, whose boundaries were not congruent with the superimposed grid, but rather projected into neighboring cells. Each cell was subdivided into 25 sub- cells (5 X 5), to help compute a weighted average for each cell's per acre land value (see Figure 4). 98 Figure 4 Per Acre Iand value and Per Acre Land Value with Improvements For Farms (A,B,C,D) 99 PER ACRE LAND VALUE AND PER ACRE LAND VALUE WITH IMPROVEMENTS FOR FARMS (A,B,C,D) I FARM : A I I I L.48.23| FARM LJ.4&23' __________7 C I i FARM l L.4a62 I LJ.8ODO 3 I $-11 __________ m}..- L.5L42 I FARM LJ.H589 I I D ___I I | I“ 4dOO : LJJ64J8 I | 783,226 I LOCATION LEGEND? REFERENCE CELL BOUNDARIES -——~—-— FARM BOUNDARIES L. —- PER ACRE ASSESSED VALUE LJ. — PER ACRE ASSESSED VALUE WITH IMPROVEMENTS 100 Fourth Step: In order to estimate the number of sub-cells occupying each individual farm lying inepart, or in-whole, within a given cell, a visual count was made to the nearest quarter of a sub- cell. It must be pointed out that measurement error has occurred in estimating the number of sub-cells within each farm. For Sample Cell, 783,226, the estimated number of sub- cells occupied by the four farms is shown below: Farm Number of Sub-cells A 1.50 s 5.75 C 11.25 D 6.50 II Total cell area 25.00 sub-cells, Cell 783,226. Figure 4 displays the number of sub-cells occupying each individual farm within Sample Cell, 783,226. Fifth Step: The computation of a weighted mean (for assessed land values) on improved and unimproved lands was figured for each cell by the following equations: ITE"’ : SCA(L.A) + SCBIIAB) + SCC(L.C) + scD(L.D) +..SCN(L.N) 25 L I c = SCA(L.I.A) + SCB(L.I.B) + SCC(L.I.C) + SCD(L.I.D) + ... SCN(L.I.N) 25 101 Where: L.C. = weighted mean assessed land value for any cell. L.I.C. = weighted mean assessed land value with improvements for any cell. SCA B C D N = number Of sub-cells in respective farms ’ ’ ’ "°‘ in any cell L’A,R,C,D,...N = per acre assessed land value for each respective farm L I ' ‘A,B,C,D,...N = per acre assessed land value with improve- ments for each respective farm. Computation of the weighted mean assessed land value and weighted assessed land value with improvements for sample cell, 783,226 is illustrated below. L.C. = 1.50($48.23) + 5.75($51.42) + 11.25( 48.62) + (783'226) 6.50( 40.00) 25 L.C.(783,226) = $ 47.00 L.I.C. ==1.50($48.23) + 5.75($ll5.89) + 11.25( 80.00) + (783,226) 6.50( 164.38) 25 L.I.Co(783’226) = II; 108.29. Figure 5 locates sample cell 783,226 within Orleans County. Similar computations were done for all cells within the county. The results were recorded as per cell mean assessed land values and per cell mean assessed land values with improve- ments. The application of these per cell means included use in 102 Figure 5 Location of Sample Cell, 783,226, Within Orleans County, New York 103 4A? (3.,HELY I.CATA SET 1 .n - --o- --—-----------o ------..-.- .-----I-n—-—----------—----------—------------------——-—-------—-—---'qv-----q--. ... “‘IAIKI R N UKRI ENN UAJN N;N «IAIN <1)qu OAIN OtBN W thN n. M- w W DJ J 0.0.0.000...oooooooooocooooooI000...-cocoooouoolloooooo- ”G7 .COOOOOQOOOOIIOOOOOOOO.COO...0.0.00...-00.000.000.000... 80’ .0..IICOOOOICOIOOIOO0.0.0..........OCUOIOIOOOOOIIOOOI... O.....00....OOIOODIOOOOOOOOOOIOIIOOD ............IIOOIOOIOI.0.0.00.0... ”Ob .0OOOOOOOOOOOOCOOOOOOOOOOI........IOIOOCOOOI...IIOOOOIOOIIIOOOOIOOOOOOOOOOOI 806 DID...O...-.....OICOQOOOIOOI.........IOOIOOOCOIOOOOIDOI-...IJOICIIOODIOOOODO ..........................'....'..I..I...‘..............................I..‘ 0.00.0...Doo-voonooionuocoaiiobloc 805 I40" sococoon-conc-Cocoa-ooaooocouuIcon-Coo OIIOOOOOOIIOOOIOOOOOOOODOOOCOOOIUOOOOOCIOOOOODIOOOIJoanna.-ooocoilooootlooon ' .-..Oonouo-o-ncocoon-o...coo-cocoononooooaInn-OooaOOOOOo-ooa-canoe-cocoon... I I'M-‘9 lOCOIOOOIOOOOOIIOOIIIQOI.I...OOIIIOCOOIIIIIOCI...0......Coo-00.00.000.000... “(no I 0-0oowooluuocountenance.-on...no...oucooocoouoocoooo¢O-.cooDeacon-cocoon...- I ...-.....o.u...-......I-ocoo-oooo.-oopo-o..-uncooouooonoonuooo-o....-....... I HLj halo-OI-OIOOa.0.0000000000000000!0000.00.00.000.000.000.000...QQOOOOOOIUOIOI 80‘ I ............................................................................ I no...-IIOOOOCODOOOIOOOOIOIOIOu0.0.0.00.IOOIOOOOOOOOOOOOQOOIOI.ooOOOOOOOOOIIU I I”? IIOIIOOOOOOOOOOOIOOOIOIOIOOOIQIDOOOIIIOOQOIDUOII...osootocoolooco50.0.0.0... U02 II....00..........CIUCCCIOOOOO......OIOOUUOUC.....I...I.O....ICI‘CCOUUICOOOC I glooooololuo......OIOOOO.loa-III-OI...-olooonlocoooooovaococooIaIOIIIoIIlODI I “I enhance-Ino-ooouooaoncoooooooono.0...Otto.ooocooooucove-cocooonunoooocoo-... UOI ...-............o-ouacuuo-onnIu-u....on.o 00.00....-svouuuoonoo-o-uc DID-ID. ana...ouco-uaonouooooo...ooa Inn-I conuuoooo-ooo-ooooo-nooa...-I I. 00-...- ""\ O.OOOOOIIJOIOOOOOUOOIIIOOOOCIOOo-I-ICOOOIOICU-IOOOOIOIIOutoOII-IDIIIIOIIOIOO 8/30 I IOOOOCOIOQI...IOOOOIOOIOOOOOOICDIOICI'OOOCCO.......OIOCOIIOOCOOIIOOIOOOOIOOO I 74‘ oonoocoounuo...-ooooaoolooolooclotoUncooocolloooco Olin-0000.09.00. 00.0000. qu ...-IIDQIII.II...IllIOOIOOIUOIOIOOOIOOOOOI ...-OOOOOOOIIOOOouloolo-On30lnoul I...9.IIOOOOI.II-OICOIIOCCOCOUCIOC.00..........-II.....OOOOCIOIOOOOOIIIIOOI'OI I 7‘)? ...-IOOI.‘IOOCOIOCOOOOCOOOCOOIOCII......OIUOUUOUC0............OOIOIIICCOOOOUOOOO ’9’ I I'M“ 0.0...OIIOOIIIOOOIOOIIOIOOIOI....O.III-OOIDOOOIIOI.0.0.0....IOOOQOOIbIIOIOIOOOOO IQ” I (“'7 Ito-IIOOOIOIOIOOIOIOOOOIIOOCOOOOOOIII-IO'OIOOOOOOOII'IOIOOIIDOOIOOO-DUIIIOIDOOOO ((3‘) ’9’) ......OIIIOI.0'l...’...l.........I...I!I......l..l..........I...........U0...... 790 I'h’ OCOOIIOIOCOIOOI......DIIOIIUIOIOOIIOOIIIOOOOCOOODOIIIIOOOIIOCUI......OIII‘DIDOII 7”” I I" 0090-.II..000...I.OOOOIOOOIOOCOIDIO.IconoonlooOODOIIOOCOIIOOloo...Dianne-0...... 73". 7M“ on0.00......Ill......-IIOOOOIIOOOOOOOOI0......0.00.00.00.00.IIOOOIOIOOIOOCIODIOO 786 ,is ......IOO....I........I..........I......-OI...CI.......O..OIOIDIOIIOCOOIIOIIOOII 785 783 ......on¢oeoooooooao00000¢0| .IIIooooooooteoI-IOOnoloo-.........oI-Iooonggo. 783 .000IOOOOIOOOOOOOOIIIOICOO.. coco--not-nuuoononoo-o-ooooonce-coccnouoo-II... coolIIOICIOOOIOOOIOOCOOOIIOO IDIOOODIIUOODUIIOOO.t....-OIICOIOOIOI-Ioocouoou 7’5.) I00-IOIOOOOOOIIO000.000.000.00...00.0..I.Otto-OOOQODUIQQOOOIn-uIOIOOIIODOIOIOQO. 7R3 ...o-ocooo-IO-oooooo-uooooooooouoooooo-I-c-oooo.ouoooooouoo-on.o..,I-o-.......... 00o.OOOOIOIIOIIOOOOOOIOOOOIno.uoilIo-oloooooooooblloooooccooccootooooa ,Ul 0-00.00...IOOODOOOOOIOOIIOOOOOOCIIIIQOI0......IOIOOOIOOIo-ooIlia-OOI-OOCIIIIOIIO 731 ...-......ouuocoooI-ooooooaoooooaoaouoo~ucoonooooooonoooooo-oo-ooo-oooo-oocooono ...-o.uncoooooo-ooocoooovoooooo..¢ooucun-Conan-IOOOo-onooo-uoooooo...oouo-acoono 70L: OOOOOIOCIOOOOO.....IOOIOOOOIOIIIIOOOOOIOOOIIOIOOOOIIOIOOIOOIIIIDDOOOIIIIIOOODIOO 780 IOOOOCOIOCOOOOQOCCOOOCCI......COOI.OIIIOICODOOQ......COICOIOOII....IIOOOOOOIIID. ~NM NN'V wk NN N n ._ .JNIN r .0fo ‘4 Id w a Ix. \p ‘94 WEIR- (HR! fl~———u—o——~u—t——_o—_>—~,——-—m—_.—>"-————~—_-r——_—. r— . . . . o o I . . . . . . a . . c u . p . o o o o . a o o o o o o o . c C c o .0 o o 0 o I a v . C . . o . . O o c O u . o . ' . o . . o O o o o o u . n . I . o c n o - I n n o 0 o A—~—_———~——H—n—————~p-——~‘-——-—-————._--—_—-———-——-———-——~—————-———-—--—-———--——~—"—_—""'""‘"""—————_—_"_-_—-——_~—————~— O I I I I l I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I l I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 104 determining property tax revenues, and acquisition cost. Furthermore, these cell means were mapped by the computer routine as shown on pp. 170-77 of the appendix. However, the direct use of these means for recreational planning was limited since they were not directly linked to a specific community objective function. With the cell means computed, the researcher can begin to analyze the first objective function, which is to minimize property tax revenue loss. To determine the total property tax revenue loss from each of the cells within the study area it was necessary to multiply the per acre assessed landvalue with improvements by the number of acres in that cell (247.1 acres), and then by the corresponding tax rates (based on a thousand assessed evaluations). The equation below illustrates this relationship for the sample cell: PTRL(783,226) = L.I.C. X 247.1 X TR Where: PTBL property tax revenue loss for the sample cell L.I.C. = average assessed land value with improvements, per acre, within the sample cell 2h7.1 number of acres within each cell TR = corresponding tax rates for county and township for the sample cell For the sample cell cited, the property tax revenue loss based upon current millage rates of $ h3.00 per thousand assessment of improved lands yields. PTRL = ($108.29) x (247.1) x (0.0u3) = I 1,150.61 105 This value of $ 1,150.61 is the amount of property revenue generated by the sample cell to the county and township govern- ments. This is the value cost to the study area if a non-mar- ginal change occurred resulting from a shift of private agri- cultural use to a public recreational deve10pment. This value also may be referred to as the opportunity cost of such a land use change within Orleans County. Therefore, to minimize the property tax revenue loss, or Opportunity cost, it is necessary to select those cells which generate less prOperty tax. The output of the objective func- tion can be visualized within the computer maps, on pages 178-81, within the appendix. Those cells havingaiproperty tax revenue loss between $ 152.14 and $ 343u.76 are within the category for a lower revenue loss. They appear in the areas of lightest shading on the computer map, pm» 179-80 tn the appendix. There- fore, these cells should be considered for feasible sites, if the objective function is to be satisfied. A second objective function was to select a campsite facility within Orleans County by minimizing the initial devel- opment cost. The initial development cost is that cost outlay necessary to: 1) acquire the cell for public recreation (acqui- sition cost), 2) provide adequate drainage (drainage cost), and 3) link the cell to an existing highway facility (trans- portation construction cost). It is these variable costs that the investigator has chosen to analyze and assign to the ini- tial development costs of a public campground facility. In order to determine the initial development cost for the in- dividual cells, it is necessary to analyze the variables and 106 their measurement units. The methods utilized to measure the individual variables are presented below. As before, a stepwise procedure will serve as a framework for explanation in conjunction with mathematical equations. The first variable to be discussed within the computation of the initial development cost is acquisition cost. Acqui- sition cost was determined by two approaches within the study area: 1) average recorded sale value per acre, and 2) an adjusted average improved land value per acre. Both approaches were utilized within the study area to estimate the market value. Acquistion cost per acre was based upon the per acre recorded sales value or the per acre adjusted average on improved lands. Once per acre costs were computed, the total acquisition cost per cell could be calculated by multiplying per acre costs by 247.1. The first approach was to acquire the average recorded sale value on a per acre basis for lands purchased for public recrea- tional developments. It was assumed that the acquisition cost for converting privately owned lands into publicly owned areas was a reflection of true market value. Hence, market value would directly relate to the acquisition cost of individual cells. Based upon this premise, data were acquired for trans- actions which reflected changes from private agricultural use to public recreational use. Within the study area, public recreational land purchases have occurred adjacent to the shores of lake Ontario. The purchases occupy cells: 806,236; 806,238; and 806,239. These cells are the only land areas that 107 have been purchased from private owners for public recreational development within the county. However, sales information from other counties similar in nature could have been incorporated into the existing sales information, but such data were not in— cluded in this study. The per acre value on improved lands within these cells represent sales averages computed by New York State on 640 acres of Lakeside Park land, and are recorded in the Transaction Office of the County Clerk, Court House, Albion, New York. The acquisition cost of fruit land per acre had a mean sales value of 875 dollars; open land had a mean sales value of 300 dollars per acre. Fruitland includes acreage devoted to orchards producing apples, cherries, and peaches. A sales adjustment factor (SAF) was computed using the cells adjacent to and occupying the Lakeside Park area along Lake Ontario's shores. The sales adjustment factor is a multiplier derived from the relationship between the adjusted assessed land values with improvements for each cell, and the average recorded sales value of lands within an individual cell. The sales adjustment factor was used wherever sales information could be obtained with regards to purchases of private lands for public recreational development. Data gathered within the cells occupying the public recreational facility yielded a per acre assessed mean value on improved land of $ 152.20; and an average recorded sales value of $ 300.00 per acre. From these data a sales adjustment factor was computed by the following equation: ARSV ER SAF = T ARSV ° ": LI LI ER 108 Where: SAF = sales adjustment factor ABSV = average recorded sales value per acre on improved land for cells 806,236; 806,238; and 806,239. fl = average improved land value per acre E8 = equalization rate per cell The sales adjustment factor was 1.97 for the data analyzed within the 600 acre parcel. The sales adjustment factor was utilized for all cells adjacent to Lake Ontario, excluding the State-owned 640 acre parcel. The sales adjustment factor was utilized for those cells similar to these lands purchased by the State for Lakeside Park, along Lake Ontario's shore. There- fore, all cells adjacent to Lake Ontario, excluding the park- land itself, were adjusted by a sales factor of 1.97. Acqui- sition costs for each of these cells was computed by using the equations below: l) ACi = ARSV X 207.1 ETi 2) ACi = X SAF X 247.1 ERi Where: ACi = acquisition cost for each cell Eli = average improved value per acre for each cell EBi = equalization rate per cell SAF = sales adjustment factor 247.1 = number of acres per cell i = l, 2, 3 ... n n = all cells adjacent to Lake Ontario 109 Acquisition costs for the remaining cells in Orleans County not adjacent to Lake Ontario were computed by an alternative technique as sales data was lacking for those lands.* The following equation was used to calculate acquisition costs for cells not bordering Lake Ontario: iii ACi = X 207.1 ERi Where: AC1 = acquisition cost per cell ‘ffi = per acre average improved land value for each cell 247.1 = number of acres per cell i = l, 2, 3 ... m m = all cells within the county not adjacent to Lake Ontario In discussing development costs for a public recreation facility, a second variable was included. This variable was the drainage cost on a per cell basis, which depends to a great extent on the major soil association within that cell. Drainage costs were estimated from consultation with the Soil Conserva- tion Service staff and were based upon farm records showing drainage potential for each soil association, and therefore, is a proxy measurement of cost for the adequate drainage necessary for the construction of a recreational facility. Soil associations were chosen to reflect possible tiling costs for each cell, as each association is an aggregation of soil properties unique to that kind of soil. The similar soil *Alternative technqiue discussed on pages 50-52. 110 characteristics of soils within any given association include: slope (percentage); silt and clay (percentage); depth of water table (feet); depth of bedrock (feet). Those associations with low percent alones (0 to 2 percent); high amount of lacustrine silts and clays (50 to 100 percent); and high water table dis- play higher drainage cost estimates due to their restrictive drain- 59 age capabilities. In contrast, associations having gently sloping to moderately steep areas, 3 to 15 percent, deep sands and gravels, and a low water table reflect a low drainage cost estimate. Table 12 represents each soil association classified within Orleans County; thegxn°acre tiling cost, and the drainage cost per cell. The estimated drainage cost per cell was calculated by using the eouation below: DRC.l = ATD.l X 247.1 Where: DBCi = drainage cost per cell ATDi = average tiling cost per association per cell 2&7.1 : number of acres per cell i = l, 2, 3 ... t II t all cells within Orleans County The tiling cost per acre varies from twenty dollars to five- hundred dollars, so that the estimated tiling cost of some cells is as low as 34,942 (eg. Arkport—Galen Association) and others peak at $123,550 (eg. Odessa-Lakemont Association) for a cell of equal area. These tiling costs do not take into consideration the economies of scale that can be reached if larger areas 590.3. Miller, L.M. Turk, H.D. Foth, Fundamentals of Soil Science, (New York, N.Y.: John Wiley and Sons, Inc., 1963), p. 48. 111 TABLE 12 TILING COSTS OF SOIL ASSOCIATIONS WITHIN ORLEANS COUNTY Association Per Acre Cost Cost Per Cell Muck $ 200 $ 49,420 Lookport and Elmwood 300 74,130 Colonic-Elnora 280 69,188 Palymra, Arkport and Colonic 20 4,492 Arkport—Galen 20 4,492 Odessa-Lakemont 500 123,550 Ontario and Lima- Kendais 280 69,188 Farmington and Rrockport 300 74’130 Hilton-Appleton and Clarkson 280 69,188 Alton and Colonic 20 4,492 Galen-Janius and Elnora 280 69,188 Lucas, Collamer . and Hilton 8 280 8 69,188 112 are drained. Nevertheless, the dollar amounts represent a rel- ative difference in estimating drainage cost. It must be re- cognized, as drainage techniques are improved, that cost savings may be realized. The spatial variation of drainage cost re- flects the physical characteristics of the land; hence, this variable is a major component within deve10pment cost of a public recreation facility. The third variable, which is a part of the deve10pment cost, is the construction cost of a road linking each cell's geographic center to the nearest existing road. Based on Soil Conservation Service contractural estimates, the New York State Department of Environmental Conservation designed transportation construc- tion cost estimates for public access roads to recreational facilities. From information obtained from the Department of Environmental Conservation, a ten foot wide public access road with two feet shoulders cost an average of 29,000 dollars per mile to construct. This estimated cost included removal of t0p soil, the shaping of lateral ditches, placement and grading of a six inch gravel fill. Estimation of transportation construc- tion costs for any cell was based upon the 29,000 dollar/mile value supplied by the New York State Department of Environmental Conservation. GHKBresearcher developed a table showing the con- struction cost (dollars) per unit distance (1/8 inch map inter- vals) for use on the New York State Department of Transportation 7é-Minute Series Planimetric Maps. The map scale of one mile for each two-and-five-eighths inches of map surface was used on the transportation planimetric maps. The road building costs were figured for a sequence of map distances using one-eighth 113 TABLE 13 TRANSPORTATION CONSTRUCTION COST SCALE Linear Distance from Cell's Center to Nearest Road on 75-Ninute Topographic Maps Cost from Center of Cell to Nearest Road 1/8 inches 8 1,380.95 1/4 2,761.91 3/8 4,142.86 1/2 5,523.81 5/8 6,904.76 3/4 8,285.72 7/8 9,666.67 1 11,047.62 1 1/8 12,428.57 1 1/4 13,809.53 1 3/8 15,190.48 1 1/2 16,571.43 1 5/8 17,592.38 1 3/4 19,333.34 1 7/8 20,714.29 2 22,905.24 2 1/8 23,476.19 2 1/4 24,857.15 2 3/8 26,236.10 2 1/2 27,619.05 2 5/8 29,000.00 2 3/4 30,380.96 2 7/8 31,761.91 3 33,142.86 114 inch intervals (see Table 13). This transportation construction cost scale (Table 13) was developed from the relationship that one mile of gravel road costs 29,000 dollars to construct, and is represented on the maps by two-and-five-eights inches. The road construction cost per one-eighth inch of map distances was calculated to be $ 1,380.95. By using this transportation cost scale, construction costs could be obtained from the center of the cell to the nearest existing road. The geographic center of each cell was identified by the intersection of diagonal lines constructed between opposite corners. In order to estimate the road construction cost for each cell, the investigator followed the stepwise sequence below: 1) measured the distance from the center of the cell to the nearest highway (to nearest l/8th of an inch). 2) located this distance on Table 13, left column. 3) recorded the matching construction cost in dollars. The transportation construction cost equation is shown below: TCCi = Dir X CDi Where: TCCi = transportation construction cost per cell Di a linear distance from center of cell i to the r nearest existing road, r CDi = cost per mile for selected type of public access road, i.e., $ 29,000 per mile 1 = 1.2.3...t t = all cells within Orleans County The development cost per cell includes the summation of acquisition cost, drainage cost, and transportation construc- tion cost. The following equation reveals their relationship: 115 1301 = (AC1 + DRCi + T001) Where: DCi = development cost per cell AC1 = acquisition cost per cell TCCi = transportation construction cost per cell DRCi = drainage cost per cell i = l, 2, 3 ... t t = all cells within Orleans County Therefore, to minimize development cost it is necessary to select those cells by a visual analysis of the corresponding computer maps, within the range of zero to $ 133,289.44 or, the lighter shading (see pp. 186 to 189 in the appendix). It is these cells which therefore should be considered as feasible cells for the second objective function to be satisfied. From the lower level cells selected by satisfying the second objective function, one can then return to the individual cell data to obtain specific information. The third objective function which may be considered high priority by a community is the minimization of the total costs. Total cost is the selection of those cells which minimize all the defined cost areas within the model. As previously stated in Chapter 11, there are other cost areas not included within the model. Also, measurement units necessary to spatially analyze supporting resource components may be lacking. A dis- cussion of other cost areas will be found in Chapter V. There are four cost areas which contribute to the total cost for providing a public recreation facility: acquisition cost, drainage cost, transportation construction cost and property 116 tax revenue loss. The equation below expresses the relation- ship among these cost factors, and may be considered the third objective function: TCi = (ACi + DECi + chi + PTBLi) Where: TC1 = total cost per cell AC1 = acquisition cost per cell DHCi = drainage cost per cell TCC.1 = transportation construction cost per cell PTRLi = property tax revenue loss per cell i = 1, 2, 3 ... t t = all cells within Orleans County As before, three levels were mapped by the GRID computer routine within the study area. Total cost per cell was calcu- lated for each cell. A range in total cost (dollars) was determined for each of the three mapping levels. The low total cost, medium total cost, and the high total cost ranges were each represented by different shadings, shown on Table 6, pp. 190-193. Those cells reflecting low total cost would be selected in order to satisfy this objective function. Those cells ranging from zero to $ 136,622.75 or cells of lighter shading were selected as feasible sites for the public camp- ing facility.* (See pages 191 to 192 in the appendix.) The fourth objective function in this study simulates a community priority designed to identify those physical factors *Those lands with zero total cost reflected lands already developed in Iroquois National Wildlife Refuge. 117 in the environment which would maximize the socially perceived benefits offered by the land resource and associated aesthetic appeal. The researcher has identified four physical factors relating to the aesthetic components of land resources. Also, he has isolated two external factors affecting the aesthetic attractiveness of a proposed site: nearness from an existing and competing recreational camping facility, and proximity to a pollution source are integrated into the model. Distance from a pollution source or an existing recreational facility is the primary measurement unit indicating aesthetic quality for the latter factors. As previously stated, the evaluated cell is rejected if a pollution source or a competing recrea- tional facility is located adjacent to the cell. The four physical factors indicating aesthetic attractive- ness are: 1) water to land relationship, 2) contour differen- tial, 3) forest color contrast, and 4) amount of forested land. The aesthetic index was a composite or collection of quantitative information reflecting measurement units of the specific resource, as well as its associated weight (a1...au). which was determined by its ability to generate related camping activities. Because the index represented the effects of four physical criteria on aesthetic value, the index was assumed to be additive. The individualphysical factors were assigned measurement units: 1) water to land relationship as percentage, 2) contour differential as feet, 3) forest color contrast as vegetative type dominating the canopy, and 4) amount of forested land as percentage. 118 A classification scheme was deve10ped in order to rank the incremental levels of measurement of each aesthetic indi- cator. The scheme used values from zero to ten to represent various measurement levels. The water to land relationship for each cell was determined in a stepwise sequence outlined below: 1) 2) A cell gridawork, using one-square kilometer cells as the unit, was superimposed on the United States Geological Maps, 7é-Minute Series, utilizing Universal Transverse Mercator Grid lines to determine cell boundaries. Over each 247.1 acre cell, a twenty-five sub-cell grid was superimposed. 3) A tabulation was made for each cell listing the total 4) number of sub-cells covered by water bodies, and the total number represented by land surfaces. A percentage was computed yielding a water to land relationship, as shown by the following equation: Percent of _ Number of sub-cells water water 25 Percent or = (100%) - (Percent of water area) land 5) A ranking value (0 to 10) was assigned to each cell based on its water to land relationship, Table 6, p. 70. Contour differential, the second physical factor essential to developing an aesthetic index, was likewise calculated by a stepwise sequence. 1) A cell gridwork, using one-square kilometer cells as the unit, was superimposed on the 7é-Minute Series, of 119 the United States Geological Maps of Orleans County, where Universal Transverse Mercator Grid Ticks determine cell boundaries. 2) The lowest and highest contours were located and recorded for each cell. 3) The contour differential per cell was found by sub- tracting the lowest contour from the highest contour for the cell. 4) From the list of contour differentials figured for all cells in the study area, the maximum contour differ- ential for any one cell was found to be 100 feet. 5) A classification was established for the contour dif- ferential using lO-foot intervals. Ten-foot incre- ments of contour differential were equated to one unit of increased ranking, Table 7, p. 72. Forest color contrast was derived from an analysis of forest cover types within Orleans County, New York. A classification scheme was designed which yielded four generalized classes of forest cover: 1) deciduous, 2) coniferous, 3) mixed deciduous and coniferous, and 4) swampland-brushland. From the four generalized classes of forest cover, meth- ods were sought to determine dominance within the cells. Figures 6, 7, 8 and 9 represent the four classes of forest cover species. As illustrated in Figure 6, the dominant species in the deciduous forest cover type include beech, maple, elm, and white ash. Figure 7, typifying the coniferous forest, contains species of white, red and scotch pine. Hemlock may be included 120 as defined by Ferguson and Mayer.60 The mixed deciduous- coniferous forest type, Figure 8, includes hemlock and white pine, in addition to sugar maple, beech, and yellow birch. Figure 9 symbolizes those cells showing the brushland-swamp- land type of forest cover. Willow, cedar, thorn-apple, cottonwood and white ash are dominant in this area. Measurement sources were selected and various degrees of error were experienced in attempting to determine the classes of forest cover on a per cell basis. Information concerning forest cover types was not available on a cell basis nor was information available in a form which allowed the investigator to spatially analyze the county in the desired degree of intensity. The major problem was that information concerning forest cover types was not available on a scale which was congruent with the 247.1 acre cell size used in this research. Therefore, various sources of data had to be integrated into an approximation of forest cover classes. Sources of data to measure the dominance of forest cover were derived from the Atlas of Forestry of New York, aerial photographs, observation transects of individual cells, New York State LUNR maps, and personal knowledge of the study area. The following stepwise procedure was utilized to approximate the classification of forest cover: 60Ronald R. Ferguson and Carl E. Mayer, Timber Resources of New York State. 121 Figure 6: Deciduous Forest Cover Class, Orleans County, New York Figure 7: Coniferous Forest Cover Class, Orleans County, New York 122 Mixed Deciduous—coniferous Forest Class, Orleans County, New York Figure 8: Swampland-brushland Forest Class, Orleans County, New York Figure 9: l) 2) 3) 4) 5) 123 It was recognized that not all cells were occupied by forested land. Therefore, only cells which had at least twenty-five percent of their area occupied by forested land were analyzed. This was determined from New York State LUNR maps containing the percent of forested land per cell. Cells 803,229; 803,246; 798,251; 783,223; 784,236; and 787,254 were surveyed by transacting them. These specific cells were selected from the county's total cell population because they displayed both a minimum twenty- five percent forest-cover acreage, and matched one of the sub-regions identified by the Atlas of Forestry of New York State. For the six cells, dominance was estimated by counting the number of trees belonging to the forest type with- in the overstory, along a transect, and parallel to it ten feet on either side. Dominance is defined as the greatest number of trees belonging to a forest type within the overstory. Each cell was classified as one of the four forest cover categories, based on percentage of forest species. That is, cells were ranked according to the dominance of either deciduous, coniferous, mixed-deciduous and coniferous , or swampland-brushland. Aesthetic rankings were determined for each of the four forest-cover classifications, based upon their potential for generating forest color contrast on a total year 124 basis. The color potential for each category of forest cover was based upon three factors: 1) the number of different vegetative colors produced during the year, 2) the intensity of color (assuming that oranges and reds are more vivid than yellow, greens and browns) and 3) the duration of the color theme. The mixed-deciduous and coniferous type received the maximum value of ten, because autumnal contrasts of green needles with red, orange, and yellow hues produces the brightest scheme, and even during winter and spring the presence of the pines and hemlock tinge the forested area with green. The second most pleasing color contrast was assigned to deciduous areas (6.6), where green dominates both spring and summer; the autumn's multi-colors generate a wide color array, and only winter has darkened colors. The coniferous areas were assigned a ranked value of 3.3 because of their yearly color consistency. Least ap- pealing, aesthetically, was the swampland-brushland type of cover. Although color contrasts do occur with- in swampland-brushland species, that category was assigned a value of zero based upon the following limitations: 1) color contrasts are usually non-vivid browns-yellow hues in autumn, or monochromatic during spring and summer; 2) reduced accessibility to view the vegetation because of poor drainage, and 3) immature stand of trees. Decimal values of 6.6 and 3.3 reflect the distribution of the rank values, ranging from zero 125 to ten, among the four types of vegetative cover. (A spread of ten rank units over four categories, separated by equal values, creates this decimal situation for deciduous classification, as well as the coniferous type, as 10 f 3 = 3.33...) The aesthetic rankings are shown in Table 8. The fourth physical factor, amount of forested land, is the final remaining aesthetic indicator within the composite aesthetic index. The amount of forested land was derived from existing percent categories of forested land within each cell. The information was obtained from a land use study originating 61 On the LUNR map each cell was ranked in one from LUNR data. of five categories, based on percentage of its own forested land. Higher percentages of forested land yielded a higher aesthetic value on a per cell basis. The percentage of forested land was ranked between zero and ten, as illustrated in Table 5, p. 69. Decimal values indicate arbitrary assignment of a range of ten, equally distributed among the number of per- centage categories of forested land. The objective function relating to the aesthetic value of each cell has been previously outlined and discussed. The com- posite index, which was derived, indicates a summation of those four physical factors most responsible for any cell's total aesthetic value. Hence, the highest composite total identi- fies those cells which have the greatest potential contribution 61Genesee/Finger Lakes Regional Planning Board, Report Pre- pared for the Orleans County Planning Board, Orleans Count Land Use: An Inventory and Analysis, (Rochester, N.Y.: Genesee Fin- ger Lakes Regional Planning Board, 1970), p. 15. 126 toward a pleasing aesthetic appearance and a high value. As before, a computer mapping routine generated a visual display of the value of the objective function, allowing the decision-maker to select those cells with the highest compo- site score. Therefore, the high level cells ranging from 47.8 to 71.70 or, dark shading were selected to satisfy the so stated aesthetic objective function. (See pages 194-197 in the appendix.) The analysis of the preceding objective functions to simulate community priorities has been discussed and its application outlined. Individual maps have been produced reflecting property tax revenue loss, deve10pment cost, total cost, and a composite evaluation of aesthetic characteristics. Each map reflects a single objective function on various levels of intensity. The individual maps presuppose that the community's priority is based upon a single resource component. Therefore, under this assumption, the objective functions could be stated and mathematical equations derived. Even though a community may establish a priority for a specific objective function or resource component, it may also wish to include and rank other objective functions or resource components accordingly. In order to include the major resource components within the planning model, to simulate community priorities, an analytical framework must be established. The investigator has chosen to map three of the established objective functions in combination. Property tax revenue loss, deve10pment cost, and the composite aesthetic index were selected as the major 127 decision variables in establishing the major combinations. Since each of the three variables was mapped at three levels of intensity, a combination mapping output would yield twenty- seven individual maps. These computer maps would express the possible combinations necessary to simulate the various rankings and alternatives of the selected objective functions, for a decision-maker within a community. The various com- binations are expressed by the following tabular relationships in Table 14, p. 128. Each of the combinations expressed in Table 14 is represented by a computer map within the appendix (pp. 198-305). These maps are read in combinations for three objective func- tions, each expressed at one of three levels of intensity. The objective functions are mapped in the same order for all twenty-seven computer maps: firstly - property tax revenue loss; secondly - development cost; and lastly, rank on aesthetic index. The three levels of intensity used for mapping each objective function include low, medium and high values, denoted as L, M, and H in each map title. Each map is mapped at two levels, where level one repre- sents rejection of those cells unlike the specified combina- tions, and level two represents acceptance of those cells fitting the required objective function combinations. For example, the 594 cells at level one did not match the requirements of low property tax revenue loss, low development cost and low aesthetic index; whereas, the county's remaining 462 cells did have low property tax revenue loss, low development cost and 128 TABLE 14 COMRINATIOTS OF RANKED OBJECTIVE FUNCTIONS Objective Functions: 1) Property tax revenue loss 2) Development Cost 3) Aesthetic Index Rankings of each function: R L high; M = medium low H H A. TWO LEVEL: Property Tax Revenue Loss interacting with Development Cost Property Tax Revenue Loss L H H Develonment L LL LN LR Cost N NL NE NH 8. THREE LEVEL: Combinations of PrOperty Tax Revenue Loss—Development Cost interacting with Aesthetic Index Aesthetic Index L H H Property Tax LL LLL LLM LLH Revenue Loss— Development LN LML LMM LMH Costs LH LHL LEM LEN ML HLL HLH NLH BID? PTTIIJ IiPifi 119111 14H IIHIJ RUTH Wifli HL HLL HLN HLH tIPE £1111; IIYTPI 111111 HR NHL HHM HRH 129 low aesthetic index values, and therefore, were mapped at the second level (Table 8, pp. 198-201 in the appendix). Shadings of two intensities were used to identify these two levels: accepted cells appeared in darker tones, rejected cells appeared in lighter tones. These ranked combinations of objective functions, (as shown by the computer maps on pp. 198-305), helped identify specific cells which matched their criteria, and thereby enabled the decision-maker to pick ones which would comply with the priority alternatives established by the community. Table 15, p. 130, lists the computer maps, the combinations of objective functions which were mapped, in addition to the frequency of cells accepted at level two, and rejected at level one. Certain conclusions can be drawn from the frequency of cells mapped at these combinations. Firstly, there is a direct correlation between property tax revenue loss and deve10pment cost per cell. That is, cells having a low property tax revenue loss usually have a smaller deve10pment cost, and visa versa. The computer maps displayed in Tables 8, 9, and 10 in the appendix substantiate this by showing 462 cells, 338 cells, and 17 cells in Orleans County having both a low property tax revenue loss and a low development cost. Table 32 also isolated ten more cells in Orleans County which had a high deve10pment cost and a high property tax revenue loss. The direct relationship between property tax revenue loss and development cost is further substantiated by the cell frequencies on computer maps 20 and 21, each showing FREQUENCY OF CELLS MAPPED AT THREE LEVELS OF INTENSITY FOR THREE OBJECTIVE FUNCTIONS 130 TABLE 15 Appendix Table Combinations of Frequency of Cells Number Objective Level 1 Level 2 Functions Mapped (Rejected) (Accepted) 8 LLL 595 462 9 LLM 718 338 10 LLH 1039 17 ll LML 955 101 12 LMM 980 76 13 LMH 1049 7 14 LHL 1056 0 15 LHM 1056 0 l6 LHH 1055 1 17 MLL 1053 3 18 MLM 1052 4 19 MLH 1056 0 20 MML 1040 16 21 MMM 1040 16 22 MMH 1056 0 23 NHL 1053 3 24 MHM 1055 l 25 MHH 1056 0 26 HLL 1056 O 27 HLM 1056 o 28 HLH 1056 0 29 HML 1056 0 3o HMM 1056 0 31 HMH 1056 0 32 HHL 1046 10 33 HHM 1055 1 34 HHH 1056 o 131 sixteen cells having medium valued property tax losses and medium deve10pment costs. These findings appear true in most cases, since the model utilized assessed land values to compute both the per cell property tax revenue loss and the per cell estimated acquisition cost. Estimated acquisition cost is one of three components of the development cost per cell. (See pp. 114-115, where development cost includes the summation of acquisition cost, drainage cost and transportation construction cost.) variations in this direct relationship between property tax revenue loss and deve10pment cost per cell would be caused by other large development costs as drainage cost or transport- ation construction costs. The LML combinations (Table 11) and LMM mappings (Table 12 in the appendix) both illustrate a digression between low property tax revenue loss and a medium development cost. For those 101 cells (LML) and 76 cells (LMM) within Orleans County having larger development costs than property tax revenue losses, perhaps poor drainage and high transportation costs were the cause for this variation. Conclusions regarding the aesthetic index were less obvious than the direct relationship between property tax revenue loss and development cost. After surveying the fre- quency of cells in Table 15 though, it was noted that there were fewer cells having a high aesthetic ranking in conjunction with a low property tax loss and low deve10pment cost (17 cells), than there were cells having a low aesthetic appeal, along with 132 low property tax revenue loss and low development cost (462 cells). That trend was also recognizable in the frequencies for mapped combinations of low property tax revenue loss and medium development cost: only seven cells had high aesthetic appeal, whereas 101 cells had a low aesthetic rank (Tables 11 and 13 in the appendix). The mapped combinations which showed low property tax revenue loss, low development cost and high aesthetic index (Table 10, in the appendix) will be explained in the conclusions chapter to follow, because they comply with the selected objec- tive functions of this research, and represent those cells most suited for the campsite location. The county's ten cells which have least adaptability for a potential campsite would be those having high property tax revenue loss, high development costs and low aesthetic index. Such cells will be identified and explained in Chapter V. CHAPTER V RESULTS An attempt has been made to develOp a planning tool to assist community decision-makers in selecting feasible sites for a public recreational development. The model simulates hypothetical community priorities through the use of objective functions. Each objective function represents a hypothetical community priority. However, it may be recognized that each objective function realistically identifies specific physical, economic and aesthetic resource components ofa study area, and these components may be incorporated in the desires of the community. Measurable variables have been assigned to the resource components so that a spatial evaluation may be made. From the spatial evaluation of individual cells, specific sites may be selected in order to satisfy the stated objective func- tions. Furthermore, various combinations and various rankings of decision variables yield a spatial array of feasible sites. From this spatial array, cells indicating a specific pre- ference can be located within the study area. As we change community preferences, or change priorities, the spatial array of desirable cells also changes. Thusly, locational tradeoffs are visually portrayed. A visual analysis of the combination maps generated by the GRID computer routine expresses the locational tradeoffs. 133 134 The model exhibits considerable merit as a preliminary screening device for planning purposes. The strengths of the model can be discussed in relation to the individual objective functions simulated for Orleans County. Computer maps as shown in Tables 1 through 7 (pp. 170 to 197 in the appendix) illustrate single objective functions, or a component thereof, each at three levels of intensity (low, medium, and high). Computer map 3 (Table 3 in the appendix) is a simulation of the first objective function, property tax revenue loss. It shows an absolute range of values from 8 152.14 per cell to $ 9,999.99 per cell. Three levels of intensity were established, as illustrated on page 181 of the appendix, in order to categorize each cell. Cell groups included in the display were: 1) 961 cells were selected representing low property tax revenues (ranging from 8 152.14 to 8 3,434.76 each); 2) 43 cells were chosen as medium property tax losses (ranging from 8 3,434.76 to 8 6,717.37); 3) 11 cells of high property tax value were selected (ranging from 8 6,717.37 to 8 9,999.99); and 4) 41 cells had no property tax value since they occupied federal and state properties. The second objective function, deve10pment cost, is repre- sented by Map 5, (Table 5 in the appendix). These range from zero development cost dollars (no existing cells) to an upper development cost of 3 399,868.38 (810 feasible cells). The middle range in deve10pment cost was $ 133,289.44 to 8 266,578.88 per cell, where 230 cells from the county qualified. The high range for development cost was $ 266,578.88 to 3 399,868.38 per cell. Sixteen cells were selected from the county in this category. 135 Total cost was the third objective function, which was simulated for Orleans County (see Map 6, Table 6 in the appendix). The total cost range for the study area was from zero dollars to A 409,868.25 per cell. Categories of cells and their total cost for recreational development include: 1) 824 cells at values from zero to 8 136,622.75 (low); 2) 216 cells at ranges between E 136,622.75 and 8 273,245.50 (medium); and 3) 16 cells ranging from 8 273,245.50 to 8 409,868.25 (high). The fourth objective function displayed on Map 7 (Table 7 in the appendix) reflects the aesthetic index. It was a composite score ranging from zero to 71.70. The range of low values was zero to 23.90, in which 595 cells complied. Medium value range, from 23.90 to 47.80, generated 436 cells from the county. The high aesthetic range included values from 47.80 to 71.70; twenty-five of the county's cells were designated in this category. Computer Maps 1 and 2 (Tables 1 and 2 in the appendix) were included because the mean per acre assessed land values were important in the estimation of per acre acquisition costs, as well as the calculation of per cell development costs. Those maps simulating a single objective function, (maps 3, 4, 5, 6 and 7) did not effectively isolate cells at three levels of intensity. This resulted from an analysis of too few levels for each objective function. Also, there was an unequal distribution of tax revenues for all cells within each category, resulting in the greatest cell frequency in the low-valued category. The effectiveness of a single objective function, based 136 upon a single community priority, can be strengthened if we can isolate a fewer number of feasible cells. The decision- maker can increase the sensitivity of the model, when dealing with a single objective function, by merely increasing the number of levels. This may be a solution for the use of single objec- tive functions. However, as we increase the number of mapping levels, and integrate or combine objective functions, dif- ficulties arise. The difficulty stems from the total number of combinations possible in simulating multiple objectives. As we increase by one additional level of intensity, the number of combinations increases exponentially. The result is an extensive array of theoretical combinations. For example, at two levels of intensity for each objective function, four 2). Whereby, the addi- objective combinations are possible (2 tion of a third function produces twenty—seven feasible combin- ations (33). Table 14, p. 128 illustrates this exponential relationship between the number of levels of intensity and the resulting number of combinations produced. Because the number of combinations of objective functions increases exponentially with greater number of levels, a greater number of alternatives become available to community decision-makers. For the above reason, it was decided that the mapping of objective function combinations at three levels of intensity would offer the decision-maker an operable number of alterna- tives. From these alternatives or twenty-seven feasible com- binations generated (33), the decision-maker selects those combinations which best reflect the priorities of the community. With those combinations selected, the decision-maker can 137 therefore scan the mapping sequence and isolate those maps generating the desired combinations. The cells either accepted or rejected within each combination map can be pinpointed on map surface and their grid locations identified. Those cells accepted by the computer routine for matching the objec- tive function combinations, will be mapped in a darker shade. Those cells represent those combinations in which the community has identified as being more optimal. Each cell therefore becomes a feasible location for a public recreational facility, i.e., a campground. For example, the seventeen cells of darker shading shown on Table 10, pp. 207-8 , are the areas selected for a potential campground, assuming the county's priorities include low property tax revenue loss, low development cost, and high aesthetic appeal. From the application of the model to Orleans County Specific recommendations can be made concerning the selection of feasible sites. As we view the various combinations of ob- jective functions mapped, specific combinations tend to sup- port a community's overall preference. Mainly, a rational decision-maker would select that combination which incorporates low property tax revenue loss, low development cost and a high aesthetic index. This combination (LLH) satisfies the indivi- dual or single objective functions previously established by the model. These single objective functions: to minimize property tax revenue loss from the acquisition of private land by the public sector, to minimize development cost of a recrea- tional facility, and to derive themaximum benefits socially perceived from the aesthetic qualities in nature are 138 incorporated within this combination. These objective functions are integrated within the LLB combination. The researcher concludes that those cells accepted by the computer routine isolating the LLH combination should be selected as feasible cells for a campground. In referring to Table 10 on pages 207—208, seventeen out of the 1,056 cells were accepted to represent the LLH combinations. Cells 806,242; 806,252; 304,242; 803,227; 803, 238; 803,239; 803,240; 802,238; “01,238; 799,233; 796,230; 795,252; 795,253; 793,252; 792,225; 788,225; and 784,236 were selected as feasible sites for a campground. This array of cells can be visualized on pages 206 to 209 in the appendix. Page 207 represents the eastern-half of Orleans County, whereas page 208 represents the western-half of Orleans County. In analyzing the selected LLH cells, some observations can be made about their location. Many of them are equally distributed throughout the county; however, there is a group of cells positioned within the Township of Carlton, which reflects a pattern. These cells are aligned with Oak Orchard Creek following its course from Waterport to Point Breeze on 'Lake Ontario. These cells generate relatively low property tax revenues, a low deve10pment cost, and highly contribute to aesthetic appeal because of their proximity to water. Furthermore, these cells represent variations in elevation associated with the stream's eroding action; hence, adding to the aesthetic qualities of the selected feasible cells. It is this array of cells that the researcher has isolated and highly 139 recommends that a site be selected for a public campground facility, if sufficient demand exists. The locations of individually scattered LLH cells in the county are less easy to define than is the cluster of cells near Oak Orchard Creek in the Township of Carlton (Table 10). Yet, most scattered LLH cells contain a creek and are traversed by at least one highway (eg. 803,227; 799,233; 796,230; 804,242; 795,252; 795,253). The listing below helps to substantiate this grouping of LLH cells within Orleans County: Cell Creek or River Roadfls} 803,227 Johnson's Creek Yates Center Road; Blood Road 799,233 Oak Orchard River Kenyonville Road 796,230 Oak Orchard River Ridge Road 804,242 Beardsley Creek Marsh Creek Road Marsh Creek 795,252 Sandy Creek, Ridge Road, East Sandy Creek, Groth Road West Sandy Creek 795,253 East Sandy Creek Ridge Road The location of three more individual LLH cells was bordering a lake. Cells 806,242 and 806,252 (Table 10 in the appendix) were located on the shoreline of Lake Ontario. In addition, each was adjacent to the Lakeshore Parkway and had secondary roads crossing them too. Another scattered LLH cell, 792,225, bordered the east end of Glenwood Lake near the village of Medina. That cell also had a road for transportation purposes. The location of LLH cell, 793,252, in the Township of Murray 140 was unique, for the Erie Barge Canal cut through the southwest corner of the cell. Table 16 summarizes the major economic, physical and aesthetic data available for the seventeen LLH cells selected by the GRID routine as potential campground locations. Each cell was accepted because it fit the objective of this study: low property tax revenue loss, low development cost and high aesthetic appeal. Analysis of data from the LLH cells (Table 16) can more clearly illustrate this relationship: 1) Tax revenues generated by LLH cells remain small (8 566.93 per cell as minimum and $ 3,337.59 per cell as a maximum). Selection of such cells would keep the losses down. 2) The development costs of such cells were relatively low and included acquisition cost, transportation construc- tion costs and drainage costs. The dollar ranges for each of these expense areas were relatively low, which helped keep development costs down. For example: a) acquisition costs per cell ranged from a minimum value of 8 8,901.77 to a maximum of $ 95,414.30. b) road costs for cells having roads through their centers was zero, with one road transportation cost ranging upward to $ 690,476.00. 0) low drainage costs per cell were reflected by a cost range between $ 4,942.00 and $ 69,188.00. 3) The total aesthetic index ranged from a low of 48 to a high of 71.7, which indicated lands of a high aesthetic 141 0.0: 0.0H o 0 o.oa 00H.m00 0mo.0maa sa.0m0.0sa oe.0sm.awso.0aaa 00.300 0mm.:0s m.00 0.0 s a 0.0 oma.es o oa.0mm.:m sH.mmm.H ee.s0 0m.ms 0-.00s n.50 0.0 0 0 0.5 oma.es 000.00H 00.0mm.ae m0.sss.H 00.0HH m0.sm 0-.~ms m.00 0.0 0 0 0.0H Nem.s 0a:.om0 33.000.00 ss.m00.a as.s0 ao.am ~0m.maa «.0: 0.0 e 0 0.0H mea.s H00.m00 ss.sao.00 a0.0o0.m 00.0ma mm.0s m0~.0ms ~.H0 0.0 a a 0.0H Nsm.e Haa.0sm mm.aam.0m mm.omo.m a0.soa no.0: ~0~.0os s0: 0.0 a e 0.\. ~35 0 0053.00 00.300 00.33 3.0: 09.03. «.0: 0.0 0 m 0.0 oma.es 0ss.oa0 NH.0HN.00 0m.0HN.H 0s.00 ms.0m mmm.mms «.00 0.0 0 H 0.0 00H.00 o 30.000.H0 mo.:0m.a H0.0NH 0s.00 00N.Hom s.aa 0.0 0 a 0.a 00H.m0 Haa.0sm sm.mmm.mm 00.000 mm.s0 HN.NN 00m.mo0 m.s0 0.0 0 0 0.0 00H.m0 H00.m00 00.Hs0.sm om.sam 0s.mm 00.3: osm.mom s.m0 0.0 0 0 0.s 00H.m0 000.00H 00.0so.o0 00.00:.H 00.0:H 0m.0s mmm.mow s.H0 0.0 a 0 0.s 00H.m0 000.0mfl 00.0H0.00 sm.o0m.a 00.00H os.o0 00m.0ow 5.00 0.0 0 m 0.s 00H.00 HOH.0sm 0s.HNN.em oa.mmfl.a No.00 mm.om s-.mom 5.0a 0.0 0 0 0.s 00H.m0 0mo.0ma mm.m0s.:0 0o.H30 00.00 0a.:m Ns~.:om N.m0 0.0 0 H 0.0 00H.00 ma0.0m0 os.os0.00 m0.sao.a as.am as.s0 ~0N.0om N.H0 0.0 0 0 0.0 00H.m0a 000.00H0 0s.0o~.a00 om.s0s a 50.05 0 s0.0ma mam.0ow c t 2.“ a e _ . m e m 0.. mm. m .10.... ...; ”mm mm 0.... we. mam... mt mxm mnmm 00...... us 300 mam mam a... 00m 0% “new .00 as. :03 .00 3 Tel FCo ano pc 00 r sent a. % m M “mama .m Anna C NEH... Ni FC D mmtnnw Anny mqqmo mam m.waz=oo mzemqmo mom eyes oHemmemm< oza.q¢onwmm .onozoom 0H mumda 142 appeal. Individual rankings for the aesthetic indicators were generally high, which caused large composite scores for these aesthetic indices. The four aesthetic factors listed for LLH cells showed ranges as follows: a) percent forest cover (5.0-10.0) b) contour differential (1 - 9) c) water to land relationship (0 - 8) d) forest color contrast (6.6 or 10.0) Each cell can be isolated and individually analyzed in order to determine which specific cell would be most suitable for development. As stated previously, it is not the purpose of this model to select a specific cell; but rather, to pre- sent an array of feasible cells, from which the decision-maker can ultimately determine the site. It is also recommended that cells representing the HHL combination, high property tax revenue loss, high development cost and low aesthetic value, shown in Table 32 on pages 294 to 297, not be chosen as feasible cells for the deve10pment of a campground. This combination of objective functions yielded ten out of 1,056 possible cells within Orleans County. These cells complied with HHL characteristics. The grid coordinates of the HHL cells include: 800,226; 792,240; 783,248; 782,240; 782,247; 782,248; 781,248; 780,237; 780,248; and 780,249. By locating these cells on the computer maps, a clustered pat- tern occurs within the southeast portion of the county, page 296. In analyzing this clustered pattern by the use of supportive materials, such as the Orleans County plat maps, 143 U.S. Geological Survey Maps, and the Soil Conservation Survey Maps, an understanding of this pattern can be reached. Cells 783,248; 782,247; 782,248; 781,248; and 780,249 occupy muckland situated.in the Township of Clarendon. Other HHL cells with similar swampland or muckland characteristics in- clude two scattered in thesunnnicentral part of Orleans County. Both cells 782,240 and 780,237 occupy muckland or swampland in the Township of Barre. Muckland reflects high property tax revenus, due to intensive vegetable farming, high development cost, because poor drainage results from high organic content within the soil. Furthermore, transportation construction costs are higher resulting from poor drainage and unstable road foundations. Aesthetic values are not generated within this area since there is little t0pographic variation, no substan- tial areas of water-based recreation, and minimal forest color contrast. To help substantiate these conclusions, Table 17 below provides economical, physical and aesthetic data pertain- ing to the county's ten HHL cells. High property tax revenues generated from intensive vegetable farming on muckland are illustrated in Table 17 by the column labeled "Total Tax Revenue." Seven of the ten HHL cells analyzed produce more than nine thousand dollars per year in taxes. The probable cause of high development costs in these muck- land cells may be explainable by: 1) the presence of high drainage costs, which may be attributable to organic soils, impervious sub-strata, 144 0.0 0 0 0 0.0 000.00 000.000 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000.0 00.000.000 00.000.0 00.000 00.000 000.000 0.00 0.0 0 0 0.0 .000.00 000.000 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000.0 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000 00.000.000 00.000.0 00.000 00.000 000.000 0.0 0 0 0 0.0 000.00 000.000 00.000.000 00.000.0 00.000 00.00 000.000 0.0 0 0 0 0.0 000.0 0 000.000 0 00.000.0000 00.000.00 00.0000 00.0000 000.000 .0 t000000t e 0 ... .0. ea .5 n Tmch Fan Mnm pi FCR aC mama .mnw mstvc W %V wwv Cm A m 00.0. m thw W R P A PA L Mn 00000 000 0.002000 0200000 000 0000 000000000 020 00000000 .00202000 00 00000 145 flatness of the landscape, and lack of natural streams. 2) large road construction costs (3 138,095 - $ 2,07l,h29) which may be generated by poor drainage, general absence of roads through the muckland areas, (only two cells referenced as HHL had any road) and unstable road foundations. 3) excessive acquisition costs, where eight of the ten HHL cells noted exceed $ 300,000 each. Muckland-swampland, which has dominated the HHL cells in Orleans County, produced very small total aesthetic index values (zero in four cells; 18.2 in one cell). Topography varied little in these lowlands, as six of the ten cells had no relief change, and a rank of zero. The rank of zero for all ten cells in the Water to Land Relationship Column of Table 17 indicates that there were no identifiable bodies of water (eg. rivers, creeks, lakes or canals). Cnly HHL cell 781.2fi8 had sufficient forest cover to provide moderate color contrast. All remaining HHL cells had either no forested area (zero rank), or less than 10% of their area forested (rank of 2.5). With the absence of hills, lakes or streams for water recrea- tion, and noticeable forest cover, all HHL cells had little or no aesthetic appeal. Cells 800,226 and 792,2h0 were both accepted by the out- door recreation land use selection model as HHL cells, yet neither is muckland normampland. The low aesthetic appeal may be due to the absence of streams and other bodies of water, the small contrast in topography (ten feet for cell 800,226 and 146 thirty feet for cell 792,240), and the near absence of wooded area which could generate little or no color contrast. Cell 800,226 represents flat, fertile farmland, in the Township of Yates, southeast of the village of Lyndonville (Table 32). Perhaps its high development cost resulted from a large acquisition cost and a large road transportation construction cost. The cell has two roads, one forming its southern boundary, the second serving the southeast corner of the cell. Cell 800,226 has a large transportation construction cost estimate because its existing roads are near the cell's boundary and the cell's center is the basis of calculating construction cost. The high property tax revenue generated in cell 800,226 is attributed to its intensive use in vegetable production. The locationcn'the other scattered HHL cell, 792,240 is bordering the village of Albion, where there is no forested land, no body of water, and only a network of highways. The high development cost of cell 792,2h0 may be due to the high acquisition cost. These ten HHL cells should not be considered for recreational development in Orleans County. It can be recognized that a decision-maker may wish to select cells based upon other alternative combinations of objective functions. The land use selection model deve10ped in this research offers this option and should be considered if valid reasons dictate that cells of the LLB combination are proven to be unsatisfactory. However, it is the recommen- dation of this study that the LLH cells match community priori- ties and have the potential to fulfill the desire of the camper within Orleans County, New York. CHAPTER VI SUMMARY, CONCLUSIONS AND RECOMMENDATIONS m This research project has been designed to develOp a recreational planning model for the selection of feasible re- creational sites. An inventory information system.was constructed and data collected to evaluate Orleans County's resources. By use of an information inventory system, feasible sites can be selected based on community priorities. The community priorities or objective functions indicated which resources either economic, physical, or aesthetic, or various combinations thereof were important to that community. The objective functions were used to simulate decisionsof the communities. Their decisions were simulated through the use of computer mapping techniques and were visually displayed. By establishing hypothetical objective functions and by_ranking their individual importance for the community, Optimal cri- teria were formulated for the selection of individual cells. It was the researcher's assumption that those cells complying with low property tax loss, low deve10pment cost, and high aesthetic index would most nearly represent community op- timality. Therefore, through computer simulation techniques 147 148 those cells fulfilling the desired criteria were mapped and their locations analyzed. From 1056 cells within the study area of Orleans County, 17 cells were chosen as feasible sites. These cells were individually analyzed to determine if the model indeed did choose the feasible sites based upon community priorities. From the analysis, it was validated that those cells did fulfill the hypothetical objective functions. In evaluating the feasible sites selected by the model, it can be shown that each of the seventeen LLH cells did fulfill the model's criteria (see pages 137-l#2). Furthermore, by visiting each selected cell it was found that many either contained an outdoor recreational facility or are adjacent to a cell containing a developed recreational site. The following cells indicate the validity of the selection model: -cell 806,2h2, site of undeveloped Oak Orchard State Park, a marine type park for boating, picnicking and gamefields; -cell 806,252, a feasible site adjacent to the Lake Ontario Parkway, a scenic drive from Rochester to Lakeside Beach State Park; -cell 803,227, adjacent to public golf course and to Johnson's Creek; ~cell 803,238, contains subdivided tracts for recreational cottages; -cell 803,239, adjacent to Oak Orchard River with sub- divided tracts for recreational cottages; -cell 803,2h0, contains subdivided tracts adjacent to a country club; 149 -cell 802,238, contains portion of Lake Alice, with subdivided shoreline having developed cottages; -cell 801,238, contains Lake Alice with developed recrea- tional cottages; ~cell 799,233, Oak Orchard River widens and meanders through the cell, undeveloped but having the potential for camping and boating; -cell 796,230, contains portion of Oak Orchard River and tributaries, undeveloped but having potential for camping and canoeing; -cell 793,252, contains private recreational deve10pment with swimming and picnicking; -cell 792,225, adjacent to Glenwood Lake and Medina Con- servation Club, with nature trails, picnicking, campsites, and recreational vehicle trails; and -cell 78u,23€, contains future site of Barre Rod and Gun Club, with outdoor activities. From the seventeen LLH cells selected by the model, thir- teen cells exhibited either an existing recreational facility under present use, or are planned for recreational development, or exhibit recreational potential. From the deve10pment of and the application of the simulation model, conclusions and recommendations can be derived. 150 Conclusions The model exhibits both strengths and weaknesses in the direct application as a planning tool for the selection of a public recreational facility, a campground. A major weakness within the model's design is the mapping output of the single objective functions. Specifically, with three mapping levels utilized, (low, medium, high), generating a large range of values within each group, a large number of cells were selected within each group. As a result, the single objective function maps reduced their utilization as compared to the multiple- objective function maps. The model could have been made more selective if an increased number of mapping levels would have been assigned in the mapping procedure of single objective functions. It must be recognized however, that as we transfer the increased number of mapping levels of the single objective functions to the mapping of multiple-objective functions that the number of combination maps increases exponentially. This increase may add increased costs and evaluation time for the decision-maker in his cell selection procedure, since the number of alternatives also increases exponentially. The model is a preliminary screening device to facilitate the selection of feasible campground sites. The model is not calibrated to select a specific site for the decision-maker, or the community, because the model cannot differentiate between similar cells where each cell relates to a range of values rather than individual cell values. This limitation resulted 151 from the use of three levels of intensity for each objective function. The wide range of values at any one level contri- buted to the model's inability to isolate a specific cell from the array identified for matching community priorities. Thus the model selects a group of cells with like characteristics, all supporting a specific objective function, but no individual cell is isolated. The model could have been made more discrim- inating by increasing the number of levels of intensity in the mapping sequence. The application of the model as a planning tool is directly related to the size of the study area, the amount of detail available at a specific level, the size of the cell sampling unit, and measurable variables available to the decision-maker. The size of the study area dictates the degree in which data can be utilized effectively. Therefore, if the planning area was a township or municipality, data could reflect greater de- tail. In contrast, if a county or multi-county unit was select- ed as the study area, greater aggregation of data would occur. The aggregation process tends to reduce the amount of micro- information which can be stored within a sampling unit such as the individual cells. Furthermore, as we reduce the amount of micro-information which can be stored, greater aggregation error occurs. The measurement of economic, physical, and aesthetic characteristics of each cell greatly depends upon the measur- able variables available to the researcher. Information is not available at all sampling levels for all resource components within the study area. Therefore, the aggregation of data is 152 not derived from the same levels of intensity and measurement units have various degrees of precision. Deviations in the intensity of data can be shown by examining two variables and their data sources. A comparison between property tax revenues per cell and the estimated drainage costs per cell can be related to the specific problem. The number of observations taken within Orleans County to determine property tax revenues per cell were greater than the number of observations to estimate drainage cost. Approximately four thousand land parcels were observed to determine property tax revenues. In contrast, twelve soil associations were the basis for estimating the drainage costs per cell. As a result, the density of spatial data utilized for cost information estimates differed. Further- more, information was not equally distributed within the study area, since standardized measurements have not occurred over a geographic region. Known micro-information from a specific area often is discarded because of the scarcity of micro- information from adjacent areas. Therefore, we have a tendency to analyze only that information which is available on a uniform basis for all segments of the region. Another weakness of the model is its lack of sensitivity in measuring some physical characteristics precisely. For example, drainage costs were computed from agricultural tiling estimates based upon each cell's dominant soil association (Table 12). As a result, minute physical variations influencing drainage within each cell were not considered. If the study 153 area had been smaller than Orleans County, soil series and as- sociated types could be utilized and more precisely measured, to determine drainage costs. It must be also pointed out that the development of the aesthetic index to determine the most pleasing site for campers was constructed on a judgement basis. Its rationale was based upon the researcher's perception of optimal resource character- istics. The major objective of the researcher was to select sites based upon a diversity of outdoor recreational activities associated with camping. However, it may be necessary to determine various preferences of specific camping groups in order to further perfect the selection model. A weakness of the planning model is the implicit assumpu tion that campground demand was equal for all cells inventoried. Demand was assumed to be equal since the population was basically 62 Fur- rural with an average of 86 pe0ple per square mile. thermore, the total population of the two villages, Albion and Medina, was of relatively small size (11,416 people) when compared to the larger rural population of 23,172 people.63 If larger urban centers occur in other planning areas, there would exist a distinct difference in the demand for camp- ground development. Application of this research model to an area with unequal demands should be accomplished by integrating demand measurements into each cell's location. 62County and Citypata Book 1967, p. 252. 63Buffalo Evening News Almanac and 1222 Fact Book, pp. 129- 300 15h Lastly, the use of linear distances for figuring transpor- tation construction costs was a weakness inherent in the model. The values were based on a constant cost per unit distance supplied by the N.Y.S. Department of Environmental Conservation (Table 13). It must be recognized that this cost is an average value per mile, based upon a specific road type. Physical var- iations in soils, in parent material, in slope, and drainage patterns within individual cells have generated deviations in construction cost estimates, from the suggested New York State average. The model is not calibrated to reflect these physical discrepancies leading to possible differences in roading costs for secondary gravel roads. The model provides the decision-maker with an analytical framework to align community priorities with resource com- ponents of individual sites. The output of the model is a display of these objective functions produced by computer mapping. The analytical framework allows the decision-maker to integrate the economic, physical, and aesthetic characteri- stics of a study area for planning purposes. The framework serves as a screening device to isolate groups of feasible sites in order to satisfy specific alternative community objective functions as shown in the appendices. The model presents an array of feasible sites which can be indivudally evaluated in conjunction with information recorded within the original data file. In addition, the decision-maker may wish to use other data sources (e.g., the nearness of the proposed site to population centers) in order to facilitate a 155 single selection from the preliminary data array. The simulation model has application within other planning regions depending upon the clientele and their prescribed objectives. Other county units may utilize the analytical framework to solve similar problems. However, different land use characteristics in other counties must be considered and their values inserted into the model to reflect the structure and organization of resources in that area. Nevertheless, the model has the capability of being applied within other planning regions. Multi-county units and other population centers may apply this model to their own resource problems. The selection of feasible sites for other recreational land uses can be made byimeasuring different economic, physical, and aesthetic variables within a given area. Also, the community priorities concerning a different recreational land use may be adjusted within the selection procedure. Even though the variables and the community priority may differ, the model still offers the capability to select feasible sites. For example, if the recreational land use was golfing, substitutions such as the importance of topography rather than water to land relationship (used for camping) may be made. In this study, the author has utilized a county as the spatial unit to simulate community priorities. A cell size of 2&7.l acres was used as a resource inventorying framework for this study, in part because the New York State Land Use and Natural Resource System utilized the same cell size for inventorying county resources. Because of the congruency of cell 156 boundaries in the LUNR system and that chosen by the investi- gator for Orleans County, a recognizable integration of planning data is possible for the study area. Expansion of the proposed model resulting from its integrative properties allows future investigators to strengthen its applicability to planning. It must be recognized that the degree of integration allowable by the model depends upon many factors: 1) the time available for research, 2) monetary constraints, 3) the objective of the study, 4) the clientele, and 5) the need for additional var- iables as the use of the model is expanded. However, the pro- posed model is flexible enough to allow further modifications to fit a different problem context. In comparing the cost of producing planning maps used to locate feasible campground sites, it is found that the proposed land use selection model developed in this thesis is economically feasible. By comparing the computer method versus the man- ual method within defined cost areas (total, fixed, and vari- able costs), the economic feasibility of the planning technique can be illustrated. In calculating the costs for the computer and the manual methods, it is assumed that fixed costs are common for both techniques. These fixed costs involve the collection, recording and plotting of raw data, Therefore, a data file had to be organized and prepared for both techniques. This could be considered the major fixed cost. Since 770 man- hours, at $3.50 per hour, were devoted to developing the in- formation data file, the fixed cost equaled $2,695. 157 PC = Man-hours X hourly rate FC = 770 X 33.50 PC = a 2,695.00 However, as we look at the variable costs of producing the planning map sequence, by both computer and manual techniques, we discover large differences in preparation costs. The esti- mated variable costs for the manual method were $ 990.50, based upon 283 man-hours of labor at a work rate of $3.50 per hour. The estimated variable costs of the computer maps were only $34.00. This figure was based on a rate of $1.00 per computer map estimated by the Genesee/Finger Lakes Regional Planning Board. In analyzing total cost of map production by both techni- ques, the equation below was used: TC = 770 ($3.50) + 330 ($3.50) TC = $ 2,695.00 + $ 990.50 TC = $ 3,685.50 TC = total cost Map production via the manual method had a total cost of 8 3,685.50; whereas, the computer method cost a total of $ 2,729.00. From this cost information, it may be concluded that the computer method of producing the sequence of maps used in this planning model was more economically feasible. The simulation model visually portrays possible results of decisions made by the community. Since each cell is identified by locational coordinates, supplementary or complementary information may be integrated for analysis. The computer maps 158 visually illustrate locations and locational tradeoffs result- ing from changes in community priorities. Therefore, the mod— el's presentation to planning committees, agencies, and decision- makers can facilitate analysis of locational tradeoffs. Com- puter maps may be viewed individuallycu'in groups. Using these generated maps as a tool, decisions can be made by planning groups, or else individual decisions can be simulated. The visual display provides maps highlighting the area's resource base, and permits community planners a clearer understanding of the physical, economic, and aesthetic characteristics of their region. Property tax revenues, deve10pment cost, total cost, and aesthetics have been evaluated to assist communities in inventorying the resource components of their area. It is believed that the resource components of the selected study area were reflected in the variables and associated measure- ment units. Hence, the economic, physical and aesthetic characteristics of the area can be integrated into the decision-making and planning process. Within the model, a complete enumeration of all cells within the study was presented. The surveying of all possible sites within the study area allowed a partial inventory of the economic, physical and.aesthetic characteristics. The value derived from a complete evaluation of the county's resources tended to reduce the amount of bias since each cell was equally considered as a feasible site. If a county's land area is not uniformly inventoried to reflect the economic, physical and aesthetic concerns of its 159 population, effective planning can not occur. A single objec- tive function, property tax revenue loss, may not be reflected in other planning techniques. It is necessary to evaluate all feasible sites selected by a random sample design, in order that the economic, physical, and aesthetic concerns of the population may be considered in planning. Site selection bias is reduced by the fact that economic, physical and aesthetic concerns of a population are considered. In order to accomplish this, a uniform evaluation of the total study area is manditory. As we examine the objective functions we find that equal consideration is given to each. Other preliminary site sel- ection techniques as air photos and field reconnaissance methods only partially evaluate the county's resources. A major weakness of these methods is that they do not reflect the economic aspects of land value and property taxation. In addition, air photos may not show current land use patterns, as aerial field reconnaissance occurs less frequently than tax revisions. This study used the grid cell as a preliminary screening device instead of the air photo field reconnaissance techniques because: 1) feasible sites are more easily located on a grid system, 2) ease of updating planning information resulting from computer capability, and 3) summarization of micro-information by measures of central tendency for indi- vidual cells is made possible by the grid system However, aerial photographs complement the use of the grid inventory system. Detailed land use information exposed 160 by air photos may be transposed onto the grid framework. Therefore, the strengths of both techniques cantmecoordinated within a planning method. Preconceived knowledge or images of certain sites may directly influence the decision-maker, or planner in his or her selection procedure. It is hOped that by evaluating all possible sites and presenting the economic, physical and aesthetic data for each site, the decision-maker will obtain a comprehensive analysis of the county's resources assisting him in an unbiased decision. Furthermore, the evaluation system formulates a framework in which spatial information such as aerial photographs, soil surveys, property plat data, and distance relationships can be integrated into a framework which has coordinate location. It must be recognized that errors occur as one incorporates this information into a prescribed geographic unit. These errors occur from round-off, measurement, and aggregation procedures. Within this study, economic data extracted from individual farms were transferred onto the prescribed grid. measurement error resulted from the transferral of data from ownership boundaries to grid boundaries. Measurement error also resulted from the transferral of physical boundaries developed by soil characteristics into the 247.1 acre cell framework. The investigator recognizes that error does occur; how- ever, the system has the potential to reduce bias in site se- lection, to integrate eonomic, physical and aesthetic infor- mation, to facilitate the expansion of further information into the framework from other sources. The grid used is also 161 congruent with the existing LUNR System within New York State and corresponding satellite control points. Recommendations In incorporating demand within the analysis of feasible recreational sites, future researchers may wish to establish attractiveness indicators for feasible sites based upon near- ness to population centers. Demand may increase in more urban- ized areas, when compared to a rural county where this model was tested. Public opinion concerning the type of recreational facility desired may be an important facet of recreational demand for any study area. Through the use of opinion polls and community discussions, future researchers may be able to ascertain this element of human demand, before making specific decisions on the kind of recreational facility to be developed. Public opinion polls may also reveal specific preferences with regards to aesthetic criteria calibrated within the plan- ning model, to select specific sites from a feasible array. It is recommended that future researchers deve10p a classification system based upon individual outdoor recreational facilities. The rationale for this suggestion is that the data file may also be applicable to the selection of feasible sites for activities besides campgrounds, such as a public or private golf course, leisure home developments, ski areas and wildlife sanctuaries. It may also be recommended that an updating system be 162 initiated in order to keep pace with land use changes and pro- perty tax revisions, including assessments and taxing rates. Updating must occur on a yearly basis in order for a county to assess the tradeoffs from non-marginal land changes. As we analyze the alternative feasible sites selected by the model, it may be necessary for future researchers to construct a more detailed development cost framework. This detailed cost framework should include the actual cost of constructing a campground facility, including the water, septic, parking, and internal transportation system for the full year operation of that facility. It is recommended that once this cost analysis has been made for each alternative site that future researchers may indeed select an optimal site. It is recommended that this information system could be used as a part of a multiple-use system since the data collected can be used for other locational decisions. Fur- thermore, it is difficult to rationalize an investment of time and money in constructing such a system for one loca- tional decision. This data file could be part of a regional system, such as those constructed by regional planning boards. It is therefore recommended that this extension of the model is worthy of future investigation. This researcher contends that the grid inventory system has great potential for recreational resource planning. However, it must be pointed out that there is a need to intensify and improve the measurement procedures in order to reduce aggregation and measurement errors. Then, a viable resource evaluation system will be deve10ped and made applicable for planning. BIBLIOGRAPHY BIBLIOGRAPHY Agricultural Resources Commission. Annual Report of 1262. Ithaca, N.Y.: Department of Agriculture and Markets. 1969. Barlowe, Raleigh. Land Resource Economics. Englewood Cliffs, N.J.: Prentice-Hall, Inc. 1958. Beardsley, Wendall. "Bias and Noncomparability in Recreation Evaluation Models." Land Economics, XLVII, No. 2 (May, 1971). . Economic Value of Recreation Benefits Determined by Three Methods. U.S. Department of Agriculture. Forest Service. United States Forest Service Research Note RM-l76. Washington, D.C.: Government Printing Office, 1970. Beazley, Ronald I. "Some Considerations for Optimizing Public Forest Recreational Development and Value." Journal of Forestry, LIX, No. 9 (September, 1961). Belknap, and Furtado, . "The Natural Iand Unit as a Planning Base." Landscape Architecture, LVIII, No. 2 (February, 1968). Brown, 0.8. Outline of thQLCanadian Land Capability Classi- fication for Outdoor Recreation. Ontario. Ontario Department of Lands and Forests. Toronto, Canada: Canada Land Inventory, ARDA, March, 1966. Buffalo EveninggNews Almanac and 1972 Fact Book. Buffalo, N.Y. Buffalo Evening News, 1972. Burke, Hubert D. "Wilderness Engenders New Management Tradi- tions." The Wilderness Society. (Summer, 1969). Chappelle, Daniel E. A Computer Program for Evaluating For- _§stry Opportunities Under Three Investment Critengg. U.S. Department of Agriculture. Forest Service. Forest Service Research Paper PNw-78. Portland, Oregon: Pacific Northwest Forest and Range Experiment Station, 1969. Child David; Oglesby, Ray T.; and Raymond, Lyle 8., Jr. Land Use Data for the F1 er Lakes Re ion of New York ta. Report of the Water Resources and Marine Sciences enter, No. 33, Ithaca, N.Y., March, 1971. § O 163 164 Chubb, Michael. Outdoor Recreation Planning in Michigan by A S stems Anal sis A roach, Part III. Technical Reports of the State Resource Planning Program, No. 12, East Lansing, Mich., December, 1967. Ciriacy-Wantrup, S. V. Resource Conservation Economics and Policies. Berkley, Calif. University of California Press, 1964. Clawson, Marion and Knetsch, Jack L. Economics of Outdoor Recreation. Baltimore, Md.,: The John Hopkins Press, 1966. , and Stewart, Charles L. Land Use Information. Baltimore, Md. The John Hopkins Press, 1965. Cole, Ernest J. A Review of the New York State Land Use and Natural Resources Inventory. Center for Aerial Photo- graphic Studies, Ithaca, N. Y. , March, 1970. Commission on the Preservation of Agricultural Land. Report to Nelson A. Rockefeller. Preserving Agricultural Land in New York State. Albany, N.Y.: Commission on the Preservation of Agricultural Land, 1968. Division of Research, Graduate School of Business. Summary Report. Indiana Information Retrieval System. Bloom- ington, Ind.: Graduate School of Business, Indiana University, 1970. Dowell, Thomas P.L., Jr. NARIS: A Summary Report of the Natural Resource Invgntory Sys_te_m_. Champaign-Urbana, Ill., July, 1970. Driver, B.L., ed. Elements of Outdoor Recreational Planni , Ann Arbor, Mich.: University Microfilms, 1970. Ellis, John B. Outdoor Recreation Planning in Michigan by a Systems Analysis Approach, Part I, II. Technical Reports of the State Resource Planning Program, No. l and 7, East Lansing, Mich., May, 196 Ferguson, Ronald H. and Mayer, Carl E. Timber Resources of New York State. U.S. Department of AgricuIture. Forest Service. Resource Bulletin NE—ZO. Northeast Forest Experiment Station, 1970. Fisher, Howard T. SYMAP Mapping Technigue. A Report from the Laboratory for Computer Graphics at the Graduate School of Design, Harvard University. Cambridge, Mass.; Harvard University, 1967. Genesee/Finger Lakes Regional Planning Board. Economic Anal- ysis: Regional Summary and Orleans County Profile, Technical Report No. 2. Rochester, N. Y. Genesee/Finger Lakes Regional Planning Board, October, 1969. 165 Genesee/Finger Lakes Regional Planning Board. Recreational Attractiveness Components: Appendix E. Rochester, N. Y. Genesee/Finger Lakes Regional Planning Board, 1970. . A Technical Study Series Report No. 2. Drainage Study Regional Inventory and Analysis. Rochester, N. Y.: Gegesee7Finger Lakes Regional Planning Board, October, 19 9 . Report prepared for the Orleans County Planning Board. Orleans County Land Use: An Inventory and Analysis. Rochester, N.Y.: Genesee7Finger Lakes Regional Planning Board, 1970. . Special Studies Series Report No. 2. Parks, Recreation and Open Space in Orleans Count‘: Inventory and Analysis. Rochester, N. Y. Genesee Finger Lakes Regional Planning Board, 1971. . A Technical Study Series Report No. l. Physio- graphic Features: Regional Inventory and Anal sis, Roch- ester, N.Y.: Genesee/Finger Lakes Regional Planning Board, October, 1969. Hendee, John C. and Mills, Archie. "Enchantment Wilderness: Management to Preserve Wilderness Values." The Wilderness Society, (Spring, 1968). Hermansen,Tormod. "Information Systems for Regional Develop- ment Control. " Regional Science Association XXII, 1969. Hills, G.A. The Ecological Basis for Land40Se Planning. On- tario. Ontario Department of Lands and Forests. Research Report No. 46. Toronto, Canada: Department of Lands and Forests, December, 1961. Indiana Information Retrieval System. Division of Research Graduate School of Business. Bloomington, Ind.: Univer- sity of Indiana, Graduate School of Business. 1970. James, George A. "Inventorying Recreation Use." Recreation Symposium Proceedings. State university of New York College of Forestry. Syracuse, N.Y., October, 1971. Kalter, Robert J. and Gosse, Lois E. Outdoor Recreation in New York State: Projections of Demand Economic Value afid Pricing Effects for the Period 1270-1985. Special Corne 1 Series, No. 5. Ithaca, N.Y.: New York State College of Agriculture, 1970. Leopold, Luna B. "Landsca Esthetics." Natural History. (October, 1969), 37- 166 Litton, R.B. and Twiss, R.H. "The Forest Landscape: Some Elements of Visual Analysis," Proceedin s Societ of American Foresters. Seattle, Washington, 1966. Mo Harg, Ian L. Design With Nature. Garden City, N.Y.: The Natural History Press, 1969. Magill, A.W. and Twiss, R.H. A Guide forflgggnamg Esthetic and Biologic Changes with Photographs. U.S. Department of Agriculture. Forest Service. Research Note PSW-77. Pacific Southwest Forest and Range Experiment Station, 1965. Manning, G.H. Linear Programming, Resggrce Allocation and _ Non-Market Benefits. Ministry of the Environment, Report No. 1298. Forest Economics Research Institute: Ottawa, Canada, 1971. Manthy, Robert S. and Tucker, Thomas L. Supply Costs for Pub- lic Forest Land Recreation. Michigan State Agricultumal Experiment Station, Report No. 158. East Lansing, Mich., March 1972. East Lansing, Mich., Michigan State University, 1972. Miller, G.E.; Turk, L.M.; Foth, H.D.. Fundamentals of Soil Science. New York, N.Y.: John Wiley and Sons, Inc., 1964. Montgomery, P.H. and Edminister, F.C. "Use of Soil Surveys in Planning for Recreation.n Soil Surveys and Land Use Planning. Edited by L.J. Artelli, A.A. Klingebiel, J.U. Baird, and M.R. Heddleson. Madison, Wisc.: Soil Science Society of America and American Society of Agronomy, 1966. N.Y. Department of Conservation. _New York Statewide Compre- hensive Outdoor Recreation Plan: Municipgl Respgnsibility. Report No. 2. Albany, N.Y.: Mastercraft Lithognaphers, Inc., October, 1966. N.Y. Department of Conservation. New York Statewide Compre- hensive Outdoor Recreationg;an: State Regponsibility. Report No. 1. Albany, N.Y.: Mastercraft Lithographers, Inc., May, 1966. N.Y. Department of Conservation. New York Statewide Compre- hensive Outdoor Recreation Plan:__ghe Role of Private Egterprise. Report No. 3. Albany, N.Y.: Mastercraft Lithographers, Inc., October, 1966. N.Y. Department of Enrivonmental Conservation. How to Create An Agricultural District: A Guide fg§_InterestedLand: owners. Albany, N.Y.: Department of Environmental Conservation, 1972. N.Y. State Legislature. Assembly. An Act to Amend the Agriculture and Markets Law in Relationto Providing_for Agricultural Districts. Article 25-AA, 1971-72 Regular Sessions, March 2, 1971. 167 N.Y. State Office of Planning Coordination. New York §tate Development Plan - I. Albany, N.Y.: Office of Planning Coordination, January, 1971. N.Y. Office of Planning Services. Newl York State Land Use and Natural Resource Inventory: What It Is and How It Is Used. Albany, N. Y. Office of Planning Services, September, 1971. Orleans County Area Redevelopment Committee. Orleans CountY, New York: Overall Economic Deve10pment Program. Albion, N.Y.: September, 1969. Orleans Recreation Committee. Appraisal of the Committee. Pptential OutdoorJRecreational Development in Orleans County. Orleans County, N.Y.: Cooperative Extension Association of Orleans County, 1971. Rettie, Dwight F. "Plans Don't Work; People Do." Elements of Outdoor Recreation Planning. Edited by B.L. Driver, Ann Arbor, Mich.: University Microfilms, 1970. Rickard, Wesley M., et, al., Economic Evalugpion and Choice. U.S. Department of Agriculture. Forest Service. Forest Service Research Paper PNW-49. Portland, Ore.: Pacific Northwest Forest and Range Experiment Station, 1967. Rochester Bureau of Municipal Research, Inc. Regional Economic and Demographic Analysis: Orleans County Profile. Rochester, N. Y. Genesee7Finger Lakes Regional Planning Board, October, .1969. Shafer, Edward L. and Mietz, James. Itigeems Possible to Qpantify Scenic Beauty in Photographs. U.S. Department of Agriculture. Forest Service. Forest Service Research Paper NE— 162. Northeast Forest Experiment Station, 1970. Slotnick, Daniel. Natural Resources Information System. Re- port of ILLIAC IV Project. Champaign-Urbana, Il ., 1970. Stillman, Calvin W. ”The Price of Open Space - The Need for Research. " Black Rock Forest Papers, No. 28 (1966). Stigler, G.J. "The Economics of Information." Economics q; Information and Knowledge. Penguin Modern Economic Readi 8. Edited by D.M. Lamberton. Penguin Books, pp. 1- 2 Stinton, David and Steinitz, Carl. GRID Computer Progam. Cambridge, Mass., 1970. Cambridge, Mass.: Laboratory for Computer Graphics, Harvard University, 1970. 168 Stout, Neil J. Atlas ongorestrygn New York, U.S. Department of Agriculture. Forest Service. State University College of Forestry Bulletin No. #1. Syracuse, N.Y.: State University of New York, 1959. Swanson, Roger A. Land Use and Natural Resource Inventory of New York State. N.Y.: State Office of Planning Coordina- tion. Albany, N.Y.: Office of Planning Coordination, June, 1969. "The Corporate Move to Leisure Towns." Fortune. April, 1971, pp. 73‘79 o Twiss, R.H. "Conflicts in Forest Landscape Management." Journal of Forestry. Vol LXVII, No. 1 (January, 1969). . Recreationists as Decision-flakers. A Report of Proceedings of 57th Western Forestry Conference, Portland, Ore., December, 1966. Portland, Ore.: 57th Western Forestry Conference, 1966. . Research ponorest Environmental Design. Report from Proceedings of the Society of American Foresters, Seattle, Wash., 1966. Seattle, Wash.: Meetings of Society of American Foresters, 1966. . and Litton, R.B. "Resource Use in the Regional Landscape." Natural Resources Journal, Vol. VI, No. 1 (January, 1966). U.S. Congress. House Committee on Merchant Marine and Fisheries. Environmental Data Bank. Hearings before the Subcommittee of Fisheries and Wildlife Conservation, House of Representatives, on H.R. 17436, H.R. 17779, H.R. 18141, 9l§p_Cong., Zpd Session, 1970. U.S. Department of Agriculture. Soil Conservation Service, Guide bMaking Appraisals of Potentials f9; Outdoor Recreation Developments. Washington, D.C.: Government Printing Office, July, 1966. U.S. Department of Commerce. Bureau of Census. Census Use Study: Computer Mapping. Report No. 2. Washington, D.C.: Government Printing Office, August, 1969. y _ . County agd City Data Book 1967. washington, D.C.: Government Printing Office, 1967. U.S. Department of Housing and Urban Development. Local - Planning Guide Series: The O n S ce v . ‘Albany, N.Y.: ‘Office 0 Planning Services, 1972. 169 U.S. Outdoor Recreation Resources Review Commission. Outdoor Recreation for America. Washington, D.C.: U.S. Government Printing Office. January, 1962. Wager, J. Alan. "The Carrying Capacity of Wild Lands for Recreation." Forest Science, Monograph 7 (1969). White, Donald J. An Appraisal of Potential Outdoor Recreation- §1_Developments in Jefferson County, New York. U.S. Department of Agriculture. Soil Conservation Service and Cooperative Extension Service. Washington, D.C.: Government Printing Office, February, 1966. ~ Wiebe, Richard A. Legal Memorandum, U.S. Department of Housing and Urban Development. No. 1-7. Albany, N.Y.: Office of Planning Services, June, 1969. Wilson, Stephen 0., at. _l. Pgtential Recpggtion and Opgn §pace Areas in New York State, N.Y. State Office of Parks and Recreation. Technical Paper No. 6. Albany, N.Y.: Office of Parks and Recreation, July, 1970. Wittich, Robert I. Land Use: A Computer Program for the Simulation of Agricultural Land Use. A Technical Report 71-13 prepared for the Computer Institute for Social Science Research, East Lansing, Mich., December, 1971. East Lansing, Mich.: Michigan State University, 1971. Zeckhauser, Richard. Ungertainty and the Need for Qollective Action. U.S. Congress. Joint Economic Committee. The Analysis of Public Expenditures: The PPBS System. Washington, D.C.: Government Printing Office, 1969. Zimmerman, Erich W. Introduction to World Resources. New York, N.Y.: Harper and Row, 19 . APPENDIX APPENDIX Table l : Mean Per Acre Assessed Land Value, Orleans County, N.Y. 170 Table 1 (cont'd.) mi 1.9mm 2.1mm 5t] 1 ' n ”V ad r\. N L H: Nrm. WJ‘N' I‘N an, an. bk; Ifu :n J“. "\. JR WU". J‘Jlx '_n U" “who i u‘ 0‘ ‘1 o D r- \_,'. N U‘ 0 ‘ ‘ ovI.oo-cnncohuuu,u-Iot-Ioo-uooonoeuoo-»--~.-.ov|vono-~IQ§-uoctu o-o-o-nooool 60" ' orc~uooooaonovcocon-...-on......-n‘oooovooaovuone...v'III-oc‘vov.vveotcoooo .-...-...gnauuoouuoon-no-...-....o-asno.c.~..,..-ooo-q.o..-¢....-..o-oaonon- : . 1‘ -:-uacctu¢ocvooucuununouuocaonou.u-pooI-nu . ouga.-..-u-cou1.. I..'.I.....i H05 u-A...cue-cocooucuono...-.o.oo.a.o.nno-v9... ...oo.- ..u.sn.ioao1-oouoc.-~n ‘ o- IQuill-DIG...IIUIIIUCHOOIOOCIQOIIOII.I'OQQOOI'O~CIO’OOQOOOIIIIOULIOIDOOOO i...aid-0‘0...IOOIOIIIOIOIIIQIIOIU.‘vbolraboduOCDDOI-Iiiacloc obooluo-oaooo. 80.! I'D..."..I'nl.U'C'UDIOOOII‘I.OII‘° rno'V-OJI'IclU-‘IIOOQDODUOIII....III ' K ‘ —-¢o...-ao-oc-uvooc-aoaccuse-.......oaooocuaVAot-atone-tovao¢otqboocllou 7'0 JIIOOO‘IIOCI ......l...'..,".l.' - IOoOII .AI‘I\‘I.'D. DI.IILII."'.... ‘ ‘ newscoo-one....occuuoe-II...--»uonu..ocuco.~ on~OIOO-.,-.It euro—00...... 795 .__H_._.,_.._—¢H._.~—”Huh—Hu—HH—~—~u——-—-Hp—.—-...—-—4-—o-.._—--—._—-H—_-—_.—D——t———_—_——H~ ll.l...‘.'.l..........C....I.O.UII‘I.'.....I...‘....O.ll"I..O......."..'.I 1 “ tilt-IAIQQ-tanolaollaaIll-DIODOOIIOIIIII-00's..uponillloooO-OIII...tor-OI... 793 l IIIIOOIOOOOIOcuoouocblliilOIllihttillClo-voauvccllII!CDOOOo-Oonulvonlllulull T I‘IIOIII Incuo-co.cocon-.noao-aloa-Ibo-ooo-ucon-oun-coco-oc-nuooooo-o r > /‘ ..I....I .I'IOIUCI......I'ICIDUCICOUOUIIQII.IDUIUCOD0.......0'I..‘... 702 I Ana-o... Inge-ocannon-ouonooou-nvca-aon:counts-ow...hove-ouuneooooouu I...l.'.l...ll..DUI............IOIC’I‘UIIIUICIDIII'.& ..JDOIIOUIIOOOIOUCD..I . "L Itch-cocoon...no-oo—unlounnuoocuouoIcons-accouuaauo-Iounces-.nuuuo-no-aooa-n ’91 tQOIIIDI ......§‘."."00..§'.".I"‘IJa...‘.'IQ-’lJAI-“".¢n"l..’l.'...'. .....-................................~... ................................... I a norI-Ioloo-ooncoooelalnoon-I-otcacvnc-I'o-’0vvu.>Io-oo.c-ospooailtioooboloao ‘40 I II..'..'...‘C§‘..I'.C.......O."‘el-IO OWOyli‘ .-.«l-A .ICOIQ.|I.‘OICQIOIIO.. I .. .... ...................... ... .. ....-.. . .... .... .........,..... I ’11‘ ....-..-.... ...... ....... .. .,, . . . -»...~-...... ........ I! I ........ O-Alloolurvfltaoil'savol .».a...y . .... pig-kayo ....ooo--c I O.'0'.9D...‘.D0.0.I......OII'.AIDI DOUOIOOIGOQ O\"O 4 0 e.“ ..‘I....'I...O 1 l ‘ ..aono-cooo-oooo-nnoyoonoon-tact... .ne.oo-.c-~nooouoonoouoannnon-o.oo-ouuo&o {’15 I .ruona-uoouoooaor-oouuaaco-o..ao-..»-:o 0” ....nuvoco-.¢~ ooo-onoooc-c...y4 l l .....---.¢uo-. n-IOOOOIp/ar.u04u ---<-.-.:~'-o.~u --~-~u-vv-osoo-olunononvn l I“? I >7.-1;!-ouo-.|I:‘I'Jo~un:n.‘cc - . .. ...-. .. . ... - .. v.40-ao'o ' .._.....................-....... .. . . ... . ........ .....,.. I . .o-so:-..oua..o-vonoo---qy........... ... « .1 .. ,,.,.,.., ... . ...c ...... A I ....p-o-o....--o-nno. oomuu......a.-.,.... . .42.... u... sou-o-oucocoun. IUD I ..uuoy.-..4cn.ooouaulquo-a-o.‘.....r.... .. A .4 -. ..r..-v~.¢.n-ouu-I- 1 ........... ........................ . .. ,- .,...... ,.........,... 1 ’M') I chUoQIuI-al’rcvcaulll.Diego-bu!‘ .. . 1.. v . 1 ca. .v........-.. i..- «Int-OIII‘UOOIOOOOCO'I-usCIIOOII. Al~¢§ ‘II-l‘ . h I ‘ IO- ’I---IC".07... I I § fl'COI'IFOQIIOJ'IIO‘CDOICII‘IO' -' ...}. I y la \ li'!‘ O'UOUUII A "3 ...»v-gu...o..-a«...-...... a... ..c. ... .....- . ,-. . nouns-.00. "’ l . of-oyol-IOIOtebl!.l0l0~ul.¢ulo- a»..-vu - 'vtlo ... ~tfi‘v-ooq ........~ L It vu- ...oo.v.¢.-.you0..blunon-nuclo. H-u-a.‘- 1. .... .... ......n ..oc... I ...l. ,‘ 1 .- ..........o~..Ix.: ro-o- .... -oc--no oo-ooct00( ‘ rev-«r..oconooo-.-.n-.ooaoo-n40-~.Qro.oso ....»uovv-t...o.-~¢....--..noo.ooooco. I .announoncuuoan-countess-o...nun-u¢->.o-.o;ao.--.I-..o-Io.onoa-u ouca-aanvcouioo I I ‘. 7w‘ [ 'IvvOIO-cbodlilcciloolqlniihlfi'fillI-b'oI-IO-Iufioi ~v-e---. ...acpptugr;n«.-O|:oo ‘L I Ia'lp'IOIICIIIQOQODOIOI.ODI'QOCOOI-IQIQIDOp..uull§n»opn~n6.’--'o.h0..oonb..atobtl I ‘ I ...................uou... ....-.....-.,... I.... .- |l npo'loov'--dloloi\l I 31‘ I I . oo........ a.........u.a ...... ...-... ,..... . .I. .. ... o-....;....... . ...........,.. ., ...... . , . . ......... I l.- (in I I.-.....-..A...u uv-~-«-. ...;«. «.- .... ...uavcboOO'I-ooooou otunilyoooiuudio .Ov"- . u.----.ucII qrya4o. -u~-q-..-¢80«uooullao I ........... ..... . .. ....... ...... l I I _ I ... .,, ...... ..,.. c.-.. I ~ .. I.. ’ .. . - o .u u 1...... “ L .. ...-Ian... ...... .....ogy- .. . -. ~ I.,co:o.c-oa., I I ..............,...................... ...... ...”...s... .... ............... I I ‘II 71% I l --oI.Io--.-.oo.o.c-..o-Io-n =.o-.... -... -. .... t.iy.>1v»a>~lou'.!ouronoal .. L ......u...-aout.-..o-a-.......I; ... ...... . ...,......,- ~sy,. o»-.oa-..:.o¢-.I [ I .............. .cu. -c...... ~- « . r . .- . ¢.. 0).... I ,‘ I I ... . . . ... 4. ‘ e ~- ... ll . - . - ..., a. I ... .4-. co (P .. ... ~. . In . to -~ --'v I b«AOIlo\-OOCa-o v:IIIv.-. . o. u - - .hq-.-‘~ . L . ‘ I_, I ‘ I' . . I. 4-«....-....«.u. . .... . . I .. ... ., , II. . ......u.n.o .... ..u.. . .... . . . . .0: an... . .. .. .... ....... .I....... .. . ... .. I .I , ,. ......... .... .... .... .. .. I.........I. I- I .I. ~ao...~vb.oo l.-uvv--'1!..II. . I ~ - p4 . . aQ:‘.rI.\CI I ....x- -.r.--......I.... - . - . .--.... I ‘I. .... .a....... u .... .... a ... . . I.- a I.. :-;- .oou-o~v» V I I ,.......g,.......ap...ar-..~.oa.. ... . . . a... -o .-ua‘ .1 .. 04.0.». 1 .. .... ... . ......» —..1..... .. . n~ .. .... .. .n. ... .. .4 .- —¢- . ..... . . .. I — . . .~ . ..- '.-$ . . , . ... ,, -.-.I I: o c 5 .. . ,- . ... . I I. .... ‘ . . . .. . . . ‘ ... ‘1 A . , I ...... . . . .., -...I. . . . . . ... .. ..— . I y .. .. .. ................. I-‘Il ,. .... «.c»....u.cco-o>0cva I I .1 . .. ..aa-aa»--.a.c . » ... C .- .I.. .ffIII . ‘ I , , ._ . . . . .....Ao. ,,,,, 173 T bl l ( t 'd a e COD. . ‘I. . ‘I . : I ‘ I 4 IIII I III A I' I II ‘H :2 . I .I ~, I -I I ‘ ‘ II" III'I‘I’LIJ I‘.‘ ‘ L‘Vr’Lg. II’I..I I -|II I .I ,1 I I ,I1, “duh ; «(Haj LJ‘ IIII )I IIII II III II 7 I ‘I' .'I I II, . 'II‘I .I’ I'M I , . ‘I ‘ ‘.“ I. I ' ........I‘ I “Ali"! \q ... .. .- .. 'I "‘- E‘I I.I':<:'1€I'3¥-.{“" II - . . .. I . . . . , ' 'l‘ I79"... IsliI‘ .-..... . I III‘I 'IKL’IC‘Cf-'.'13I.s." ~ 5’- 17br Table 2 : Mean Per Acre Assessed Land Value With Improvements, Orleans County, N.Y. I II ”\CIIJ VI.“ 1L“: -'I\)Ij~.‘\:‘I l_“w‘,l,‘ VXI i; anH INpROVtMEhT§ LI‘I'ZAIM Ir; I?.T‘v "in YIIVK Iv IIII / TI I II L fI-I I-II'.I“II~‘ VIII II Is I'L'I ILIHJ as 12.13 ‘rp ‘J‘t‘lnuflv‘ .L JL {4 iz‘L‘rl'lfll 54‘) CC7!7C Table 2 cont'd. NIP 2.5IIEEI BILMI’: Sci 1 - o_---___.....-._H_-_-_-__-___.__~_ .7- ______._--._----..__--..-..-__- ... ---. -..--__-_ .. -------_-_...-----—_----_--------__-----------_..---------... rwv «L I‘\ N I‘M A“ N Dr; ."I\ u ;-N p (\- IJ N\h\ guru J‘N LPN U'N J‘N C. WI M w :I \J O! ‘ III I I I I l I ‘J O l I I I1 I I‘ 807 A ‘l ltIll‘... l.ht.xu.udvvv.'lv§-vnl iI'!!l‘..«l.fi‘f...lhlu'l‘." I III‘ 1.11...-cuo-vuurout-c.on...col;saulltslotIUD-......OGOOOCIIIODI. 606 v I ... u...\-.........¢n-.¢.o.a-.boo-o » o ...-coconoouoooo-oonnuuu I I l4..ya‘4utobitld.UJVDIUCIh....-DUIO.0n.I..y...0.....0...i'1......OCICIUOCDUO (, I 1' O-IaIn.vvuoaouootula)ulu.a.00-ola...-pr¢v00 o~onoono...onlono.oo0Jooncooioccs HOS I .....ca.a--o..o.uI.;o¢o-u.\-..o-voa....no...-.ca.-coo-ova...nootaotooooo-ooooc I I' I ‘ .IIon... I..I..¢- Inexa.s...¢iu5... ...oeu .(‘otucvho-QBOD'I.0IalOlI5‘OOIIQ I‘M“ v I... ~05! I§O< VIhFUaIk «no. I .l h‘.A-ID l..-h€.l~ - b§Il\h p....‘..‘0“"-CI'I~I.-.'U~I'. .I'O’D'IVICCOIIOOIOIIOOCUCI 601 I leg, 0....«'1.D..“.'. Ion-......OICO'IIOUIID'JODIOCIIIIIIAl...’.fi.‘....‘d... I I.I...vc.|ca.cn.o-ocao.o-suoa.oo..a...-n..-.~..uaga.0oaoooobtocoooooocucoo-u I I PI} ottlIDIQIOIJOICDI'D'IOIOIOIIIIII...doODOOOOOIIUOUOll'OODOCOO'IIIOOIOIICOIODO 800 l . coo.'uvvcouuooo'o-oocn-ounocooovooOOCooouvo-nuannc-pooooocoluooooollo-oaoooo I onl-ollsanlcooCilia...OIIDDIDO.Inc‘s...III.a...I..06.....OOOOOIIOOIOOIIOCOIO I 'II 799 I on.ounogqpoolconlnploo-tta.IOIIoa-co.nuint.-..aalsoll15.0-‘UOOIIUOOOIIIOIOOI u . . v A . a 4 s I u o . 9 o ‘ h c » a . v a I a . u o c a o t . u n l c n 0 v 0 o o I —H#—HH-dH__—fl—-—-'—"HH—_——‘—-Hm—H—I“h‘h’-~H"F‘-——-—~H~_fi—~H~_— I .Ioovo-ot-nn.no...-...:cocpa-c.onaoo‘aavnnoosoccotoo-oovoooooaconga-00.0.0.0. l (' '5'.uIOOOIOIQOOI6OI§CODIUQQ.GIIIII-DIG...IIIIJIOD'OIIOI..I..'IIIIIOOOOIOUOOI 79" I ...-I. - ...-c-uunooococ-ooouot..v-o.o.o-~-po.uq.-o0onooono¢ooouuoooooonlouoc I ‘\ ....I‘L'..q.:o«o-ooa...cos-c.0uaI-oa2o»va...-no...oncoouononouoooca-Iooc ' I J III'I'aoovI‘ ":I-ogacavvo-Islin-uovv~I-poo-uo- atlou~oulooiloooovI-oooluuooooao' IQ} I I" 'ov-~(l I‘Ioooocopa-4......oav-vuIo...-'so...o..-ocv-wovo-wcoovuo-o.v¢ouvooo I LII.“°\KE .O‘OCOOOOOi..OOOOCGOOOIIO0.00IOGOIOOOOOIOOOOOIDIOODOOIIOQOQO I I'J, ‘IIICKKIE Inn-II...nontooltlltvvvttlotOlin-.....anliola......ICOOIOIOO 792 I I| IOII‘WEX .actan....-nos...n-ooo-nuogoo-uooooaooanotooocolooosoooooaoo i IIIIIICDODIIOIUIOD’OI‘.‘O'..U....I.QOIO'.II'..III‘I’.‘l...‘."'..".....‘.... l I [I ....OHIOOICUIIIIIIOIICOIIIIIOIIOto...OOOCCIIIOIIOOIOIOOOI.....OIOIOOOOOICOI. 791 I I anvo-oot-ooouco-o-ooo-on......-unnaoo-oovovvcou-ovoocuoooioooooonouululioooo I I ...-9.. clollllc.ortuuca'{IhultvovvovI-ooO-IIICOOldol0l5‘li'OIDOCOOIIOOOIOIIII I I If“ .nI»uvonoa.oooo.nun~a-unQLIIIIIIjg~octnvoovuu-ooocuvoooo.o-'ooouoqItooooooooocoo- 7V0 1 I ........--..r...~...-...l'lI-IILII-......a.......).,......a....-Ina....»v-oo¢ooooo I i -D‘ ’IOIGO‘CIIOO I.)'.-|O.v‘.‘I-J --vp|" xi. e’I-dIOQJDIOIOIOO....I.II'. I I’ll. lvn.-orav- 0 ..-¢.. .9-‘I a... ... VI ~n.v-..-.<4o-oo.oa.--chovcoo l l I.u.;..~-.a.. .....I-‘. ..I..-... III-.... .: .I .. cine-v.9 oaro¢ocooooov I I .. .........;lo.o¢I.¢-.......-.,—-c¢¢. ~~o . «I... .un:.oo-o.«..o¢o.c-uao. I I I I I --»~o...a.‘.--u-on I-o<-- s V'DVII" . .- -.v«~II~n-oo....v.oo..-ooo-oaog.... 78H I A. n.00lgtIOIIQI-I .. - -~-l-~I4 II- I- ... ..II -.Iy~. ‘\ ...... 0.30.01. on I .. . ....... .I I. . .. . . . ._ I. .I.. I....«.....:............ I II I. . ... ...- ... ... .. .. .......... 7"? I . .. .... ... ..II. ....-. II . . ... . ....¢-..,...... I I f .4tl-.«.¢.o¢~cairbr'fllva-lu-clnuyofitpogvitlro4no.‘In».I.-ubouacl.QIIICIOOIIOC 760 I ‘I U. Our-...‘ull\v‘.vFV.O‘I-".)L'IlVIU' 'Vli'. viiloldu-b~-~‘.‘OI‘..I.".I...O I ‘ I '- .......c‘a.c...nvnuounoa.|vo.cq- \Oilo‘lrIncl-ail.O'ctOGOIUQIvooOOOCOIII. ‘ I I )I A ...... .... . . . I. s: . I - . .I -:.- ... .-- 3.-...DIDI‘A 781 | .. . .. I . . . . I . ... .,.......... I . ..I... .I .. ‘....I,. .. . . ...... . .. n . :,--dOQOOUIIQ-ovl I I '-v ..I.. ......o-u..4au-.ouco...'uu. .... on...» II-A'IOOOIOOUCIDODIUCIOICIOADOOOO 75‘! I I I . .. ... ...,-..~..~.- a-.a.o.. '-.. . ..4.o . . uaonncao~v;0 o:o.-apllol.utli : I “'3 Au.. , , (.. .... ......g. ...; '~ .lun ... ‘- I-a.‘o-»I«lo-evan.aouoouoaro9 I " 1 I _ , ... ... I . . . .... .I-v V I u'ck‘.‘\:1...I .. -.:- . r - v we. uVrvvvovoo-dc TH- I . . - ..‘ ,. .. ... ‘Il . A GAS, . .. |,a . . .aao-AI-vtaeocauob I I . _ I I I .. .'\:\ K.. . .. I. . --‘.-~ I. ..n...-..4r.. -..ma..o--.un-on II‘Z I ... . ' .. ..V-.< 5. ...~ 1) I. >. 4‘. - —- (VsIl‘fl-v‘. JII.-.....o-.. «coon. ouooctlooo.oo I ' I _Its" ‘_ . . , ...... I... I . .. , ,I o In.....-~.-. c-.‘c .cootoooc-o \ I, I | II III I...:.I.:-.‘-‘ 'I‘I‘ ... .... . . ..~- ‘fi\4“-' ".q-.--~i -lI»oq-.v.unu.noouoonupop 7dk . " "'I' I ......nus40.lIII‘..a.....-cc.»-v~.- IKLNLK ." ~o- aooo-nvoy~-avo...-DUUCaOIOIIQ I ,,‘,,.,.,,,..I..II'-.,I'§.‘III. :...." I-IIGHSMHUNG’I...III.......... .....oocoucocbo I ‘J'I‘ .‘ V_,.",:..‘.,II l_|lll,..._I,IIIllL’:.‘.“anm:-$..Ig~. - Is -~u.¢o-..u-.gn-¢Ioo 780 ; . ....... ... 11!...I,IIIJ.II gnafia‘flifi . o o v I c o . « I c c a v o n o o 9 c I o 9 . __--.—.H-—< H"...— I I | -, - A ' ‘ z ‘ ‘I' .f i , .4 II II I II -. ~ I ~ “I ' ‘I “ 3 ‘7 I I I f‘ ‘ ‘ I . ‘ ‘I ‘ (I .7 I ,-I.~ IIII- W . I..'I wur IIII-I I’W’Hl‘r “IRIS . Table 2 (cont'd. AAP ZISHEEI I'UAIA SET 1 t-———--—-———-—-—-—---—~ ---—--..-.-_---_--...-_..-—--..--___---------—--_-_---___.._----_- -———-——-———--——-——————----—————--—----—--—-—---—-I .— r-s r\ '\I H m v-«N N N m m CNN comm 0mm nwrx u um- Luv: bulk Ifium own- w 9.»er p— I’\.' “J 0: IV ' II? u‘ootolultlootooaquto-ooo-rQOavovuiOCC~§;oéav006.Io-o«x. do? “H_H___—_.~_ {I a I I “I‘m DOIIOIOOIOIIIIODOUIOIOOI.IJDOCIoIJRIOIOCOO\IIOUOIOOQI0000 0.71;. 300 l C.‘I.......'...-..............O.I‘bl...Ilb....hl.d.u..IOJDIIICIIO I IO..IOOODOOIOCOIIOQIOOOCIa...It...»O.oto‘lohl’30900-OOODCOBOIiOIOOOOuICUIIIJUUO. I F4(Mr‘ ......i'...‘ D. ......‘fl....'.' ...Il.'..I.'.I~O<~ 'I'l! : (0' IOUVOC‘ ooo'..0[jDU-OOC 808 I IOO'IOOIOIUQ0'9.IOOO‘OOOOOIOOOOIOIOOI.IbObualoonttl00440COoloo-OOII-UOOOI... l ....I......I...‘......O...I-...".l....905...‘.......'00"QOOO...O‘......0-. I ~III“ tau-ounocc-Icoco-.uuncuuonco-v0ln-I...-....n-aooI-nvnua-Incnun~IIu-.Ic~'ncooa 5011 l O‘...-IIIDCIOI....IDQOUOACII.-\I.‘DOI..II O~Ol~-J‘Q.O.Ii‘.‘ OQ'nQQOGOCCUIIC. I otllu..¢¢iutulxl.ntnu.uoIIII)(‘cnvl-OIUOOII ov--.-o-o..cno-.o. ......ocoo-no-nv I II I I0 .lldl'lOIOI'CblIOIIUUD IUIWIIa II... to I: ...-.u-Iaoa: I~I§I .. .0: a: .. . 9 ill it. ...... “DJ J I.I.........II......-...‘]OdCJ.O....IU..fit.l¢\hl..lbu~..§'l..ptbluh-‘I.D.....C I coon-.ncnonou-......ua-u'II'I'Iac...-o...u. ...;. a... .I. na-oo..--u ..oo-s-oo-coo 1. '- ‘ u.no..cpo-nuoo...-.....IJUIIU.-..n..u....-Iov con-vu~ooaoooo.v‘ocoooonoooo.ao 802 I n. .... lilo-....llIIOOIDQJIIIAJLIII-‘uokb-Illl no... .. ...‘.--.- no.¢oazn.o...0lniioul ]- COJ‘D'CIIICU.III....I..II.OOUI.......IO.-..oI-‘CUICCI..C‘...IU...I.I....".. ‘- FI‘II O.II.‘.'.III.'Q¢I.I'JC¢.IIIIIOD..'~-"".Vl".."’.’.'.l.l'....0.I"..I'.... HUl I IIOI...‘ICll.C....‘D-‘Q‘....I.Il‘.‘......0.‘I..IOO'DCOICC..'.I...I'.....'.‘. [ 0‘G.J.-II...0....IIOIU'IJGL‘AC.FO.IIOOIIIOOO.'...‘...‘.IIIIIl...l......‘....fi I " ‘ I.............o.........$@l¢u aunts-noo:.u.oo..~000ct-ccoI.vu..ooooQovv.oo‘ao UOU I lanolin-louaaot-opun.outxxmm-ouln.ul-u.ncol.ouovaruvv‘otolc-ooco¢.v0¢lco'vvv I nun-no.0...-a:...-noonaoaoouooon...coouoovlnl~canp.a--Ioloco-cono.oa-ounnous I III‘ O...-OOIOIOOIIOOOOOUOOOODAOIIOOOOOIIIDale...tutu!...-.0010.0I000IDOOOOOOIOOI 799 I nortovannooo-usoc-note...-too-utocu-oo-a-o-ub-ooo.:~-au.ooanouaoo-o'o-aooonc I U...II......'U...I.‘..Q‘I'III..I..b'ul'.'..-DOllI.‘.I'I.I...'.....'..U.........I I (1“ ¢o-oooloun»u-oonao..u......nooooobnul-n.uao-n-oc-s-cwo-.o.gnuoo...-oocouooo-oooo ’98 I ooonvo'oancocoa.DItact-onuttaocoovolno.loco-oooeoauuapoo-oooo-onobtocnovoonocoou I III..-......C....'.'I..........I....I.JIIII....I...’........DO.........II..‘...' I III, III-IIIIOIIIDODOIICIIIII-ICIIOIIOICOOOOIIOOOOOODUIIIIIDOUIIIIvi...QIOCOIOOOOUOI. 797 I nous-uv-ooooaucooutta-n3uaoqooo-uv.‘-o..ooua.osly-4.‘oo.avoa-.uuu-.-.¢o-onuuuo-u I ......II...IOII..0’0‘......-......‘I'V..‘..U..."..I\Ll...-........II..4.'..I.I. I (’I‘ c-oI-.oaq..o.ao-oo-o-u-n-oovq-oooooo- .o----I.u.:--I...o-vuo-o o v¢tovouoooooono 796 I Coo.IOOUIUnfit-IIIQIvOOIIJOQDOIIIIIIc-vD-I y~vu.-o.o.-\vo.-o...-...ona-non-unoou I Iou-Iooouo.a¢«saOno-I3.0000in.Clot-Ila.oo.¢lloooau'¢ocv.hol-n.uour. aooooocooaaa I Ivfif‘ 0'00000lloonoiooIDIOOODCIOIDIII.0III'VOII.ltv‘ltvIIOCOtOIIOIII'IUIOCIOOIOOOOIII. ’95 I DUOOIOCIOIOOIOI.OIOIOOOOOOOOOI...OIIIOIIOOIOIOOOIO0.0Idol-OIOlOttUOOOOOIOOGOIO'. I I4. 793 I ) ‘I...'...'..'.....‘I.’U.I...-.....IODU.""I....‘U.."....'.U'V‘.b...‘.......... I OIIOGIOI.tonoflollIv'olOOllOoolulIall-ICOOOIOOODOOOIIIOOOUODIIQU00.000.000.000... I concoct-onlooooano......-00......ouaocooooonuoooIcoooooonaooooo...-coutlononuol~ I I I‘ II.It.IIIIOOItOUIOOOOOCQIOIloot-IIIOOOCIIDDIOOIIIIOallqollloltl.CIOIDOIIIDIIIOOI. ’92 I I'OIOC‘ICI‘IIIIC....I......O.........I."......U.I..C..COLO‘OOI......Ol.....'... I IODCOIOOIIOOUOOCOIOIICCO I000...OOIOOIOIIOOODIIOQOCOOOOOOOvOOUOOIOIllIOIU .. vol I I'I ruin-Iooaoa-ano-o-o-Iano IOIQIOOI.OOOI4‘hn-no-nnccoa-c-‘dot-naodOoIO-DOOCO I ,I . oacoouonotoqII-no-ucn- OOICI0~UOIOIIIJIOIOOIV .«...I.Io-,. Ioao-Ioooo-n ‘ .....ICIIII’O'I. I......OO'I‘IOVIII.CII.’I...‘.O‘.ol..-I‘.......I V“ 7‘40 I ‘ ODICDIDUIOCJIIII Geno-voucounotIa-OI-POIQ.-:o-IioraoooOCaoothloao. I I Orv-olclco¢coi~l t».>uu.ov-ooo -uo ...: -...II «.r-I-c-n botcorvo ‘ ush-IOICIIOIIII .00— COOIO- 1|‘DI'OO' va‘.‘ P 0. ‘ v llflllitV'IOCl‘Ufid. I ‘fi' -.-.-w......o-oo-ooou.v¢-~ ..oI. ...-....‘xo . .... I .I ... ..,.- o Lrlt. 5‘0t0 III/ . noonIOOOOCVIIQlololuuoafllOob-yloooJIl I'L'I.‘ t.--I---.I.a... '.y¢ .ou IoaooO-CIOO. l I D’OOGOIIIIIDIIOIDOC-IOIUOCOOIOOWOVOOIO-9.’i'l .a-n... I I. .I...II'l.I.ouxno-u...un 1 I' 'I‘ lHj I ‘ oofillvnotallolll.IOOOIOOII-...llllvluuolOOlooo-¢A§II§|-(¢:av.)o--l Un-vltloocovq ' Il‘II I tall00OOOOOIOI.0Clio-00....-llbuiloo-Ilunooau~uaflco-4-Ulouro~uoo IIIo-cou.ooooog : ...-n....-o-aa-a-o-I-ou-ouncur-uv«.--.~- o..2r.: .. . .... .....oo-a-ooqu.-I . I Id? I III ..oa-uvlouo-IIIInicotine-a-Ian-gooo-aq. ....I‘.ao.-..,. a I... -I .II....,...,,. I ioutol-OoqofluhoOIQDC‘JIO'O-t.4-l«¢dn ...... o; . ..... .: .... -c. IO-luu10I.I . .:.o.-auu-cooaooooonou-ooo-u..~~--.:oln.zau-- '>'V-V’i . I-I...a III'QCIItOr- I I ....nnoto--~o.»uouuu-n-.o..-.uau< - uI...¢ "I- ...,4 . .,~... II¢a-oool~oov IUD I .r..-o--auo-ouou‘uo.nIoauo'onnuao....a.<.—.u.- ...I, ~I r»r'l-rivu-OIOOI004...-00yn.v .... ...........,... [6% I Ictgoonoiictluoo...-Ottolcillul~u.¢0-ot-btlz-D¢ .- ou-a..c ca...- A1ICI¢IOIQIUQQ I IIUI'CIUOOUOOCO.III-......IO'O'IAOII'....CICII."."COC’hOlU--"‘D'C.ln00t"....ll I I ‘ O'IIOODOCCOCOOIIVO.QCl1."i“l~llob"l t-‘~- ~.. . i. a-.. -.. . IQ’I..v'oc.ou 753 I I...0.00.00...ICIiovvcfiOIInl‘luuvpvl ov~5¢1o' ......Iu.o¢ I;a.......v.n..-onn I avooouoclooo o.-I¢--.-a--Iou bu¢*ov v-nn. ..QVODODCII I ') I 7". o¢~¢vaourpco -r«v- ... ...O~‘J'-v .., .uooolnoauo: 75x I ...-1.000... .... .......-.u.-I .. I...I.o¢.‘«..... lI-_ I I. .. I« .. ~II- . . ~- »o-yut.L.I--III.... ~ ~ I III >~¢u unoq. - ...-~-za.¢.cIo-OLOLOOOO 761 I":I I .. .. .. . . .. . I I4.- vo-op00onoIL)UIJ'JIIUI L Ol."‘gl' 6.. 1.... rO"01|.I OlncnmoIUI o..”.§o.n 750 I ....I..... pOAI.o;ll.l‘lllt‘.fio‘ccn00000 . o ‘ [H.I“ ..yl. I-I- . Ql“ .-...‘I .... I 2 C I _ I J I - . I. I I I I s 3 4‘ 2 I I I: .3 4 ' 2 ’ I I 3 i ‘ I ‘ 5 3 i 5 5 I I} I‘ 1 ,i' 3 w ‘ I I' “I ‘1 I I . ~. ‘ t. I 6 177 ' ' 'd Table 2 (cont .) [.in I‘) . I, I- I? I , , ‘ ‘II'~‘4.‘. Iv |.II ., .I » I . .- a 12,-r x In It HAL IIIA‘JJMJ IILILLI; (II-LI..." l'.|'I~"'I'\II"‘ "()IIM «I ”IIZ‘I Iuw --I . ';1“II’I‘ I\"II|I "Ikry II-Y4 )Alq WuPVIF I” j LLVLL; HLIwItU L‘IrIIL :JLH H I L5,L: ”HI ‘L/.(C HLJN : 1|}.52 SI, UtV. : 185.59 JHSILUIL flALdt «bung AlrIfilgu IL CA(H [‘uL 4IoI'I'I‘I I.I.II I‘l‘.«.’) f:‘¢".]“ I'-'.‘.A [MIMI ‘ )I .f ‘- ‘x‘w‘ . I’I "‘-u".I‘ Ir~I MIKI— r I ILI QWfiiIUIl [IL I I ,II‘I I In I m "-4) 1:.I‘: I‘. *I’” )‘h’Ql' l‘ISIkIIHIIIl 7. .l III'II/I FBI-III ‘Jn‘IlIIr-H I'. r3”! LI VIL LIN VQI\_IL§. 'VII,:I “..AI 'l' LL‘JI‘L'D 3 I J 5 ~ ......... IbiiInuuw wmgmmflouw ......... [VLIHHHIH oxzmxxxuw SYfiWVL) .... .... rhffl Iqu QSQE sfihx ......... VVUIH(”II WNKGMGWXfi a..ooo..- IILJII'II " '- i‘rEEWK’wVK-‘r '-I:Nur «l th I“ I) t 178 Table 3 : Property Tax Revenue Loss Per Cell, Orleans County, N.Y. MAP 3.5HEET 2.CATA SET 1 ) 7 a L 7 z. ) 0 l‘," )I IJI'o-ooLILIkr“ ‘Cl JUJU....m IOICSCKE 74’ mHImefla IIIFRRKK I I I I I l I I I I I I I I I I I UIHhI....IIHII I I I I I I I I | I I I I I I I I » v 3.79 Table 3 b r-N “4 w o . ’2 2 R 2 o . o «4 ... a... .. ... i o uuuuuuu I ........ . I . .. ... I .. ..... . I I * .. .. i I O. .01 I . . . I ‘-» . . . . l 1 :01 I I I ....... .. i . ... . l O I I ' ..... . I .. .... .. I .NNRX. I e 3353.. | I . .. ..... I I . ... o I o. 0‘ v I to A ...! I } . ....... .. I I 0.. ¢ 1 l I I l I I l w I I l y-l,4____,fl____7__a -,~-,--_4 _ _ __V ‘avv:~Is IA\ 4Fvbhe; L ;k IVA \’IL .KLI‘AI‘Q) L;L'\.I‘I ’I;a 3‘er 5". o L: . . In. a och I 'I ,.. I U1} N O b o o n u a u I o t a - a o o I o o o n n h a I a . u a a 00 Our-0‘" .........II II IllOuu-IOII~ . ........kk (cont'd.) --_---_-_—--——-——- ._------_---——--———_—_-_-____-——---—----———-——_-————-_--—-—-- Dov-00.00... 00.0.0000... ....QIOIQIOO ......DCUUUI ....UODOOOCQ .......... IOIOIO.‘.. ooIoOouo-o cu... .0300. I .....UUOU- O .....OOUUI .IUOOIOOQOO ..00000000 IIOUUO...I 0.0000...- 0.00000... OOOCIIOII. .IODDOOAIO Clot-lullll lot...q.on o «I on. II-%E“80 no. IifitQficu I :IXQGG.... KKQKQtLUIQ . . ...smxaxwusdanu. .........suasa«esvisu. .........u0nflflt¢888flfl. ICUQEUUUGS. 00 at to b. a“ ‘_If'3@aixamu .........(I J v , . u »1 ~ 7 h 9 I.....JIQIUFUK§GSCCCOM. 7 _f ‘FILTIICISKSQDBQ. ..k.... 'IVI”LK8ENQCCHU. O m ~m~ .0000... 00...... ..ODUO.. ..UOOO.. ..JDOO.. I .UOOOI I ..UUUU.. 6 ..)LJ[~]L-)I . ....Qll. 0.006... a a 7 I K)U\N N- w ru V‘N D rd 0 V‘m M .00... U‘U‘N O‘U‘N ‘JU\N .......‘. .....0000 .....0000 .....0000 .0000.... 00000.... .0000'... ......00. ....O .....0... ......IOO ......CI. 000...... ......... .0000........IQ.. .(JOOO..I..D..I..I .0000. ......O.. .0 a on no. .UJLOUOUO .CCCOOOOO .........0UOOUOU0 OI...COOO....I... IIIOIOOOOIOOOI... .....CCOU........ IOOOIOIUOOOOOICOQ l...’........l... b............l... a... to ID. .....l... ......O.. .....I... ......O.. I...‘.... ... O .0000 on. i .0000 .0. . IOOO(] OIOIOOOO......II. C........Il..l.l. do-OIC’COIOOIDOOO 0.9.I0...I...I... I'D-......OOIC... f u.N W\flhl v ~quIN 807 806 805 806 803 802 801 800 799 798 797 796 793 792 791 790 789 788 786 785 789 783 782 781 780 .__-----__no-..-----——---___—-—------_-----—-------——------------ .—H"—HHHHHHH__—H—m__HHHHMH—“...—n—HHHHu—...-—u.—¢._—-—~————_~—_.—..——-——~——_~———~—-——~—p—-———————-~—————~—~_—_—~—-O MAP BvSHEET 1.CATA SET adflHHFp“HH-'-O IooIIIvi .uaobuva; 00....vv c.0090..- oI-ooab I notauuouc quoioloo: 00......4 ~9~IV|VOO¢ . 1 . I . , . , . o : I. . I o . » . . . . . . . . . u . o a . 0 .... ....II 0.1» . ... . o. .... ... . .4! ale-E. IaN?=.. . spas.... AJCEL, 3. ntStI’ . t: final.‘ #mhdfixuo Aufiflwhcfi (lifiid-nfit. xgcuuaii. $EK£ECR5 «usamnms, I ..uunhufl J. ...qu IUIUHU. HUUUUC HHHUUH 50.0- ~n-III o o L) 17" (IL ..UUUU. .Luhn ...... . .... IODIID - 0 u . . - . . u r . . . O . . , I — k A v . . . . , .,___.__. ..-_-_--.._...-_ .....__..._...-..—.-t d K t 5 5 S 1 '-I .L' .iI‘InII} . UULJU. -... HUI“)..- . too-I‘IIIIL ......oLIIUL ..OIOC (11.11} u»:oI-..oaoo I ...... ..ro A ~.vou s 00 o a--."I vs. .o a: .... ._ . ‘ . .- I.....O..... ‘O’... 0 II ‘U‘I'.'.-.-- . -.: ...».- ‘0'OIDD. 9| I! I... 0..v I ..nn- 0) ....II¢.III; ......UO'... ~OIDOClv-I-00 IIOIIIIOOth 0300|0)0.000 0000.0l...~l 0.00.0000... ‘I.....I.0.0 0l000.0|0000 ooolInIo..o‘ ......U. ... ..4.:~o4..na IquIIooooxa 0.4!... 00“.. ......---.~. fiv-tl‘ ...-0 sot-OI... .. OOOOOCIOO~60 IoooIo-oouou 0000t8000uol Ocular-000- .......I..'. 000000.00... .000lf‘lli1‘IOCOU ....FCVF. .. OOD‘Ile‘ILIJUOI ....I- -.0\ 6000000000.. ...Ia---I ~0 , . ‘.,:I.I «. .-‘1.l .-.o..¢L'.\I, . ~tootsuloo coo... .. .N..".“.... III-.IIvOOODI ‘00000000 I. I 4". .9 a . .... a .. n ...-.1 v.0.7. o o. vvw.§.p I .. ...-n. .. .- .u.‘.o ~- ....... n .- 1 . Io¢ . «I -.~ .., . on .....y..- .a 9 .. . . .. o. . 7.... . .. ..., ~ . ..~I.r.'o .. .I .. . z . . . .. .. , .- ..I. ....I ... II. 0. .. . .. .. ...n , - ,‘h s -b . ... . ,- .. w W Iv 807 80c 50‘ 80a 80! HUM 799 798 790 793 792 [‘11 (GO .——-————-___H-—~_——-——I—--_~_—~_——I—Hm..—H_._..—_.I—--I—¢—I—.__~._.__...—...I—n—u—o—n—I—I—_—~_—_——~.—I—_-——~—_——_————__—__—__—__— l l D l I WAP d—w———-———v—-w—I “VSHEET IIUATA 5E7 1 r’.‘/ “U“ ‘y‘7 ‘7“ I v I . . I . m I I I , I I I I . . I . I . I l I . I I 4 ...x o.» I.I ..I .I. .. .I I I I. .onI I.. ... i L , L 1‘ ‘ .. . b .. .. . . a . . .. . #1 O .. . . I . . .. . I . . . . . .. . .. . .. . .. . .. . .. . I. I .. . .. I .. .. .. . .. I .. . .. A. . ‘0 I .. . .. . .. . OI. V .. . .. . .I .. . . . , .. . ,. . I A I . I I .. I a I I . I I I . I I s I I I I I I I I I I O . I I I . u I I . . I I I . < I . I v v '- I I I I I I I 4 I I 4 I I I I I I I I I . I I I I - v. I - I v I I ‘ . I . I I I - I I I I I I I r O I I I I I l I I I I I I I t I I I I I I I I I I I c I 0 I I I I 1 . . I I v . I ) 7 I . ‘ I . . v , I I l n I I . I o \ £ I... ..I 7..¢.. .02. I. UJI-»l: "..VI. 0 o-I... ....I.‘. .....I. IL‘QO -0- 1- u ‘1 .r’.‘ I. ..vva' ‘IIIKO .IK-III- ‘ .-.». . .. . r. . I.. . ufl'l.‘ _ .A‘Al' .IIII ..‘xJLhHJI...I .....7.'llli"..... .IIII...tHl-!l|aI ....... .Hla'l‘l‘ ‘. . I. ......... ..... . . ~ '('-'l-I.-.II«. I4IIIIII.'i“amII~ . ...‘l.'.ufimm0'.fid . I. ...‘MUOIH.. .. .-.O-I'."....‘ II Q‘IIALOCOOOOQOO'. .0.I~.V.I'..-.' 0 ..bOIICOGICDOC6i. I‘D! IIIQCD‘fiI’O §.§.I.I OOIOO'UI ...; ... -.. . . III. «I. III-45":- ....V II' ,l‘\» It“! ..la"‘..)l‘ o .-I . -..-..».. .... .... I,.. ..I. .. .I..I..., OSI‘IJJ‘IOSDOOKO. IOI'IIIIIII. ..I A III..~....III. I....II.I...I. -. OOAVAIVC ....I". OOUCOIOIOtOOI'IIV CI'QIJ".'.'.VU‘¢ ...IdUIOIIUIICIII IIIG.IUO!OO'I.V$‘ D'I.‘.O.$‘II.IIID III!I~-V}‘r‘~ok I 1“. I‘Ifiv . ‘b I.) . V o. ..I. .7 , . ,I . . II - a. . . . I. n ... I . I e- . 7. . . I I . ... . .. . » . . v s- . .. -‘ _ ,_.,. ... x...v , .7 . I. , .. ,. . . -. ».. II... I . . . _ ‘ . .,.4 .. . .... .... .- I .. I ...... . . .. . . , I 7‘ L w I Table 4 "NxU'J .I‘. I. )UUUI . ,7... ‘ mm". ......H.“ cont'd. I I .1' - _' 7,’ I 2 . 1 a , 7, . ‘ 7 . .. ....le «3L '7 ,-~.. I “Humw .11th . . . . . .”.U(H'W u ' J "V 7 . I .t. . . I.. III-.. II?- I ..h-I‘OI\‘ 4. -.-.I (r «.I I .. z. . .. .1 Ob~~u » . , I.II.I.. .. . . , . I I. ... . . . ...Is.-. I-IIIIIIII I, :- ,I..I~I. . . I . ...-..-.A- I.~ I: I ~I... .. ....I I7: IIII..‘7 I. . . ... ... - . .~» -¢. . . . - ... .III.». .. ou-O-l‘v‘ ‘I'..§"l .- nwa I.:,.I.a.. I. 30.0... IlIIvlliilfnol Agog§tlIQ l.’ DhtOIIII ..III.. I-IIIII..... C'IIIOI‘O ..I ..O‘.OII ...nI.IIs .IIIIII [III .. I -I \ I.Ivo . -01....ADO b IIIII.» I'IVOr'G- .. .—III..-,... II\-~O' .,I«g.III-- I- I- .. Iv I IIIu... -. kill...CI I . I9. III-v ...IIII.III ..II"...- I III-IIOOI-vI-ISIIIIIIII lvhllflflbvfi IIIIII I.~ IIIIIII-I IIs-I .“"‘\ It.¢.II.I. .IIIst-IIV- 0"..I'.§¢ UQIIIDOOOI. I..IIIII:( IIII.III' ...II. . .- I . . A7 I .. . ,. .....A .v , b . . . . . I . I , - - I A - . I.. .. . . L . 7 , .. I . I» 7 . . .A... . ., . .. II.... .. I . -.-. .,.. ..t . I . a a. 7 '7‘. - I.«c; l . . u . ‘ v. I . I .I. . AIII. ..p. . . . . V» II I ~__.,._,-_,_I—.~_.._...-....--~_.._.__II~--_I_I..._-II-_-II-. bOo UOHU. . « I ...uuflu. 7. . UUUU. . . . 805 dU-I :90 J 900 79’} 797 I IIIII-III , .... .I . I50 vI-II-.I~v. III , IIII ~ _, coco.a.zI (D?) 'IIUCVIIOD. .I ..,. 01"d (It. .8334...” .LCD I l I I I I l I l I l l I I l I I I I l l I l l I l I I l I l I I l l I I l I I l I I I l I l I I I l l ................. I43 I l I I I I l l l l I I I I l I l l I l I I I I 1 I l I I I I I I l I I I I I I l I l l l l l l 1 l I ---.._., Table 4 l(cont'd.) PREPARED FOR FRANCIS H. DOMDV BY IHE GENESEE/FINGEH LAKES REGIONAL PLANNING EOARD REG INFORNAIION SVSIEM ROCHESTER. OATA MAPPED IN 3 LEVELS BETHEEN EXIREHE VALUES UF 4541.39 AND 36787h.88 MEAN = 51069-11 ST. DEV. I 33211.38 ABSOLUTE VALUE RANUE APPLYIND TO EACH LEVEL MINIMUM “541.39 125652.50 2467b3.63 MAXIMUM 125552.50 246763.b3 367E74.86 PERCENTAGE OF YUIAL ABSOLUTE VALUE PANGE APPLYINb IO EACH LEVEL 33.33 33.33 33.33 HF CAIA FPINT VALUES IN EACF LEVEL H FREUUENCV DISTRIHUIILN ES IGH VALUES LEVELS 1 2 A ......... COOOCDOUD I . . . CDCCCCCOO I SYMBOLS . . 00 0000 o . 000000000 .....oooo (OOOCUDOD I'll «I 970 36 II 0 FREQUENCY 186 Table 5 : Development Cost — Orleans County, N.Y. " 5" "‘1 4T 'L'w’w f “UNA U-HLM NEH Hwn 187 Table 5 (cent'd.) NAP SISHEET ZuDATA SET I Z 2 Z Z Z 2 2 Z 2 2 Z 2 2 Z Z t 2 Z 3 4 II 4 h 4 I. a -. I» I. 5 5 5 5 5 5 5 5 9 C l 2 3 4 5 6 7 8 9 O 1 2 3 4 5 6 1 807 807 ....COUOflflflfl.... "’"“"""""“"' ‘""""' """'”“ ...UOUUOODO 805 can .OUOCOCOUQOLU....OODCOOODEGUDDODU. UU 0000 806 .ODDCDGUOODDO JODUODUUOOUGOUOO. . 0 00 . 0000....0000. ...IhuhUUDCdOOD Hfifi .... .4000....U nUUU....UbGODO 805 r r n nmm nouaooauo 50% 804 M) J 303 b)£ 0....UUOUUUUDL:OOOOOOD 902 CCUFCCGDJCODUDO 001 801 H0” 500 Is” 199 . . ..IDUUDDUU 79d . . ..CCCUDOO . 798 w? 797 70; 79b (. UI :lJlJUL mu 1”. . . [45 .CUUUUICCCCDUULUULLIL 795 .dU GOUUICUUUCIDUUUUOO. 7')‘. 79’. 795 793 79) 792 .LU L:I DHIJIJODIIUCIJUUO. - o - . o IVI I F . .Ul CCCFIIDCOULL CHI”... 79] .UI'ODHI) IIIUUJUIIOUII. N) 1'90 I: .101 {.0 103 '( HI 6000..“.UUUIJUOUUL-Orlz J . .I} . .I-I LIL-000C101 . . 789 (QIP .CDDU LDCUULL 7An 786 . .UCI‘ILllLiCU. . . H7 79'! 761: 156 Id?) 785 (,I'II“ u I00....CL{GC000IJDOD - ....I-I IUO'JGOCIL' II "C( (OOOCDOOO m4 . . .. . In 1- IIIJIII I' .vInrmu 010 Ibfi 'Il'l-UUUUIJI I"! C“ 060000000 . . .. H! 783 7d: 781 731 78]. 7d’l 160 1L ....EDUDI'I)DD.."CICOOCILOCLULI)(UIIIOIIBIUIIII...................un......-.: Z d 2 Z ‘ Z - -. ' ’ .' 2 _ . 4 z 3 lo A In I. I. 4' ~ I; ~ . - 5 '. - 5 5 5 9 I. I Z 5 6 '3 h 7 "I - | . : '. o 1 )LV‘I|I"II:NI CIJSI — URLLUVS CIIUNTV NEu VlJiuI 188 Table 5 (cont'd.) 2 2 2 2 2 Z 2 2 A 2 Z 2 2 4 2 Z l 2 2 Z l 2 2 2 Z Z 2 2 2 2 2 3 3 3 3 3 3 3 3 3 9 C I Z 3 lo 5 6 7 8 9 I‘ I 2 3 l- 5 6 7 6 MAP 5vSHEEI’ I'DATA SE7 I I I I I 2 Z 2 2 Z Z 2 Z 2 Z 2 2 2 Z 2 I l 2 2 2 2 Z 2 2 2 2 2 3 3 3 3 I 9 0 I. Z 3 lo 5 6 7 H 9 0 I Z 3 I I l I DCEOLCCCUDCO . . . .0000 00000000. . . .oouooouoaooooooooooooooo I 307 00(0000001'00. 0000000000000 00000000000 I CUCOUI 00000 0000000000000000000C000 l ......0000................ I 506 On 806 I DUCOGDODODOUOOOD. I CI 0 . I 805 r 005 I I I 50% 806 I I I 8’33 803 I I l >502 302 I I l PM 801 I I I ‘40-) 800 l | .- I 79‘) ...-...... 199 I I I 798 798 I I I 791 191 I l I HI: 796 I | l 795 195 l | I 79» 796 I I I ‘73 193 l I 1 79¢ 792 I I l 791 0000 791 1 “00000000 . . . . . . . . . . .0000 . . . . . . . .000000000000 I nnnn I 1w) mm!“ 190 I 00 . ... I .......000000000000..n I 1:19 ....-..-...0IJ0000000 00 .. 189 I ...........0CCC00000000.... I I 755 .................0000............ 188 I 0 l l 787 181 l | I no 186 I l 00 IJIU0III IJLIJ000U0000000000000000 I 785 . . . 0000000000000 JOOCI‘DCCCUDGODDUOODO 785 I ..00000000000000000000000000000000 I 1 18A 18$ I . Icon-... lic-III...[...-...IIIIIIOIO I mmm—nnwrrnnnrr “ I 783 . 0000C (20000030000000000000 JI 00030 . . 703 I OODOOCOCDCCCUUCCUUOUOUUUuInIu-JOOD. . I . . . . I 182 102 I I I 161 101 I I I 730 100 I l I I l I I I I I Table 5 (cont'd.) PREPARED OUR fRANCIS M. DIMUV BY THE bENESEE/FINbER LAKES RLbIChAL PLANNINb BOARD HE IIINAL INFOENAIION SV STEM #7 FIIZHUGH ST. ROCHESTER. H.V OAIA HAPPEU IN I LEVELS BEIwhkN tXIREHE VALUES OF 0.0 AND 599668.38 HEAN = 113710.31 SI. DEV. a 108976.19 ABSOLUTE MIVIMUW FAX IMUM VALUE RANbL APPLYING TL EACH LEVH O. 133 489. “Q 2655 1332d9. 94 10:578. 58 BSGBGE: 38 PERCENTAbE UF TOIAL AuSUlUTE VAIUE RANuE APPLYINU 10 EACH LEVH '3 35 33.33 33.33 FkEJUkNLV UISTKIBUIIEh IF UAIA Frlh7 VALUES 1h EAfN IEVEI LEVELS I Z 00LUUUOUU lldll III UCCCCCJOC I‘IIIIIII SVMdGLS )(UC C000 '80! Illa UJIGhOOUU IOI IIIIIII 00 Il:lIlI:: FREQUEICV 310 230 I: 190 Table 6 : Total Cost - Orleans County, N.Y. HAP TITLE TOTAL COST — CRLEANS LJUNTY NEH YORK ELECTIVES USED FER THIS MAP 2 THE FLExlN LCCATUR = b MAP b¢SHEET -—.__r-l..._.___—.._~.—-—-p-.._I’<._,_‘__‘___-——~—.p-— _._.,_...,_._. H__—_—_..H_.r.__ m_.c-—-»...-—...._.._..._‘._p—._.._..__._,_._..__...____HH___M__,_H ...—.._._...._. .._._. IJTAL C057 2 ODATA SET 807 800 606 604 790 764 law 767 750 75: 784 785 752 730 191 Table 6 (cont'd.) w b b m;:‘~ # b UI#IV b ~J#»~ b‘N 07b?» Oan "’U‘N K’U‘N WmN t~mrv U‘U‘N O VIN ~4U‘N ....OOOOQODU........UDOU....0000....0000000000000000....DOOOOOOO ..o.CUOOBGIG........000C....0000....0000000000000000....00000000 ....COOODOIO........0000....0000....OOODOUOOOOOOOODO....00000000 .......OOOOOOLJCOUO......IOOOOOI'......06......O.0000....DOOOOOOOUOOOOOOOOOOO O..COIOOUOOOUODOOOOOOC0.0.0.........IOOOIOCCO.IODOOOOO0.00000000000000000000 I.IDOIOOOCOOOOCOOO....0.....I...I.0......-......OOOOOOOOOOOO....000000000000 OOIJIIOOOOOOOO........0.0.0...........C0.0.00.0...IODOOOIOI.0000000000000000 ........0000....................on....o...........-.0000.-..0000000000000000 OI......OCIOOO......-I.....-...I.0'00...0.0.0.0...I0.0000.0.00000000000000000 I.........I'.‘.0.........IOO‘V)U[)EJU...O...0...............................0000 .................-O.........OoleOQDICOOIODQOOCOII..IIOOCOCOCIIOOO'OCOC0.0000 CID.......IOIDCIIIOII..IIQICUOUU.......OCOOrO.IIIO......II..."0......OII0000 ............................0000........00000000....0000....OOOOOCGOUOCOOOOO ............................0000........00000000....0000....0000000000000000 ............................0000........00000000....0000....0000000000000000 .OIOCCICOCUOOOI0.00....0.........‘OOOOIIOOOOOOOOOU..........OCOIOCOC....0000 0"....0OI0.0.0.000...0....OI...IIOIOOOOOOOOOOOOOIOIIO'IIIIQIOOOOOOODOOOOOOO IOIIIIIIOOOOOO......OIUIOOI..I.IIIOCIOOOOOOOOOOOI.O......-......CUDOCIOOOOOO D... I. 0’ II I. I I C. 90.000000... 0.. O O 0.0! I. 00000.. IOOIOOOOOOCII CDOOOOOOOUOOOIII. ....................0000................0000................OOOOOOOOOOOO.... ....................0000................0000................DOOCOUUOOOOO.... COLOCCUOOOOOOOO.......OCOODCUQO'00....I'OOII0.00.00.00.00.......OOOCOCDOOOOO DOI)OUUIJOOOIOII0.0.0....IOOOOIOOOIOIOOIOOOOI'0............O...0.0.0.0....0000 ()1)1IOC(J00.I O. O I 0' .0 O O O. O .0 O. I. I. O I I l O. O I I‘. O O O. C .0 I C I. IOOI I ... O .O ...... C IOOOO ....................................UODO........OOOO............OOOOUOOO.... .0 I. O. O. .0 O. O. 0. .0. I I. .0. .0. O O. .0 I 000000.. .00. 0 00000.. I... 0.. ...UOOOO)OU...O 0.. I 0' II II II I. ll .0 .0... 0.... II. I 'OIIOOOOOOII .IICDOOODOIOIII .....OOCOOOOCIIII .0......OOOOOOOOOOICOIOUO..C0.00IIOOOOUCOOOIUOOOOOOOOC....ICOOOOOOOOOOOOOCOU GUI-I..-....ll0.0.0...0.0.0.....IIOIQOIIIII.COOOOOOOIOCOOOOOICOOCIOOOIOOIIOI IIOOl...00......0......OCOCOIIQOIOOOOOOOOOOOOI000000..III-IOOOIOOOICIODIOOOO I.......OOOOOIOO......0.10.0.0.0.0.........ODOOODOOOOOOOOO......OOOOOIOOOOII Ill-IOOIOIIIOIDI...-IIIOOOIIIODDICIUI'IOODIO.....IIIICIOIOIIIIOOIICOUCIOCCI. I.........OU'.O.O‘][)O1)OUOOIJOUUL]L)[JOU[)U.C............‘Q.'......".............. I.soconsole...OOOFCOOOOOOUOOOUUDOOOOQ000.00....Io.-00loo-OCQOOOIIOIOOOOOIODO ...........-o...OOOOOUOCUCLOOUUOUOOU........................................ coolon.Clo-cooooooolloIconooOOIaUODOOCQo-olootIOOOOOCOIIQCDeco-IOOOOOQOIOIO. on.0000.0a....00ooh...OOOOOQIDOOUOCIJOOO0'00.no.000.000....000.00-0.00.000... IIIIDOOIOIIGUI......IIDIOIDUIIIOOOOOIIII-.....-...-......III.IOOOOOOIOICOCU. UUfCCOOCOOUOo......-cocoon.coo-tacooooocooooooooooooooooooocuconooooooooouoo COLOCOOOOOOD-ao-ooon-ocuaonc-o-onoonn¢oaoooosooocoooooooontoonooooooocoooooo OOCOCFUOOOUO...............................o..-......ooo..................o. 80888000................................OOOOOOOO........00000000.....o...... 8880888000‘...I..............O...II.....OOOUOOOO.‘......00000000............ flDGUI0.0................................UOOOOOUO........00000000....o..o.... UUOOUUUU............OOOCOOUOOOOOOCOO.......oo....ooo........000000000000.IIO (OfCCOCOOOOOO0.0...IOOCCOCOOOOOOOOOOOOO0......OD..0...00.000000000000000.... 00000000..a.........UOUCUOUCCUUOOUUO................o....-..CCUOCCCOUOCCIIIU ...-on-Ionooooa.ot-nooouOODD-oo-u-uoooooUODOooonto-on.onOOOOIoooOOOOanonloo IDOIOIOGOIOOOIC........IOOOOOQOCQIC...O.0000...‘........0000.C..0000.‘.....- ........................0000............UOOO........o...0000....0000........ UGCO....OUOOOOCOOOOO....UOOO....OOUO....UUOD........000000000000.....oc.0000 0000....UOOOOUOHUOOO....0000....UOLC....DUOD........DOOOOOUOOOCO........0000 0000....LCCOCOCCCOOO....0000....OOUJ.. .....IDODOO.........U'OIOOOODIQOIJOOVO ..0000........000000000000...o....0000 not....0....IOIOIIOIOIOOUOOOOOOOOOCICO .0....IIO....OD.......ODOOOGOODIODUOO. ......O.....0.0......OOOOUOOOOUOOOOOIO i.)00()OI.I..IIt.I.......II...’...I(JC[’)[-)IC.......0....I.........OCCCCCCCOUOCUOI. 00000-00000...COnot...otooounoooOODOooO...-altIIOOOOOCIOOOOOOOIOOOIOIIIOCOOO OUOOoooouo-oo.caste-once...oo1voUOOCoo-to...oooucooonoooo.aoooouoooolucognac .................«...........................c..............OCCCOCOOOOOOOOOO ....0000......00......OOIUIOO'OOOIDOIOOOOI'OOIOQIDODOIOI’IIOOOOOOOOOOOOCOOOOO ............................o.....................o...oo....0000000000000000 ....................................OOOOOUUOT000000000000000....COC0....0000 ....................................000000000000000000000000....0000....0000 ..........................-.........UUUOUUOOUOOUOOOOOOOOOOOO....0000....0000 IIIOOO'CCLJOOIOOOQCOOC0.0QOQOOIICUOOOOOOOOOOOIOI0.0...OCOOOOOOCOCOOCOO)OOOOOO ........OOOO....................0000............-.......00000000000000000000 O'CODOOoolltjoo.............-O‘OIOOOOOQIUOOCCODO...O......OOOOOCCCOOOOOOOOOOOO too-CCOUOOOOOODOOOOOUQon...000000000.".9000coo-OCUOGOOOOOOOOCOIIOOOOOOOOCOI OOOOUOOOICODOO03......IDd.......L)000'."l0..IIOCCOOO..I..D...COO......ODOOIQ ...-(000......oococo-o.ouooucoooCOOO‘..'oooonooonoooooocon-ooonooo.coo.0000. ....flflflfl........................UCIIIIIIUOOOOUOO.........o......0000......o. 01.0.8a'ocoooc .....II‘0....Ill......s'I'OOOOOOOOOC.....OIOOCIIIOOOOO.C...... o....ifl...-o..o.o..........o....IIUCIIUUOOUOOOOOo....o....u7....0000o.u.-coo ............OOCOOOOO..o.....OOCOCICIICIICUII......o.-...0000...40000........ InooooocoocoOOCOCOUOIUOOODOOOOOO...'.a'ea'.IOOO00OIIt.OOOOOOOOOOOOOOIOOOOOIO IolDno000'0000000000..OOOOIOOOOO°.°."'...‘.0IOnoo...IOOOOOOOOOUOOOOUIOCOIOO oaooCOOOOOOOoocoCOOOOOOCOCOOUOOO".'.‘.....'.-30.000090ooaoooooooouocooooooo ...-00000000....0000000ODCOOOOOOIIIIIIIIIIIIc............................... oocoCOCODOOOO.o.CODOOOOOOCU00000..R....."a.o.so.noooooo-cooo00000000000000. N N N N “IV N W O £re b t b D b t 0 PF4 r b w w-m'v NJvIN w 0 0,8) ‘JU‘N ORLEANS COUNTY NEW YORK 807 806 80¢ 803 802 801 800 799 798 797 796 795 793 792 791 790 789 788 787 786 765 784 783 781 780 Table 6' (co_nt'd.) 2 2 2 z 2 l 2 2 l 2 2 Z Z 2 2 Z 2 2 2 Z I 2 2 l 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 9 C I Z 3 6 S b 7 8 9 0 I Z 3 § 5 6 7 8 ‘MP vaHEET IoDAIA SEI I. I I I , I 2 2 Z 2 Z Z 2 Z 2 2 Z 2 Z 2 2 2 2 2 Z I I 2 Z 2 2 Z Z 2 2 Z 2 3 3 3 3 3 3 3 3 3 I 9 0 I 2 3 4 5 6 'I B 9 0 l 2 3 £ 5 6 1 I I I I l OCI‘CCODLCDOO I 807 000000000000. . . . C OODOCCEUDOD. . . . OUDDOUDDDUCOUODOOOOOODOD 801 I 01 1000. ...000000000000. . 000000000000000000000000 I IOOOCOUO. . 0000 I 30D "7000000.. .....1.....................-.......0000................ 806 I 10000000. . ‘ I Dr].- I 405 805 I I I 804 OOQ l I I 50! 803 I I I an 802 I I I w] 801 I l I 80) 300 I I I 799 799 I I I 7% 798 I . . .. . I .3000........0000......n........................ [ 797 nnnn 000“ 797 [ ..UUOD........0000..................n-nnunu. I I 7‘70 796 I I I 1% 195 l I I 79~ 79‘ I 795 793 792 792 I 79]. . .00 00. . 7‘“ I . . . . ...OUDODOCID....:....u.0000........000000000000 I ............-.n.... 790 790 1a») 189 000000000000. 0000. 788 188 767 787 760 186 um 00000000000000000000 000 185 00300000000007.3060COECOOCOOOODDOO 755 00000000000000000000000000000000 ...................-..nu... 78w ..........-....”nun-..."...u 75. 755 . . .000L)( OOUIIOOUDLUIM 000000000000030 . o 703 OOOUUCUU ODUOUODOOOOODODUOODO 000. .- ..... . ...“... ..COOCDOOOGDOO.... 182 o ...OODCOOOJOOOOH 782 . . . .000000000000. 181 781 780 100 ..1 I .7 ,. .. 1.3. k. AUX—5d! ‘ . .. I. ...- RENE... _ . .r Table 6 Icont'd.) PREPARED ION FRANCIS M. DUMOV 8V IHE bEVESEE/PINGLR LAKES fiEGIONAL PLANNING BOARD REGIONALU INFORMATIONH SV STEM 47 FIIZH R00 HESTEK. HN. V. DATA MAPPEU IN 3 LEVEL: dETkEEN LXIHEME VALUES OF 0.0 AND 509368.25 MEAN 2 [15230.00 5'. DEV. S I113|l.88 AB)JLUIE VALUE RANGE AVPLVING If EACH lEVEL MIN U! 36622 75 27324 5. 50 MAthUM l36b22. 75 273245. 50 4096b8. 25 PERCENTAGE or IOIAI AuSDLUTE 33 3 5.3 VALUE RANGE APPLYING I0 EACH LEVEL 5 33.33 FREJUENCV DISIKIUUIIUN OP DAIA POINT VALUES IN EACH LEVEL lEVELS “ 00 LUUUUO lflflllfllll 000000000 IIIIIDIID GOLD 0000 I'll 00.. “(It (00000 [00000000 UUDUUOUUD IGIIIIIII SVHBOLS FEEUUENCV Table 7 : Aesthetic Index - Orleans County, N.Y. MAP TITLE AESTHETIC INDEX - ORLEANS CD. NEH YORK ELECTIVES USED FCR THIS MAP 2 THE FLEXIN LCCATUR = 7 5 THE MINIMUM VALUL IS SPECIFIED AS 0.0 5 THE MAXIVLM VALUE IS SPICIFIED AS 71.70 II THE LEVELS HAPPEO AHE STORED 0N CARDS < - IS AN INVALID INPUT CCNTRCL HCRD HAP 7.5HEET ZvCATA SE7 I 195 Table 7 (cqnt'd.) I I I I 2 Z 2 2 2 2 2 2 2 2 2 2 Z Z 2 2 I 49Ahhfi466455555555 I 0 I 2 h 5 6 7 8 9 0 l 2 3 4 5 6 7 I I I I I 507 I I I 805 (0C0lllllillllll0000........_................00000000I ....... I UOOOIDGDCBIDIIIDOODO . I HOODCCODUOGDIIIRDOUD.. 0000000000000000 I H05 0000 COODUDUOIIDDUOOO................0000............0000....00000000 00000000 I . “fin“ 000000000000000 I 000000rm "0 "n I ao~ 000000...........-........0000.................... I .000000 1 nnnn nnnn I do: "000........0000 l .......000 0000 I nnnn I 801 I I I 8\I1 I ...-...... I nnnn FPOUDDODOUDO 1 ann I I I 799 I I I 79M I l I 797 I I l 795 I I .............. I as I I I 79a I I I 793 I I I 772 I I I 741 I I l 790 I I I 769 I 78% 7u7 780 785 754 ...........-o.. 783 ..... . ............... .0000.... 762 .. ........ .............. 781 ..........-.... 780 o.....-..-.u........... ......o............................................................-u.- Z Z Z 2 2 Z 2 Z 2 2 Z 2 2 2 Z 2 Z Z afibbbh66$655555555 0 l 2 3 h 5 b 7 B 9 0 I 2 3 4 5 6 1 AESTHETIC INDEX - ORLEANS CD. NEh YORK ”,. 196 Table 7 (cont'd.) NAP 7.SHEET lytATA SET 1 I I I l I 2 2 2 Z Z 2 2 2 Z Z 2 Z 2 2 2 2 2 2 Z Z I I 2 2 Z 2 Z Z Z 2 Z 2 3 3 3 3 3 3 3 3 3 l 9 0 1 Z 3 4 5 b 7 8 9 0 I Z 3 fl 5 b 7 8 I I I I 000000000000000000000000. . u. . . . .( 0000000. . . . . .. . . . . . - . . . I 807 CDCOCOCOCLCCCCCCCDOOUOOO . 807 I 000000000000000000000000. I . . I 006 506 I I I 805 805 I I I 804 80# I I . . .C00000800000000000600000o . o I 80 3 . . . . . .UOOOIIIDE 000000000000000. 0000 0. 803 I .UGCCUDBDOODDOCOUUUCOOUDO. . . .0000000000CC. . . . u .. .II I rnrn urn nnnn I 302 .0000........0 00000000000.... 000000000000................0000: 902 I 0.000....000000000000 I I 8C1 801 I I I are 800 I I l 799 n0'30 ID 0 799 l nrnonnagonnn I nnnnnnnn nnn nnnn I 7% ooou 0000 mm 0000 19s I ...........00000000....0000....-o....-.0 000 I 000000300000 nCIDDDCICD I 797 .. . nnrnguoooooo 00000000 797 ““0000000000 00000000 . . u u . . . . c . . .CCUCUL CDDOOOOOODDIDID 0000000000 00000000000. . . .00000000 706 ..DUUOJOUOUOOODODDIIII000000000000000CO0CC.. ..0C000000 796 000f0000000000300000000000000000 00000000 79‘; 7‘75 I I 794 19; I 193 793 792 7‘72 nnnn "0000000000000000000 791 nnnn ..0000........ooooacuccouooooaoooo 797. "fin" 0030........00000000000000000000 0000 00000000 79.) 790 .6000 0000000000000000 . . . . ODDDUCOCUODO. . . . . . . . . . . . . . . . 00000 769 COOUOODUDOOOOOO 00....OODUUUOOJOUO..............-.0000...-.:-.......-:....00000000 789 IJIIOOOCCDPCCDDDOO. .0007. CCCCIJOOO. . 00000000 0. .. .. .0000 0.000000. . 78" 0.. .0000! 00000. 788 0000 . . . .0000III00000. 767 .....-.....................0C000000.... 797 00000.... .000000000000. . 786 786 765 785 765 70‘ 783 783 15; 782 781 781 780 780 ................................................0000....0000..................-. .. OA-N ~ N I-INN r- uNu oN~ “Na. OWN o- own. uuw Nona uun run mun. Dun: Nun u 197 Table 7 (cont'd.) 'AHIIJILJII"uH I; ”. HUMM- \‘ Err IrLLu‘c/rgnnLu [ARF5 HtmlIHAL VLANNIND PhAQH NY: I MAI lfJUJwHAIIIJJ bYMTtH ~/ 'IIJI‘A'EI ii \“WII rt HLwIfim, 2... )AIu “dPVLU IN 5 ILVCIS HLIHEIT (\IHLWL MfiLhtw ‘ {.9 AND II./0 MEAL = 20.01 SI. DEV. = 31.97 505‘LWTE VQLJT P0.J: AJ”L1Y;M l: Iutw It‘:1 "[‘IJIHH‘I ‘ ‘ \ I .1 ”X\14H“ _'.I. «5.x; ’1,( Jy< U in» ' I‘lui . 5‘LI“ VI u‘ 3H. 3"Lv 3t“ L”! ‘ «I ‘-‘ )I ',I« FDrJWLHLY Ulglmlqul;. 7F “LIA WWl.i XJLH'B I. “|* ':«%L ILA VAIUIJ LEV',I u j I I 1 ......... {It IE'J” kWRWkaéfa ......... I(“F(t: ' Eaaxxuanw uwWHLL) .... .... IMHJ 'TIU Wflflfl 3A‘——~ 2 3 3 2 3 2 J 2 2 2 2 Z 2 2 2 2 2 2 2 I a a a a 9 A a u k « S 3 5 S 5 ‘ 5 S 9 O 1 2 3 L 5 c 7 5 9 ” I 2 3 k E 6 7 ‘-__,_..__.___n. ..._ “- _...., .H___.._._.._...._,4 g ........................................................ . _________________ I'DHEEI I.IIAIA 'I . 1 JJI I 7'1’ 4 .v . I , I 5 z ? I 2 Z J O 1 ......... 0.00100. 0-001400 0.0.0...- ... ..... ......... ....h 56. ....3000.. ..MSKW. .4..... nkrkhwcpawF ul.‘ (“.081 x.‘.‘I'IA-Ii‘.‘: . . I uxfiu33038035....wak......... ...QExEHINUHSHAI .Kflahndflaxaxxs .xwwwwaxwagiL o\./ A) I- . o .kfififiiwmuhkfih .GRJSRERKWanH .EQSESZEMNUQJ.. ABAAMGMNK . v‘ N‘ I“. \3 \ 3 (cont'd.) \. are I: N V‘- 0 ..... . KPNK . .. ....... . .JJJ3.; ... ......... ....KNKE.. ...... ..33Wb83dKflHfiS...-........... ..xfimwuukuumuu. . .smsaa.mur3.a.. '1 VI :13 ALI "- o wudwdwmuahldn ........ IAWMHfiSRKEhe!hmxhxfijAAVJI..,.. uxtamxkuxKKmIKaEWKNF: “a. I .. 1K0113WIJJIH.. .. JHGIKS'IZ'IkxéEKGI‘XOII‘3'3I s a s . o . .- - o o. c a o 4 . . xfirxitumxaflNudxM... ............M Israaxxam&..xxx...... . .... oaro.Enaxu43........ .I ....xin... fiF?uKK¥NKRHE. ..VAU‘. ..Ih;$. gabxxx. fianGaxa. ANnrNMuq. ......... ......... xnbkxznxmxnm............,.. (xKK....EhK£fiJwH........... wmua....msusxmwm........... hofifi....NkXRGWNI... HMfifiNKkKKflXkNKSKKKBRKSSK... wo§xb¥3xsamkwxxsxmxmuxxw..... gutnuk.xasuuxaaauamwxaaw. nabutsxmxrxuasuxuuxxNQAM$ Kan».artxxxmmxawawwwmxnssuwaaasfl... hxmxxurut>wrxkaa ....Hk;s....Xkfiktfifihiflfidflns&........... flfihdhhdexxxxukx,............ xxaxstaéassacams............ (u n. W A I‘. '\ $3 :‘i ”I A. :- .HWSJ. ..Hdfifi ..... ...]. ..... ...‘I . 3...... 0 c 3&1A51d... is. .V‘UII‘: - . . .343E....Nfl33.............. 33Gh....l$fih.............. .333“....H¢HN............. 3 k‘ L 2‘. I‘ I‘: .\ '0 I‘. . . . .KKK“RNXKWENKN$U§.-.v... ....mmwmzm " I RMSAhEFKRhKhEfiSE.. :xI-R.nyxxxmatauaduxuasmmsu.r......KRxfl...... . .....KNXN.... .......nfiknxrxguwaeksrnlwquxxwuawx.. . ...xsas.... .u .sxxaxuaade<. 1WUIV ”I auxa.‘ : ms.<.;o;axxx«wk-*. .... .Jasu .SRxKEEiufinwu........5xuhrr.rsnh,.afl.ax-I.xgaamunhu¢rxrux........¥aaa . . .SfiKK .000“ «B3! . ”u . . . h \ I" ‘.I'. at . too-o . Eh K'.. xaxx ........ ~..“J’(L‘.’ . . . . . .. .- . . . .-). .. . . .. . o . . u . . r-krr)t¥*6 IxRASXFtslwxxafifikmjfixla ; xajxxaéyauaaarxarKSIxxxvI x53rexr¢<¥aax4xné1 4"“ . ......... . Iv o . ... . \. . ...N I'. ,s .’ v'. .ktAJ053NA FK§’... KH?¥FE ... . 0.:7-3'“ .01, o '-:‘-trr.:'2.r.' IC-"‘.‘. 9 '.\.. .‘ ...‘PP 3.. -...I'; ...... I'n.‘.-1.“‘.u. A‘II 1‘. ’x . .. .1 .‘.}.c..\ A .4'. ". .. .. . . I. . ‘5... ,‘.'." .,-l .‘If'n‘u I‘ A . .fiflc71 ...JSXA....08“E3 ..I...33L1_ ..gupggr ,As: ” w.“‘ (Aanrmerfitnxxr NtlirK?Kkihk€hh€b?€kh¥iuh LL!» ovfiunurhx>_€htv LI.;. :4»:35179 X'AVQIOIG 73110:! ...kxhnafi" '1 a I$.§iv3..diuz ZI ‘- whfifll: " .mLIII Aun )i.’ I 577,4 3332(3'1 30». .'u."_‘., »abbfifihr” >afiagkflr" ’fiwhWL . .1103 :‘Kllq’w A ,‘ '13.. t'. A. I' .~. ~5Ka9r I 'wa'irug.’ ~.'.\ 51 In? 030235 1....300300E83S88.. i.,..333483835330.. 1 .yaflfixmmxaxmx anaanaahvuuirxfisst 1:24xuumuusumxunn.. gimme“ JIM-1F. \mINE'u: . . ,%13'*‘33%%3$ .AAHUVI'1U.Wfi ..3k840034MNdfl..... aka-sha-LHKEILL. ..L.£‘/.’. . zunaikuwxuuauxu£n3,, xtrnusxu... .«k'tulni t344..~.;.uwu$833 NxSNnZ‘” .’.r..... oo-ooo-o. ..onoo-rv o .o.ao hilt V0. 0 0.00 0.- .9a .uon c '0 . ¢ . o ....It .po.opo. 805331... .. -. 353.1‘1- 'xx” .ahfixahan»A.»:‘DKKnfiSKk“J..... A.) wandg'" t.n33¥1 .siixwrxntxvgsxuaanassusa..... at». ‘.I\XAA Kfacfififl \-* .‘qu. Insxflazxsxamu.... XSew~ “H's“; ”Lt-Mkaaq.. h": IamLus; nx¢&.. Iruf.-‘5{...i.-".'rb'r'EIiNK-n“. .r.$r.'~.. .K'I§rbh§.iflu’"’3..... v c c v o o c I o . a , c o o o o o dOo H05 809 H01 70“ I I I I I I I I I I l I I I I I I I I I I I I I i I I I I I I I I I l I I I I I I I I I | l I I I I I I _HH._..__—..—._--—..A .HMHHHHHHHHflrl VA_H_.._._..~ .—.-—.__.._.._ IATA ”..U‘Pft W‘ i L’ LLVTLJ 201 Table 8 (cont'd.) I"‘i;I‘»‘3.“I I) IVL‘I: II-‘x'x .LiIi» "‘. LIQUHIIY r‘I' [Ht \,‘;’ 5 I: I II II‘ II n l.'.\::‘) I-flrgll NIL L’l ANN-I0“) xrulwflhl |.fH-IAI13u ”YnIEV -' rET/wJuu gt, ,Umtw m I MLJIUx , VHY, I‘CIHLII“ tJlIrk'H "."‘|l‘3t\ r \." 57- 1.;‘1 AI’SSILUIE ‘JpLIJI- «‘H‘én; hIJILYINI: II IAIN LLVCI I VI II'MI ‘1 PAKIHIJ I ”1 CI; II It): f;~" yumhr Lt VCL R \Y"II I: F n'f .Ut I“ 1 \g'.%I~‘l:\UII . H— , I YALULB I. l‘.!_‘ 3‘ IN?” LI; VUIIE hhnnt AIVLWIH i‘ .l“ «L !L .‘oII UC-"fl ‘IZIA In If.I ",-"\l"IL", If. ‘mf-I [[ I'ILL HM," VLLHE x " I z 5 ......... oammuuxsu ........ fihk‘kfifihmk‘ .00. '0'! “INS” ':8Kk ........ oxznumuax .. ...... aaumxauaa Q 5». «oz 0 Utv. 202 Table 9 : Low Property Tax Revenue Loss, Low Development Cost, and Medium Aesthetic Index '4QV TI TL: 3 rHt ‘LF‘KR [ngryik ; “AP dISHEET MOO _‘._.—‘_._._,_‘_._,_.#_._,_—_.._—-" h F! ;. ...l..____.._..—..__.—._.__._ 2.UATA SET CVK‘ OPN mamm...... NHGM...... EEK”...... SUGGGGGG.. 88888888.. uamummam.. RQKEEEKN.. BN38KE$S.. bn; O 203 Table 9 NPR) “bk; ..EEEB.. ..EUED.. ..EGGG.. ..E@@8.. ..Uflfifl.. ..GGGQ.. ..aumu.. ..Uflfifi.. GERGRGQG........GGGG.. ........sammmmux@mmu.. ........ESKKGQGBE%E§.. ........EE@DDNGBENED.. KNKEEGJG........EMNQ.. ESUEGFSS..... KNRKKENQ.. SKENKKEE.. KKK!K%EM.. K§kKKEN@.. ....KRKE.. .KEJW.. ....KNNM.. Illicit... out 0... NEKGAMNN.. 0000'. ..ESKK.. ..GENU.. .888“...... .W&EM...... .5K8E...... .....8®R@.. ..@@88.. a ouumuifi .SGEN...... .MMNN...... «smsemmx....xxtx...... EXGHKGMEKKGGGNKEWMKW.. U38UGJKQGEGGGNGSEMNM.. flNnKEQKSEGSQJGKSXKNU.. ....88KHGQ8G“GSU...... ....EGSfiGBBfiSRQG...... U7 1‘ h; 1‘ (cont'd.) t___— .--_-__--..--—---___-__----...._-__---..---__..--_---—--------..------__-____....--_---___---___----..----_-..-___-------_-_---—----fl ocoouoaoolcllooboo IIIOIII‘. .....II.. ......II. .EEUM.... .KEUQ.... .QUUM.... .KEQE.... .860“.... .NGMG.... cantata-o ...flnaa....0. ...-8836...... ....ECU8.. .ECKEDGDQ. .GHGGGUGU. .QEBQSEEE. .IIOCICO 0 I C. Co. 0.00.. .....ummkmasm.. .....UEQMQGGH.. .....EEDNEENE.. .3888Ufllflfiflfl3.. .QGHGGHGGGENN.. .zxmxncnuxssa.. .GUGN....... .....MBGNNMEBQGQGGNGSNGGU... .....aaasausauuaauumuuasa... .....KEGQKSEGEECQQflQOflflEG... 000. 0.00 N N N .... NU? 9’ ....OOOOIOQIOII ......O...‘IOOO O O O 000.... ..flflflfl... ..GGBU... ..QGGH... 0.0.0.... 0.0.0.... .....O... 0.0.0.... IIOIIOOOO 0...... .8838.. .enaa.. OOOOOQIOI-‘lcmmno OIIOIOIIOOCIIII. ......IOOOCOOOOI nomafleoolod 008038.... I ..BKDE.. 00...... .......l. ..DMDE... once-It'llonganoac ........-.....@flfl@...... ...KUNNSHQOEGNQQUGCCUDE.. .....NGGGGNGQCDGGEDBUDGUC.. .....Kflfiflflflflfififlflfiflflfliflflflfl.. .8&Gm.0II...U..OIO'..I..I.....IOOQGGQ .8388............................Cfl@8 .........s@n»unsuauax.. .........KGE888§G@GMG.. .........§EKEKN§E$E8®.. coco-IOOCOOIOIQIIOIIOOO O \flLfiN I........ .0000...- .....I... 000...... ......‘OI ...-0.... 006...... ......III too-0.0!. OOIIICOCO 00.00.... ..I...... ........I 00000-00. .....3808 .....3888 .....ED&U .QEDD.... .QDDU.... .Gfllfl.... .....................GCEG .3888....QBKKKKE88&DUBDQO .HMNE....EKEGEKKEEDDEDDDD .flfimfl....SEQEESEDOQDUDDDD .fldflflflflKCflfiflflflflECGCGB........ .GCGGHBUGGUGGUUEDECRB........ .EGSGGGGBGGGGGQGCGEUQ........ .GQGG........8088....GGGG.... .flfiflfl........8680....fl3®fl.... ....8“MK888K5BE$..........-....u................Oflfifl........flflflfi....ENGE.... ..xwxmmmswnwam............wwwa....axacumsussmeasecmxaaaebaecsxszxwannassss ....83888888EK88............Gfimfl....GflfififlflflmtfleflflfiflflflfiDQMDUDDQEDEDKflflflflflaflflfl ....amauuma:3wzm............wuam....muaausmmxaasamsaauaaaauaee«Ecsxcewuxaeas ............x“E8888BENK888mUbfiflfiSKSSNUKflflflfisfiflflfllfllfl....GIGG. ....UGKG@ENDEKEKUBENflfluuxUUUEBEGUBNEKUHGHGGG....GGGG. ........KGNHQNKfiKGkEflflflflfiflflflflfiflfl........SBDSEEKD..... ........fifififlflflflflfiflkfifififlfiflflflfififififl........BBJGEGQG..... anionic-EugxmeGEC‘t‘EgouI0000IOIOI00000000£fignol ...-.6888.- .....GKGQNNGQKMN&.. ........6%HVES€£EGGG.. fififiKuNKSNflKN....NNWW.. fiNhtKflMREfiflM. 8khbfitdfllfiflfi. cacao-00.4... NMKG.... 38H3.... Mflfld.... ....IOICEuNaD ........8883. 583%. .....Ill loos-o. ooloaool [no.IIOO NbLKKfifin.. Kflfiflflmud.o ssessmua.. amum.... “KW“..a. fiKflfl.... IOOOIDOO n-ooootoaaaavnnoloo C ..BQKK.. ..Kflflfl.. I000...- 9.0.00.0 I'OO'...’ 000009-01 coeroolna CODODQIOO I'D-Fl... .3833. .nmwm. .....flfiflBGflKMfiGGflafldfiflUUfi. ....SSSECNQUMUKBSGwUKGXi .KXGKSGKEEKCREGflEEEZE. ..KKISREKNDKKKEENM.... .GNGEQUKGMNKQUUNN.... .3888838”UUEK§@33.... IsuaaOOOOOOOOOOUOOIOO ..flfi‘fi....... ..KUEE................ .NKENISSE....ESN$.... ...........-EKKEEKNK....NN3M.... ............KDKEKKKU... ........XUUH........flkkiflflfifl.... OIO‘OOOIOv IssauOCOCI .MGSGGIXJ.... C.II....“flau.......O'ause.au.l0l ”sMSOOIOOIOIIOOCOOO ”Goa-IIOOIIOOOOOIOI KDGSIIODOIIOOIOIIIO IOIIOOOIO'... I...IOO.U.€'. C U Q C o a '6 .........UHGMGKUWHGGGflGGUGGGGGGQU........Gflflflflflefl....o ..DGEDDGUBQHNE. ..flflflflflflflflflfiflfl. .....flNflM... luflxnl. .SKUK. cu 0 a O o... I... e o .uwecsuuasaau. .QDUR....RENRSGSRSNGO..... ..uausaeecauso... ..EKQESGUCDRDD... ..mfiflflfiflflfl....... ...“GJOXGGQ.....fl. ..UGRMISSG....... ......EEOBBGEE. ..Bflflflflflflfi. ..8833. ..flfiflfl. ..Eflflfl. n 4 s . v o o c o v o o o u o o o 0 ¢ 9 ouncoo-oa...‘ OOOOOCQOOUOO .GGBECOQNIIGI. .aaaaamausasl. .EQUKOIIBHIUR. ODOOOEES‘OOIOO v I uses”. a v ..QEIU... r ‘J h) r ..— r'J ..4 \ V . .........Swfixfiflhumw8KEKUUBflflEGBBRGGOGHUUUUUUGUHHG....flflflfl....KBEEEUDCBDDB .EERGBMDEBDIE .SKCKHNSEDEIG IKEKKD'OOOOOO .BGGG........ anmnblloIOIl O O ......IOOUOO ....OQOOOOOO CO C Q .flUOOBflCO .UIUUIUUU .UHUUIUUC .Kfififidfiflfi.... ..8KKUQBSC.... .SQUGGIGG.... .....Gfiflflflflfld ......flflflflfllfli ..UGQGQGOI........GGIIIIDU ..MNEDRCGICEBBSKEIQEIGIIII ..flflfifififlflflGaflflflfiflflflflflCfilflI ..flGGGRIflQGRflNUEEUBCDQODQI onauuaaa'330ooooooooc0.0-on ...BBBCGQUG................ ..0!EDE%&E...... ..........EEEB.. ..........DK&U.. ..........Dflflfl.. OOIOCOOUOOIOODID O 030.....- .398....o ogs‘goooo .acaa.... 000...... 000000000 000.00-on 000000.00 000.00..- ...-00000 0.0-boo~u 0.00....- ticooouoo IIOOCQIOO out-0.... 7" -4 IJI F4 807 600 804 603 799 797 790 7b? 780 ;.JNLLT l.[AIA BEI (v. / r J .'I‘ V I L f 3 g k - 3 8 ! _ ( : - 1 1 i L ; _ ’ P g _ $ ‘ l ‘ 3 3 3 w L l g A . l m 7 I Q 1 a a c 7 8 ...........flflflu.............................. ...... .. . . . ....Eahh.... ....................... . .. . . . .....wamw.............................. ......... ..................... ......msnunauvxxnnmaua........aa;z....mbpu.‘.‘... .. . ............... . . ......anaauunamamuumum .......«wuu....wmuw............ .. .. ....... ... ........aaxmuseewhsxmwnm........Nwwa....u;us....... ... .......... .............aiflfi........................GquGAfiLKEKK......t..... .. .......... .........muwc........................axrnumxrsprw.......... . .......... .............msss.............t..........318433ux869£............ ....uwmw.. .... ............................mfifls....dammmHE88888........Ob&0 .. anxw.. .. . .. . ....... ., . .. .. &Nax....mam4wnxgvuad........uaum ... svxa . . . ..... ...... .. ..awww. .aumwsuuafinr«. ..t...sfiwfi . . ........ ...., ..... an:.eveuals..... .... .Rxwmxsxn...,......,.wswu «nw~....xyum........uxas........auamlsxacxsx..... .. ...:aumxaxz... ........33d8 xxx“....uxwx........wxsa........Auuxwexaswxx............swuuumux............3343 ........xxez....nsxx............................xaxx........swxuteas............ ........NBNH....LKKM............................wx33........RfiKKEhaK............ .... ..h:%¢....sawv.. ..... . .... ........... %:Jm.. .anKIVL' .......... .. .ébEvFOub.. ...... ....... . ...... . - .. . u... ..... , _.A&dfl8x5x .. .. .5?338h$«........ .... . ..... .. .... . . . duax. . . .. .83468BCL ... ....Kaixbkdh... . ...... . . . ..... amah" . ..uwssaxuz rhrxzknnfiuryxgx‘.. *-x»s<.. .. ‘c .. .. ..3733 p.‘r.)jh.~.l'r.bPi‘.\;«.‘.'il"... . va‘itAJJ" .. ...... L. .' . ......fiu‘fitif. AluukihfilfiflrfiCE. .. RICKfi‘KS .. if, . ., Kai! .aflfi........3?NK....§KHK....5565.... . .. . .... «Sau . bawaxfifix -Eat .....khN3....Eth . 163$... . . . . umnx ...Kmfinausa sTMM.. .....Ekfifl.. .txmx....~uxz..... .. . . . . ....... .Nhfir........$$flulafim u-i- . rumA‘..A... .. ch. 433a .. ‘ vbwtzaxn. H .- .- .1»! :~ . i~ b. i\.\' " fitnbu“). . . ' x< , .~;r.g‘ .... (r r fink . . ... LCJflIDLC. .. .......kk$d................‘wa............ . .NMHA. ..auaakfikfihltfi.... .. ....xrux................3xuu..... ..... ..nuwu.. . . awatxmawcagn.... ........da$W...........J....SNNH....... ...... unna. . .... ...»;xsmkamzssu.... ..~*htrtknkxmvtxs‘xxex. 1.. . . ....., .... utfimwrflififiunVEuxlxaa . ..... . . . . . FrrMFflérsxfi"?Au £%‘~ . ..... .. ‘.\\" 4G3 «film's: .\'.' 5.5.. .. ‘ 3‘ ‘Lt.\.‘l.§\ .5. . , . . ‘ ’ . his? 7 - . .nlmratvxwmnxpap paxxxmaa . . fifth... AkNdkSM§Nvfikab\h... as! «Ex‘ .....‘52: “AL: .sksn. .. Ak!#k?tfi....fifi§irufix . . . ;'aV§wa¢8JJFJ$SC kh‘} r. .... G‘s ~‘nLna.. [saw KA~¢G1§3....*&:ALth . . ...... . h 'a|#kqnvfiflflfifll ....knflxfl5‘a ... . . . ....?‘{~3‘r2k58....... . . ... .. . . ....kiFEEFux ............. . . . .. . .. . . .......... .. .. . .. . 463$ ................. .... . .. . . ., ..... . ... . .... . .. .. .auac ...... ............. . ... .. ...... ... . .... ............ . ......muau ........ . . . . ... .. ... ... . .... 8333. .aaaa ....... ....-... -. ............. . . r . . ‘:X* .$(.L.\ . .. .. ... ............. .. .H ‘ ._. 4 1303 uaux‘ . . ‘ I I n .>..){. ‘10 . ,1" A H9] :10 U Inl _____, —- . ,_ -._.__,_.H.__._..__._._,_.._. ......—._.—-._v—-...._.—.-.—-._H._._.u—4—ap_.-—-q—.._._,_.— h—__»<~—._.p—-_.._~—-.._._.H._._— .‘_._.—HH.A»4fi_HHv—Frfl O._.__....._.HH._.,_.H 205 Table 9 (Cbnt'd.) w» H‘ALELJ r-[IR rem-4'1) '4” n...~!HY rV I‘M (MF‘[El:/%lLbLh Llh-3 FLUILHJL Vlflhrlhb hUktl rlhlfihfl lJrCVAxTIMH KrSIrH w/ VII’Mpfl' “I. '_,.L)l|‘ "'{ikHLuTLt'. ’4.r. nATA anvkb IN 5 LrVrLa Htwath L-Trrnt vltlrfi '% v.0 nr‘ |./u MEAL : 0.:; ST. ntv. : 0.0% AUJJLH!E VALJE HAHN? Aprlvihu TL tJLH Irvu Ml ¢IHH1 I .|. (.(J' va«1wnw {.lk 1.8' ‘t'<\,Ll1r\Lu In TmlAL .'.$')Lnll,]L Vfllln rm”: M’I‘L\Em. l‘ ri‘xLH (L‘JLL ‘1" .\ I- ‘Vli'.\ M EanHLWLV HlslwlPUIllu Jr bATA 6'IH1 VALHL§ IN :ntr ILuw L'.w vAthS HI-M' VALUES LLJtLS J 1 2 3 ......... EKCKKQKNR ......... euxnmmmaa swlwuLv .... .... exam mama ......... KKDMNKMEG ......... amxssasua 206 Table 10: Low Property Tax Revenue Loss, Low Development Cost, and High Aesthetic Index 207 Table 10 cont'd.) "411V jobHEET ZuLLATA 3E1 1 ¢-_--_._-__--------__---__--_ ____-_-_..-__-____.__-..____..____-----____-_-_----_____----—-..—_..--_——_—————_----_-——--—--—--_-_-—_-.-_---. l (v 1* h. v r n U‘ k1 dY Q 4“ \A I .f‘ x. l C) ,4 S “v 0 x .4 -OIC1' ‘nf/ 5 [ ‘ -»~-~cr»oot~unnu.oo..o..t~.ooo.-¢ vi.‘o.o.oo.‘. 009‘.volaovll'l-Cartott9lllil. HO) — h—H—H—«_HH—~————~_~—~—- l..- ‘.-I-'-[K'- a , .‘ Lu] . 1'. v -.'.‘A.~l‘~< t co. | 'I.I.I... ‘ . v _ \.'. uv.--..-¢..~ ..... .a.“.,“ 4. V.... I. 40- .. ,.. . ‘.,. .....'¢(..o.. .;. C ,-5 L- - .. . ‘ l . .~ u -¢I. '0‘! I. v- -.---I- ~O.A_| b a vs I. I ' D BIA~V --.0 -| OIIO>IOO I 0' f'Il Inn. 0.... ’v' v. u v \‘."Q .. .uv ‘D‘¢lOv-I l"..’.-.l'..'..“ l .‘..sx.....-n..o‘onoaav-a-....-0......cc-unAr.«--o.o-¢.onco-us¢¢o<~ooooovoco 3:02 I 'I. \’F".$.'.O lsllllCoOOIto....-OI'II.|'I&O.O.IIII....DOOI4ICUICCIICUD... I ‘ I o~-.uonn.ntn-nu.nu.an».o-.oOs-ootoo.ooscalc.a catacoaooconuancoo-ooooauoaolo L ..l...-u...,a.......n......nna..o.-..-ov..-o‘.. 0...:non-ntlitaoinllouocliin "L11 I ...... ol'vaOIQIOIL.IflIIOl- 4-.-.---uauu 9“. Ivy-.II-III-.DdUOVIICUOOOIOOI I n‘l.7".N"...‘D...I."‘...'......‘ "..‘-UU'.'...U~Q.O'......'..‘~I.-...‘.r 1 “'r Y o a....‘ nv up. oann-nnonpa‘-n 4......c.p-¢.-x.~..-......o‘.¢... --o¢-o.nl9. ‘ A o I~O~IOIQII.IIIOOIIIDIOIIL-O'°IOO«QQovfioul-Iuv’ rcoaoucop.ooooou.o.non-o»... I I.u.~n--:oovo-I.u.u.u~¢o.»oo.O .-( 1 nun.u-uous-c...-no-ooccuavonon-ooau-¢.cou....o:.oo-o-..aotuoo'uoccvocuuo-uu- I ' I .-...IOO".'...""."".’.'....h.‘."¢\Q...C Q‘O‘COai4..I‘.l.l"l..'l.'..... J 7(,/ I IIOOICIICOIDI.......O'IIIl.......IOOOOODOIOCIIIOOO‘In.......IUI(OIICDIDI...I ‘ . ...-looilt..|£1‘v#¢OOOt"OOOFC‘bqi‘UVO‘O 0 -| ’v"’i.l u'Oquvl‘vO'lOIOIU I ... titan-on... poo-9.: ll.DOIOCIIOI-Illoa-z.‘.¢aol ... q-nqocn-I|'-\|-Iocalo I .I.IllhlillifinIOQCQOOQl-OQCCOOOO.'OI‘OOOOFF.‘U-4U.OIR~IVDU.|Oil-.....COO'IvDI‘. l I‘V.’.~-‘oo i u..-.-‘..o..n..o.uo“,....o.o .o-.,.oo.oasuuo:...-‘oxd\0.§‘n ....‘cuu cannoo-a ,- --|' f" 1 ‘ ‘ . . . no. 0 . .. , . .s . . . ... at ...... ...... .... n-cuuau c . .VJLJAL'Vl r o I 441c4-u1-ov-l /‘L3 “,4“ .’ . ‘va..--aovA.-ovo.‘.o..a..........-........oq.'oo-~voo.m‘l l[\“.‘"‘c0v4-.OOOIIIOIQJ L .~-‘- ‘.-.-..ppg nun. -. ...-u u:. \u.. A . ....n ..A-O-‘ «-—- ~\0lt.ulo L Y ...l..o.--».vorv wvw uq.<..r‘ ..«v-v-.--. Iouioonluuina- a ...-...o .o-oo ‘ A I II.V"DV>".!"OP ‘ . ¢ " ‘V'o b.01: 5'4 .0! 'nlhuv-‘COIIODOII. I ........g..'..............-.........no.ro......‘y... ‘ 4. Ito-0...!oll‘OIv-OIIIIIvIr'.‘:Ilf'v.1l.tl~O«-OOIOO.. o.4¢.c.o.-....o.... l“! j . ...-ooon-ooou-nuI¢-I-.uuoogo.ooooooou-upooc-oooo..-o\§‘d OOII'CDIIIIOIOOIOOO I [ onyo...clot-accoo-cpoo.oooooooo...-..oot-noooo-oooco-anon-u.loo-q-‘c.-oocaoo I 1 7 1 If._ nuvu...-anion.shuns-nu.nnI-coocu-IoD-Iooonnoo-o-u-no.cone-coo-oooootoaoooolo 792 .....u....ooua.oo-ovtoooaoaout......~aocoooq«o- ooc.--- ca .‘oo"o‘-uoco‘uooo I ‘ I ; I00-...-III.o-III-Ohio.IIOOOIJIIOOOIOal‘IIODCIIIOIIIIODQIIOOIIIQOOOOIIIODIOI 7 '-'1 1 l "! .v..-».-.o..-oo.--o-‘.co.~-o.. o- .. ...‘, c ,.-..,., .- a-va- - ...-n... 3’ In< ..-‘--¢:.v .;.--'-,. .-y¢ao » v.7 ......‘c,.-‘otvo.--.-«Avos.u.oaanu.c-I I I I‘n'to-ololoaoc nu-ucuuvo.--uo.-...a. . ...... ...-. ., cu.....V... ...... l . v"['\ I I .-..--aab- .....A-n-o-‘-n...‘.‘. .- . n-. ...-‘4 ‘- I ...: 4~. . OII'-. f“ . ,........‘..,¢ .. it... ... .. .,.. ... ,,,. . ...‘ ......-... I ..A.... . 4 .. .. . H .(...4. .. ...... l n. - ......»».. ‘ruqo. . ..; ..... .. .. 9 a. .. .... .vo-...o.... ‘1 I ..................;.,..... ..... ...... . .. ................ .-...... I 0‘run-u.........noo...ooocn-‘.oou.o......a.v . .... ..a-.qy~--4s;uu.-vno-o- 1 V'H‘ I do. .....nt-.so-Jcodoooooo.oo.¢-.oo ... . x. ,_ o u. o .00 an; sq.“00roouo '{ ‘ I ...-v1...---...-n..-.-una-¢nc.-...4 ‘01". ,... .n.- ..... a, .. ...., ,u I y." E . - n~ .o- u... un..ouc . ' a r .- ‘ . . . v ‘4. , l ..... .. ‘.. .... . .. . . .‘ . ‘v .. To ....... l r . o'-.o....oo~.n...ooo.-u-~.-. lvcv .. ‘0 .¢- rv--:.- .v‘u » r .- o.na-.-.-. «. . ’ 1 “ . - ..un..¢’~p4.u-- ~~----a ‘ c c . . .. ... .. < - -o oo-n.. I’I‘ .......................r..... . .. . . .... ‘ .. ¢ .... [ ‘ .. . ... . .. . .. . . . . ... . 1 ,-s ‘ .., .... .- ¢.-~ . 1'. - . .. ;>.- ‘. (.- I .. ..... T . , ~ . . . . . : . 1 .,.. v.. .. . V , , . ... . . . .... ‘.__,..., . I . 1‘) ‘A- ,.......--Anu.A , ,,...,._, - ., o . .. T . . 4.-‘o..tu‘ “ l .. ........................ W. .... ........v........ I ‘ l j .. ......... ...... .... ,.- ..- , . . . . . .._ . .l.......... ..... .. . . ... . - .. v. ‘1.) A A ..A..‘.‘.,.....,..,.... a. .-. . .« . ..... .V .. « . . ‘ Iv-ub‘.l0»ltl'v0vo.rooo.to. ... .. .. .. . o- .oo.oo-~.¢..-..-.o ,5oo-.. I ‘ ".' I T ‘ .... ....................‘ .. .. l. l. . . .. T. . . ., c . .. . . ...,... . . ... ’¢ ... .... 0. .~' o... .«aouco. ooaucctoc I n u Ibo ¢ ‘ ’ ...,...‘..,,.,...,.............. . .. .....-..-on...-.......o-..oonnI-...-.o 751 I .~v.-¢.-.-ona-.-..-onoy-qc --...r'~~ . .o: . «c «u o.o.s.¢.‘w:n4¢o { .4—.«.‘..u¢ '0'? - ~wt-‘ r ~ -~ - . .. . -- ...4 o uauac. O . Q . O . . . ‘ b V s . . U . v A . . . . . . I ‘~ ‘AA ‘ V‘) '-_._..._‘.—~._. Table 10 (cont'd.) 1 I E h A T A D l J'SHEEI up .UHGR..... 807 806 J r L q 4 u q u 7n~ 793 Q q 74H 6 7nn h B d u IbA 782 181 76' 209 Table 10 (cont'd.) PrrPARLU IUN FRANCIS N. LJMUV W\ THL biNE>lilFlNGiR LAKES FtthhAL PLANNING BOARD GHvNIH. IN‘> UKNATIUN szTEN 47 FlIlndLH ST. HCLHFsltkv . DATA HAPPIU 14 d LEVLLb H}Tht6f tx1~t“r VALUE) “F ‘ AND 1.2u MEAN = 0.r? 5?. DtVu ‘ Au>ULUIE VALUE KANGE LIPLV!NG TC LAC“ ltVH NlNlMud n.~ fi.p) MAXIMU4 |./n 1.2L] Pt-lLENYAbE uF NIAL MSLILT: VAHJI AI‘PLVIHI. 1r UMH LkVLL 5(.3fi 5’ FRtJULNCV DI>T~‘ .. 'JriHM . .wv .1»: \: ”$419.39; ' ..o 0 .- . . "WI‘ . I-‘AK".. . ... . .. . . . “~J.';L . . . ' lwfl. .v v \ IQ . o <. no no . u ; . . .QNUIW. . . "HM”. In 4 I I Q c Q] I h .4 I . I g I J I. Q t OI O O I. l . .. ' .. -. .. .. . . ..h . .. ... . ... 0: . . u \ x . . o - . I I l I “ a . . u. . .3: l . . ~. . ........ .. ... .. .1“ ‘TL\ .w‘....Lm".nH. ..- .. . .. . . I’k ‘ . 0 “1‘ . . . . .d. 1 . , _. , \ 3 Ci 1 s I A I )1 . . . . ..anJ - . . 1 . n ; u " ill 0 1 O A .. . fi': 1 l . . . . c. .. . ‘ ‘ I. I a s I. I. OI. - I. O O I 'Q l . - C I .. ... III n ..n. .1 ‘ ; - v » n cc «. . o b . . . .. u . .. .... .. ,. . , . . n or . . | . . . .. ... . .- ... .. ... - . ll ‘- . . . . . . n. .- . u .. n n. - .. - . . - o o .a . v0 - ... A I: , . £ . o . . n. . o o .u - a ... - . . - - - . . u .. .. .... u . u . . . . .u . . . - . n o . .. . . .. . A , » . . c . . .. - - . . .. .. ~ ' x n . I. 0 o r o 00 a b I O I . . . ~ . . » o ‘tj .‘. a ' . " Chi . \r -' . u . . . . . ..\¥K‘?C4;§L\c.u?c:ir ~, ..-'!Zu,,. . . . .. , . C. I O ..G 00 fi I A t i I I >. c I I o c o. uDI .- . . .. u- ... .. - u o -c . n . l u . a a .. A . . .. . . . o. o o o. u u . . 9 . l . .. . .. .A 0-4 .. . n. . . . . . . to o. . ... I . n. . ... ‘ . ». . . . . .. . . . . un. -. o ..x 4. 4. . . o v . . . .. ‘ . .n .. u I. a . . . . . . x .. . . . .o ... ‘a . u - n .. « . ,, .‘ .. - . - .. ... . -u ..o u-c S‘L‘L‘... ...-Nu . u .. - . -.- c . v . .‘ . . ..""7.4. ..A‘ '. .. . .. . .. . " v: . . I l .69 l 1 , ‘ In . . .. . , '2 ‘, ... . . . . u n .(K . . , .. 9' . o . v " . . . . . . x . o. u - -‘- . n at ¢ I « u“ ‘C II I l. I u b O - u. ' i D r I C - o I. i I ‘ I Q f ' ' ’ D- I . I n. c. .- . o - . . 1 - .. - 3 v . . . i . V . i . . . . . 4 . i .. on o .‘. “ . . . . .. a . 4 . . . - . , . . I 't o -‘I. . .-..".- . . . . co“a \'c . - > . I 2.52. . . . .. . . . . . .1 . ”5.4 . . . . fill-J I.‘ “.3 . I . i a 4 . a . . . n o a o . o o . - u . a p .o ..4 .. o. . 4. u c , n ,. . ,l---_----_---------__-_._.._-------_---. L . x L‘ s’ I C) l . o I . o . . . ...-rang... kxtanIBSSS xnpyusuwunr :wxmummaca ...-..a-oo .u‘u. .i\~. .k.~3khi.hr b: HEEQMBKK‘BNN Ml“ HORN! 040110“: . . - ~ 0 - . I n . w a a o c a l . 4 a - u a a . o u 1 u o Q ~ I . o o o l o r o - u C b\ .. 4 7 m (I. i" . . O . ~ ... o. . .o'.. ....o . nu... .. . D o u c . u 0 ¢ - . o v n a t u o u o o a . o n . n n a 1 . n 4 o l u - ~ ......u ..v v... .. n.- '..I-.‘.l-. . ... o-\ .. ... .u .. ... .. .. a. .. .. . .- . . ... . . r . .A .a . . . ... .. ‘ .u on. . ..a .. -- ,.... . - . .c _ ‘~'-.‘ (5‘ . . u . \'_‘ o . . . . Fl}. .. ... u ‘. v¢‘ACll I. O 'U ' ! “Li‘s M! .3 ahl law "-Hv VIII.) NIH/C PEEP? CIL°3LM Nani t‘rgfi‘fl FERN. I I L‘lINH. I I i-I'EM'I. . . I -. .‘ huh. I a I ncI .4 . ..» ... .... , . I . - . I . . u . o - I . . . . . . I . . . \ O . . - I I A . n l . . . . 4 I I . . I o . . o Table 11 c - Z 4 . 7‘ f 47 ‘ I n . a . . a , D l I -~ . a o o t . I o c a p l v - . x o o . , n , c - . . c v , u I A b . 4 . v o . ~ . o . I I II . I u . . . I 0 o O I . u I o O A a c a A IIII-v can» ... .I.- l ,rw‘u » .. A. ‘ lit... . . .I . ‘ ~ II~...~. .. Q'Il'quifl' ... n-4--0.1.¢ID .I. u: ... - ... . II. It: ‘or~ 0.4 ... ... . i.fi€....-. $174....I. . . - . . a . I I. u . r . . .. a I I ' n n . .. . . . . o . I I . . o- . a n v I . - 4 4 o . . v u 1 . I I v I . . . c . . a . I . - a 0 I' I o s v - a u n I a o . o o v . I - . l I II > - g o o . . 4 o a o o a I. y I x I J v . l . . r . . . . . o .I . ’ I . . ‘ 4 u . . I . o 0 ~ I I. I Q I . I . o I I I I- . . b b n l a - . . .. - n . . . u - o n . . . . . . . - I . I . . . - I. . . - . . - . . I . I . . 4 I I a a . . . I q . . I . . - . . . . o o - v . . . I n s . ‘.~ I, .3 \ I - 'I 'I . I . I " . 5 . . I - ~ I I - - . . . I . . . . . . o a a I . . r5; .. ' .‘ -. I a .... . .4‘ ..I .. -, .. . . .... . ,. -. .I ... ,. ”...... ..... .... .... . ......... .. .IA . ». \JUQUO‘G- cont'd.) . .LL 1 C-n 43M!.‘&is°fmf< ‘ .1. :‘1 F' -; (5' {3 I . ,, n3: . II \ -.- .-- 1, ..n - I. or. . - I no. .. . - .. . .. . . a u .- ,..4I . II ~ut- ..l 0.; 5n 4 I. I ~ 9: «ca v. I 0. a pg. .. .Io IA‘II‘? .- a . ..2 t. . I . _ I . . . . .«I. I. n - o : av. »I I . . . .I I. .. . ‘I I \J.‘ .-.. . ... -.. I) ". I‘ b I ., .~ , I . . ‘ , i ~ » 4. I. n-nc e .. OI'IL . ...-o. I. 10 con .‘ ltul . - nI- . II nvu » a I . 1"! A . o 4: v . . I .0 b - -u.-- .. o - . .n ..I V .. I .. ... . . . » o I .9 - .v I - , . - I . . . . . I . .I \ n ' a Q . . - I ... . I. ...}.L‘I. ... . . ‘r‘u ”l ..\.~ ..I . .~ . .- ‘.. ‘I ‘. . I . .. .. 4 . ... O. I. . . . .. . l u.:nl ’- . ‘ . ,. ..-... .. ... . -. .... ..‘ n 1 r. ... - u, . .. I I I . I c I ., , - .I - . . .. ... : . .: . o . a- I. w .I § , I "i \ . I ‘I , x I . . . W01 .Ht 7“ 7., {IL )‘x in i l I l I I I l | I I P l R | t I I 1 l I F l I I I I l I I | I I I l l I I I l | I O I I . HH_—HM~H_H—A_H~_——<_—~H— —_.—.._.»—.-._.r—~—..--—-._r—-—.—I—— -—. )ATL Wawutw in 3 L(vrvA 'xn7.L)[_‘_JT€ VI\LLH‘ «13‘;ch .H’JL ‘4] AI-w‘ VAKI‘W“ PERL-.';b_ r T T x 1 , L L '«‘ ll‘ MJ.f4:nU11l. ‘* L II ."\L‘)') Li V‘—L\ , III. ..-0 \Y4\“‘l 3 avo- 213 Table 11 (cont'd.) r r. ‘Id‘ . v I“ H‘r‘n'tw x‘.. NW- {‘1 HM IA! i ilw Q H L I"L , ‘;L A ‘ ,n' " H- 1"- [\L~2.'<:\91i~.‘ ((fii‘} hxaaiikfim MHKH “5'3": CWKJAEE@N Li“: «\ .‘M‘h f" ['n‘fl l \ 4'4. f'I'J11‘y' J HEUILWAL PLANNINU HUAHU arsT»M kn%\L§L&/f 1&5L [Ani3 ~VH11L3L IUrW4MAIIWN Vi .11, Jun ;I. 5'Hiw ‘ 4t “' v H."- > H ,.) :p [L‘n “LK‘H‘. : C'lr ST- : “ g-AK. ‘4 L l ..|_ ,‘ UtV. 214 Table 12: Low Property Tax Revenue Loss, Medium Development Cost, and Medium Aesthetic Index qAP (ITLt PHE FLt~it LJuAT'k 1 3 215 Table 12 (cont'd.) 14H 5.5HLtI :.UATA DEI 1 av-.._-..-___ _____ -..----.....__.._.._._1-,n___-_.7-_-__.._-_--..-..-..-—.---...._.-__.._.._-.. _........-.--....-____-_L_11.--..__..—_...._..-..._..-_..——-----_-_-_--—-. FKFK.... .......fiKEh.1..FK$N . . ... . ..... ......lIfil ...... l - I I I I n- r 4 g‘ I . , .1 c ' . I. l L I I 5 v ‘1 A H * v I v t 'I ' L " I j ‘. l I 1 I I k A H t I 1‘ I I I 5 a (3 I. I I I I I l I I I . -?’ PC! I I l I ...........-~uu-¢a.-o. .......... ..,.\’..'I.I.’Ia’-L‘Im . ;- ~yo.o I I J" .I.... ......n.......~...... DJII- .4. I':$~..Iug%“G-...~ ..,... 130’.) I ......:...-...4............ . 1. A -. .é.<"-%'Ii13a... .1....r.. I u.......LKKIII’I.-.................... 1.......~.. ......BHVJKKUSHUBU“ I L" .......,fEEE........... ........ . 1 . . . ...... .........6PEBNAUG%§6§ 3C7 I ........USSN......................... ....“ ..................!8K889883M&B I 5.00 nan-3Ivli‘"uuooo.y...-......to-.. q V’I" >~ ‘1IIOKmKNOC‘OQJOICQIOUOOICOOD I ‘» ........k§fld.......... .... ...- . .. . . ...&GHG...........1:....... 00% I ........HKhM........,..... ... .. . ... . ....KtKfi.. . . ,.1......... I 1 .................. ....... ..1.. . 1.... ....... ........ ........unda I .. .... ...-..... .... .... . ,. ... 1.... . .............SHNB d”) l ....................... . ..... . . . ........ .....,...‘ ....UKUL I I .. . ...1.........I...... ..wu1fi1 ~ -..¢.... ........... .. .. ........ I I -"' ‘_ ....,........-..............II‘ZI‘CN. Iv ..-¢. v¢.--n.o..o-- 1......-..-oboloroo LIL": I I . 1.... ....-.........o...9a‘|&"\1. ,. .... .. ...... .....h...“ I ‘ .... .. . .. ..... ... ... II . 4 . In”; .... . ........ ....oua‘. I I o .. . ... .o o .. . u . . .. . .-*".‘Is’l.o no .n. o : vuo-ooaou. "II I .... .. ... ........ . ... .. . tn?u....-. . ......... ......... I .. ... ....1....... . ... . ., ...... ................ .hEufi........ I . .... .. .... .... . .. . .. .. . . .6rrr ... . H C l ..I.... . .. ........ .. . . .. . . .... . .... . .6696....v .. I .. . ... ........................ ... ... . ................ ........ l I «c.-.oo.oconaooo~---. -.... ..... -.-. . . ... ........oo. .....uyna. III I Ill-IIOOOIIII'CIIIIOOI’UIOQQOU‘Oa-O c’l... I' rlOQCOOO IOOQIOOOcIOOOOOOIcIo I OI\OIIIIOI.OIIOI....IUOIIII.IOCDIJII"V‘|O,'-vl 0"...COIOOIOOIDODODQDOIOIOUI ‘ I I» ................................. . . .... ............................... 794 I l OI'CI'OIOCOCDI......DIDOI'I...~II6§-.VCO\I‘O IUQCOQ§.OII9.Q.O.....IO....C.I. I vDIUOOIIvDOIOOQQIOCOOIo altublai OI. xllrbh- a CQOQOCIOOgnOCOOCI lIt-CIIIOII I I" non-on:u-ooaogo...oou¢a.onouopnco.a.;..n-c4..¢..uo-oo....vcovuuu-u..--aoullc 79’ I ......... ............... ...... . ... ..... . . ...... ........... 1 IO|OOIOCOICOII OOIOOOIOIancpsIODCIB ‘00. v'l 0' It. 'IIOCOC'UIIDOQOOOIII'. I I I‘ wu-o.nnoo¢oolauonnnuvt~ a.....-s.- . ..u. 41-... . ...-... n.0aa...o.o I" I ................................ .......... .. .... ......... .......... J IOI~GIOIDUODOI....UOIODIOICOIIOc...e-IOOOOI. v‘l-ll...vl.o.o.l§a ..IIOIDOIO I 7 .. ............................ . ... . .....1... . . ... ........... IWV I 1 .......................... ..........~........ ................ ........... [ any:Into-uo-Iunn-ooclooeo h...li°l‘!.‘l’ruslolwle-.-1-~.- ......nnuno oro-It-obh I I (1* oon-locuooocccnacho-on.onacct-oIfidalqooaouon.luo ..oooo-o...on--.-.notuaou-o.o IV”: I ................................EGtWr ... .......... .... ... . . .. ... I L ....flmNJ................... ........ .......1.............................. I ‘ IF' aucaNfiN'x.-ucuu...-.....4....u....~o. . 9a.‘o .-oo-uo. 04va'.-~...-ocaood-0~ {Q} I E ....FQSW...............................1..... 1.......-.. .........,........ I I ........................................NXSJJCIM........U$GM................ I I I 1 .................................... ...ESNOK¢$Y........£JNU................ /HX I .................................... .-.NVKIVJIS..... ..HxWW.. ............. I yfikflflhaé............XNHS....NGAZ... ..... ...................-.uKkk.-...... I 1 muraxxar............exuu....nxmm.. .. .... ...... ........., nut»........ III I r} I ......... .. ... ........ . 1 I .n . u I ll .vuo o o g. I I .................. .... .. ....A. .... . ... . ~143 ..... ........ I ‘s'~":'.‘:.... . ~ .. 'I“3‘I“I... .... .. . . . .-' ’.~;':-‘:u‘a;>t‘-1‘.P . ..NSSE. I Nn-A........1&N$..... .. ..1. ... .-. . ..Lh.rngflkwnnh . ..xaas 3%" ! £153........wmxfl........... . .. .. 1 , . ......nfldnnlfi.fiflt... ...Efi'x I uo-o.uooocoo-...o.oo.a--o.a...a ... . .. 4v .1. ..............ufimukP.i'.I.K........ I Is« ............................... . _. ,1 . . ...... .. Aufihnuss........ 3r“ I ..............o... .......... . ... . .. . . ..... . . .I'IISv-KI~I'\'«O‘~........ I .. ...... ...... ....A. . . . 1 .. ..... l ' .............................. . 1 . .. A... .... .. ... I“! I ..1.,............ ........ .. .. . 1. . .1.. ... ......,.... I ' ........................I... ... . ... 1. ..... ....NKILakhELbBKtAUI I Ix ........ .1.............,. ...1 . 1 . .Hkmuakgmguufitsuu 7n. 1 .. . 1... .. .. . . .... ... .... ..... .... ....l . wh’lr.’;|-4'.-.9)“NN I‘.‘: I ......111 . ...... .1 ... . -I¢J . ‘n33. ... J I I .. . ...‘ . .. 1n - I’Rhl ... .. . I ‘,, ..., . . . ~I“- h“" . I .... ......--.0-- 4... . - .. ’O'v'k". \.. . . I 1 ...... .. .. .. . ... ... ‘.~\fifl It: . . . I . ........,.~. ....o..... ... ~.r’-.('.... . 1 .. .{s‘i"4.. ..... . . . I . . 3&5 . 1, .. .. .f.*\."¢‘.......... . . ... . .. .. . . . .. .... .. . . . . . . ' I .. . .... . .. . . I on o.-.9nc-. on I Iv. -‘ r I .. .. ...... . A . . I). . . .. . I - ..................... . ..«éAl . . . .. ... 1 1. . .... .1. .... . .. . . I .. .1.... .... 1.. - . - ‘ . ........ ..... . . .. .. 1 ‘ I I 1 . , . 216 Table 12 (cont'd.) Any 3,3HEET 1.LATA 5E1 l 1 _________ - ___________________________________ -_-___—-_——- ————————————————————————— -————--—--~-«7-- —————————————————— ——---_-—--_-—._.—‘ 4 M'u lrx,I\4 p—aNIN) IJN". I'J\. INK) 'DI’VIV r \INNJ \ I'\. K;- I.- \A Lu Lu“. ‘wh 0.wa I ‘I w-v A r x UCQ“EE§EEFKE....Efimxkfité. ......kWNm....- .-..a.... .... III ILEGENGEUQMQ....WGGEEJHJ....I...n%Rm.....A........i..... b0? msssmwmaeuwa....Eumzmzws........muuw...............,.... ........Exammsmu........................................uasm................ 500 ........EKKRESKE....................................I..OESOM1....u.......... 806 ........EHKNKDKfi......-.......... ......................MDEK..............H .............................I.............. .... ... ................uw&u 4‘7 vvuliolnloso-uouuansAuloo-voauvo’ ....-.... ‘1'0oo-~~»vv9¢IQO .Cuo Ich‘l‘fionnoo...¢u.. II.“ -. x, I I'lovvcollvlsro-OIIIto-DOUUUI.u.P\?ll';thIo-9Coo-a... .on.4-oc.E-.I\?.-oo«o~.-.qo. I @N‘G otIuI-oIOICIIIOIOIOIIOIOIInto-It‘lolocl-hOO-Jlian \I ......90................ I‘ ~. ~ I I'I cottons-....Ito-clooo-oooI.........c.0000...oovoumGGOI-ooullIto-IOIOIOIIIQIO 7‘)“ ' d I .-..............................................JNEU...........»..3.......“ I warn conuopnlabbotonoucoonoou k ouo-u....o:.ouo..... u-n......c.>o- ...-.....I9011-un ., I - I l' .... nu.o.ovol- ...: q.o.-':(-'.\\'~‘-‘-ao- . .......... r....‘- . u .. -O¢l~ . .a.:.... .... /! I “'4I not-Innonnnlla-.«CIIIOII xv.o-|.-I-0-|I ollenlyn ...o.‘-... curc..a «no-......a I ....-.....ocooocc-ov¢o-..-o to o I-o.o-.. tn ..,- o¢-.-.-1-oo-o .~ «on-o. .no ‘I AhlldlIOIIOIOUI‘OIOIIOCIVOIIOIO-IQIIdgc ..‘—..o ..uuo Juli-I” c I - .‘IJOIOI 1 ['I I l l I I l I I I I I I I I I I I ............................u... .u........, ........ ..................umum I I I I I I [ I | I I I I 1 1 I I I I I [ l I I I I I I I .....‘c... .........-................. u-. o . -. .. .. .4 . . ... I . I . i ...-......... ... ........ ........ ........ .... .. .-. .- .. . . . ... .... I ...............\........ .. SNQI... ......- . .... . . ... .... . ..--.... I .. ... .... ............ ......fifiEK.. .- ..... . 1 ... ,. .. . ......- - Irv I . .. ................. ...xd41 .. . . I . . .. ... . l ......u....-....o ..n’Il-ZN....... - .,» ~.. (.- ..: .'.-._\.u.-- ... .1-‘III-.41. .. I I . .u u - . . . . n. n u- . I'I‘II‘II' .- . . u v s - .. . . . .. . 1)}: . . . . . r .- I-K‘EI‘ . .' ._ '4‘ I .......,...... ......RWUK...... .. (i.........-. Thflm ......1.. .. . rAfifl........ l1 o...4p..-pn-IInIaoo-o-uu-un;-‘§IMKI-o-pcooooo-nooo-‘.¢H‘.\‘a.vlnunu.-oouuau'vv9vwca8¢soo ,4, v v v- I u I- I I o r no 93 u. o- p , pg. :1 .‘Kddd. o I o n . ~ . . - . n» . n n-«I‘I‘KJIJIO a: n n u u a c s 4 . o . u - -4..NU9I“‘. v nu 7': I . I uv o .0- I v n! 9 I v I II -- - u- o u. l-¢C€Lqml on. ...-0 I... no - .-‘:N%:‘fooo 0 on; A ‘7. do - o q¢.§:%l’_4maooi SENGGNKMUUE a I IOOO-DIIIOIIDOIOO'DIIUIOIOOIIIIOOIOIIIOIOIICOII'D-CIDOIIOIIOOOOOVQO ,__,_‘H’._H-—._.H «I ... . v\' I II. ................................................«..... ......I...l1.EEbNKK&NUUUR I‘I _,, I .......................................... .. ... ...1 . . ... wfirjdlidhfidt it'.»I'llélI'DOQOOU‘OCOIUOII-v uvl.‘ ‘4 --l I .14. .0 ’ )0 I, ’ 0'41. .4. b ...... .................. .....,-- .. .1. --- .. . . . 1.. ... I A I '19 I «v.0o-no Inn's-IIDIQ Oct D or I I97 ¢ I ~ u . - . .. .. ... x‘-~‘.‘I1. ‘ . l I . . . I5 I I I 1 ... .... I..........8KKP. .--.. . ..o «. . . -- .. . 95?". . III' I ..-. I ... ... ....-. .... MANN. ... . . . . . g\ . I Dr! llll'o'll_‘ '4'. . O'“I\b I A I | I t C 1 J . ' ‘ I I '0' I II" Clo! v. I‘l‘ A it: I . . . .. ... .... '0 .1. . . . , I . .... . . ... - . .- .. ‘ ‘ . . . ... ..... - 'n.... I _ A .. I ....................mdud....... .. .. .... ..... . ....A ...1. ......... .... I . . I I 7HH ....................k$tk.............1......~-....,......~. .II....1... .. ..... Ina I I II...‘IO)......-IIOIGJGGIOIIICIO‘....Ah‘sl... I-I#IIIwI-“u O)..<.u‘..s...IUDO-. ! IJ" ' ‘.. I ..I.............................. .....1.............,. .. .....h?h....&8333@3u I 1‘ ~ .~.~. ,_ ....I..............'...,.I.. ....... .. . .. n ..... .n. . a...du€§...=kaoe$$hh - I . .._~‘. ‘ ... ....«V‘... ... ............... I. ... . .. . ..... .wb..,.k3§$,¢hp . ... , .p_. ..o-. - . - » . r.V -.- I . ’~ I (“I ...-..u...---..-.-o-~uc.-.-..,9... .... -..... -A.. ..11.A-.o ..~..v‘.n-...... .w I .........................,....... .. . . . ..)..........1 ........ ............ 1 ...... u... .cI-ntII-D.OOIO ..o\v‘II‘la-‘t....v‘vfi-‘I‘s..... --.- ,1 I. . ... .... . . . . , .... A . ........ .........hdn: :éam. .. . . . . . . ..; I '-l 4 ‘4- ‘ ... ......n..o.n....)I’II‘IK.....JI\-.V.‘I.-. _., .... .. ... . . . . . . .. . ... I A .1 DIIIOIIDOOIAIOIIII*2. :To "L7. l).é8 218 Table 13: Low Property Tax Revenue Loss, Medium Development Cost, and High Aesthetic Index MP HTLE A YHE FLtXIh LUCATUK : b 219 Table 13 (cont'd.) HAP OQSHEEI ZoEATA SET 1 -- ..-- -- 0 Lu J‘ H: .b b «b .r OkN «rm: ODJ~N r OmN t—V'ON NU‘N wmm me mmN omN NVIN 8")? 807 ...-aaaaooooo.Iloovoonooll-oooo “Ob 03008868000...00000000000000... OOOOGOGGQOCOOO......OOOOOOCCOOO ......OOOOIOOOCOOIIIOOOOOOIOOOOO 806 ...-......OOBEDDOOOIOI000...... 505 ...IOIOIOOOOQO'GOOOIOOOOOI.I... o O O .....IOIIOCDOIIOOC......OOOIOIICOOOIIII...-II I .IIQ.....IIOBDEUOIIOIIOIOIIIIIIOII..ICCICCIOIIICOOIOU......COOOCOIOCIUOOOOOC C O I O O I C............DDOII......-00......DIUOOOOCUQI 805 63“. OOOOOOOIOOIIQI......OCOOOIOQCCO ......OOQOUOQOOOUI...IIOIOOOOIOIOIOIOOOOCOI. 80" 5k): ODOOOOOIOIOOCOOOOOCOOO0.0.0.... .0.........OCOOOOOIODOOCI......ICOOIIOODOOOO 803 con-0.0 ...-oooooaoooonlloiooo. ...O.......OQOIOOOIIIIOIOIOOI.....I'IOCIICOI 802 IIIOIII 0...... ..Il...IIOII00......OOIOCCICOOO.......OOOI0.000.000....IIIOOCIOOII... 802 [111 ....IOIIOCIIOIOO......OOOOOOOOO I....IOOIOOOOIOOIOOCIOOOIOICI..IIIDIIOIOQOOI 801 ......0.00.0...-OQUDOOCUOOCOCIOCOII......l. 800 1Jr OOOIIIOIOCI ...-....IIICOIDOCO. I o I I.0.0.0...OOOOOOIODI.....OOIQOIOOCOI.D.........O...‘.O...C0.00UO - I 0.0.0.0...................I...’..C....ICIO. C O I IOOIOOOOOOIOOIOOOOOOOIIOOIOOCII canto-too... 7*; at... ...-000.00.00.00... I...IIOOOIOOOOOO......IOIOOOOOCCOCCI....... OICDOI IOOOCCCIOOIIOOOOO ....O.IOOOOIOCOC05.0.0000.........ICIIIIICO 799 a. ......CUIODIOOOOOI. 0.... 00...... ....I.OI....0II.I.........CCOOICCIOCIOIOOIC a II 79H 00.. .00... IOOOOIOOCOOOICIIO ......OOOIIIIOOOIIOOOI..I'II'IIOODIOI 798 O C IOOIICOOOOOIDIOOOI I I0... I I... .00.......0.00..........OOOCCIIOOIOIO - a O o IOOOI‘OIOOOOOOOOO.....OOIOIOIOOOOOOOOOIII... a c a on~olnotoooooaIODOOOOCOOOIIOIOI o u o I .0 .0... ........IIIOIIOIIIIOOIOOIO III-0.0.0....l...-......OII......IOOOIOO... [‘7 OIIUOOIOOIOIOI...!IOOOIIIIIOOODI IOODIOIIIIOOIIIIIDIUICDUIIOIIOOODICII...... 797 out.Oll...IOII...-...IIOOOCOOIOOII.....IIIOOOOIIOIOOOOOOQII. IOIICIOUICII... IIOOOIOOOIOIO.III-IIIODCICOOOOOIIIIIQIIIIOIOOCCI......IOOOC. ......OCIICII. I"? OOOOIOOIOOOOOOOIOUO0.00....OIOOOOOOOIOOOOIIO......IOOOOCOOOC ......OIIOOOOO 796 D...IIOIIIIOOIOOOIOOOIIOC......IIOIOIII......U'I........UIII .....IUOIQOOI. OVOOOCIOOIOOIIDCO......II....IOICOCOOOI......IOIOIOOCOOOCOOO IIOIIODOIOOCID 17)" IOIIOIIIIIODUODOOIIOCIIIOIIOIIOIIII....IOIOIOIOOI......IIII. ...IIOCIICDCO. 7QS IOOOOIIIICDIIIO.............IIOIOOOIIIOOOIUIl.........ll.... ......CDOOOOCD 791. 1" 00...............-..........COIOI.0.........OCOCOCCOCCDDCUOC ......IIIDIIIO ......Ql... ...-.....I....... .0... I...’.'............'. ......OIOCOIDO 7\“ OOIDOIIIOII IO... ......IIIOIIOIOOOOI'. ......IOOOIOII 793 on. IOICIOOIIIOIOOOOCOOD .000ton-Ootlcoloonncdl30.0.0... IO... OOIUIOOOOOIOOO to. ...-0...... IIOIIOIOIOOUIO... OOIIOIIOOOOCIIOIllnno C O O O O O I O C I I O O .I'IDOIICOIIIOIIOICOICO........30.........-............IIUCCOCCOOOIOOIIOO... O I O I O I O I I O IIIOOOOOIIOII... I 142 ...-OIIOIIOIOO......OUUIOIOIOOI III... ...II000'000IOCCCOCCO IIIICIIOIIOOIOO 792 U I o l I . IODIIOOCII..COCIOOCOO.CC I O O O C .....UIIIOOI‘ ......OIII.......O...I°."....IIIII... 7&1 ouonuolnuua-oo-ooulocoIcon-Ono. so...onlocooo.loultonltoo-ouaaaaolooocononoo 791 oucnonoooooooooncoooano-oooooco .o.......o.o.o.........u...l0.l.o.......... IIOIIIIOOOIIIIIOOIICICIOIOCIOOI IIIOCOIOIOIOOIODIO..........OIOOIIIIOIDIIOOI 7’.’ IO... IICOOOIIOIOIOOOO......O.’ C0....C...I.........OOOICOOCICUOIIIOII...... 790 noose-noon...-noouo-nto-uoncocooooooooocacao-o-ooooooooao-oa-zoo-0900......- IHQ IIOIIOIOOOCO0'IIOIDOIOIOOII00"...0000.......IOUOOCQOICCI.......COIOOIUIOOI. 739 OI......lIOOIIOIOOIOOlDIIIIOOOIOOOOOI...-0..........CICOOIICCCIIOOIOI....... {"1 ova-coototOIOOolotuooctioaoobcoooI...COIIIIO'OOUOOIOO.IOCDOOOOOIOOOOOOOOOOIC 788 7”? QIOIIOOOOOOOCIIICIOIOOIIOIOOOIIIDIOOOQ......O.COCO-....I.......DOIOOOUOOOOOI 787 «to.000000.0010.000000000000000IooooooolltloolololooooOOOIOIOIOIOIIOIIOOCOOO 750 00..O.IIIOOOOI.....IIDIQOOIIIOOOIIOOOOIOOIIOIIIOIII......IIC......OOOICOIOOI 786 .0000..-lot-Ia0.00.00.00.0-III-lID-I...0'00...00'ICC-O...-ICC-OIIUIOOOOOODOO ......OIOOQIUOIIIIOOOI.llII.IIOOIOIIIOIOIICOCCOOC...-0............IOIIOII... 7‘1‘) nooooooo-a-tooaooonooouoooooocoo-oootoooo-oooooooooocoononnunoooooououoooo-o 785 00.00IOOOOOOIOIOOOOOIIno...0.0.00.0...-OOOIOOOOOIOIOCOOIOIIOOIQOCIOOUOOOIDI' 75w o-oop-ooo-uoo-sou-oun-oo-annoon-ooo-no-aooooooou-onocI-Iao-cooooooooouoooooo 786 .000...00000.00l00.0I.OOOOIOI'OIOOOOOIIOOOIOIO0"0.00.0000...IOIOOIOOIOIIOIO caustic-IIICOOIO00'...OOIIOOIIOOI...-IDOIOIOOOII.ODll.IOOUOOOOOIOIIOOCIIOOII 703 00...........CIDIIOIOU..I.I...-.....CCIOUICUOCO......COOOOIOO......COOCOOICU 783 .....IIIODOIOCCIOIOIOI0.0.0....00.......0.........OOOOOOI......OCIOCCOOIOOIO OOIOQOOO'OIOCOIOOCIIOIIOIIOIOIOIIIIOOIDCIIOOOIOOIOOOIOOOOOI'OOOOOIOOIOOIIII. 752 OIOOOCIIOICCC.ICOIOOOIOOI......OOIIOIOO...-IllDI.0.0.0.0..OOOIOOIICOIOOIOIOI 782 0"... 0......IIOOIIOOI.-l.....0.0.....IIIIOC....I....C...........OOOUOCI... 751 0.00.00.00.00......OIOOCOIIOI0.00......0......0.0.0.0..........OOOOOOIOIOOOO 781 OOOOIIIIICOOOIIIOICOUCIOCCOOOOIIOIIIOOI0....O..........OOOODQOOIO......‘Q... 750 IIOOICOOOIOOIIQOIOOOCIIOIIOIIOO00......I...0......O......OOOIIIICIOOOO0"... 780 0.0... DID-...00...............-.........IIIIOOOOOOOOOOCI.........OOOOOIOOO. V.» I 3 1‘ uJIN 3‘ I 1‘ b 3‘ 4‘ U! r-‘MHN NU‘N U‘ U! \I‘ —-._.-—-—-.—<-—-—-._q-—-—-.—-—....._.-—M—r—_—-~_—.———H—fl_~_—p—_H..."..._..__.—,_.__._.H,_._.._.._.._.H_H,_ .._._,_.._.._.,_.H._.___M...,l._..—.._.._.._._._.,_._.._.._.._.-—_.._.,_u—,..—_..—.._.._———-._.u—~.—-—n,_.._. ... .... --_—._,_...._——~—_—~—~——————~—H~_~—--—_- ._~—~—~——C--———'——_H-_--~H---——b-I——‘-—F—————I—-———- I—n—D-‘D— I-Iu- O I I I I O i I I I 1 I I I I I I I I I I I I I I I I I I I I I l I I I I I I l I I I l I I I I I I 0 I I l I I l D I I l I I I I I I I I I I i l l I I I I l l l I l I I I I I l | l I I I I I I I O I I I I I O C O I I I | I I I I I I l l I I I I O LNH @—-—H——~——~—_H-———~_—~——q—~—»——-—~—q—~o—p——.—.H_—a._.._._.——.._—._.p—Iu—n‘4..—._.H.—,<.—.o—-——-—~—..—»—4....—.—-<—-—._.-—fi_Hfl AP ("SHEET I'DATA SET 1 ........................................ 8C7 d0!» BC) In? 798 7:38 787 783 782 00.... CAIN fik-Iu O-‘NN NNN ......C. III-.... 00...... .0000... ......U. 00...... 0.0.0... ......OI II...... 0.0.0... 00...... 80...... 0.0.0... .IOIOCQO ......‘C 00...... .0000... ..Oll... 0.0.6... 220 Table 13 (cont'd.) UNIV NN WNN NM NM NUN OWN on.coal00.0.0000000000...'00000000.000.... 00000-0.-ooo-oooooo'oo'...oococoo-oooo'oco cot...Ino......000.00-.....OOIOOOOIQOOa... Clo-0......0................CIOOOOOOOIIOOOOOIOOOOOOIIOIIIOOOO. IODIIIIIOIOCIOOIOOOIOI.OI..0I........IOIIOOCOOOOOI0.0IOOOOOI... IOOOOOOOOODI..........00....0....00......-00......OOIOOOOOIDI. CID...IIIOC.....OOOOIII......ICOOOOOOOOOO......O........‘OC0.0 OIOOOOOOII.00.00.00.00000000000IOOO0‘00.0.00IOI-OOUIIIOIOIG.0. DIODOOCIIIIOIOIOOODOIO..OIOOOOOOCOOOIOO......OIOIIIDDOIOOOOOOO .....OIOOOI00.0.00...I.......O.......I......ICIOOOOIOCCIOIOOI. 0...........OOCIIOCIIIOOIDIIOOOIIDOOII......IOOOOOOCIOOCIOOUI. out...Iooooooo-Icoo-00.00.0000.0.000.000.000.00.000.000.000... 0.8.00.0.........OOOOCOCIOOI...I'D...I......OOOOIOOOOOOOOIOOOO concoc-0.00.000090000..IOU-Olutooooouocvooonooooooooooon-ooooo ..-00.000.-00.000.0-tonnooooooIII-coco...occult-oocoooo-onoooo 0.0....O....0...............OOIOOOCOOOII.I0.0I..IOOOIOOOIOOIII on.ooooon-nocoooooo-utoo-cocooocoto00000.0...coooivcoloooooooo coon-IIOQIIalong-ouuoo-I-Inooooo...Incoconuts-con.-Inna-...... O...IO“'..IIOIOO0.0.0.0....-00.0.0...0.00....IOCOOOOIOIOOOIIOO ....IflnnaiiII...0.........-IIOIIUIOOIIIIOIII-IIIIOIIIOOIIOOIOU on.OooaeunoooovOIOOCII-cloouooooooollu00.000.0-.....llooocoooo 0.0.0.0......OIOODDOOOCOOIOOOOOOOOO......OOOCOIOIOOOOOOOUOO... ought-000.....-ono...oocooooooolocc-Iluacoooucocoon-0.00.0000. on.no.ha.Inc...cocoon-o...o-....on-cloooaoocacounts-ooooI-oaoo OOIOOIIIOOQI...0to...I.00.I00!OIDIOOOOICOOOOOOOOOOOIIOIOOOOOOO ......IOOOI.0000............OOOOOOOOOI......IOIOOOOOOIOOIOOIO. .IOIOIOIOI.I...0.0.0.0000...I.0......00.........IOOIIIOIIIOIOI coco-.10...occ-out...o.00.000-0.0o..-00.00.00.000..-0000000000 oo-ooooooooanooooo-ounloooucnooooo-I.ooooCOOCOOQoooooooaoolooo OOIIOOUI'I.......OOOIIIOOOIOI.0.00....OIIOOOOOOOOOIIIIIDIIOIOO 0000009000.00000.0.0.0000...on.o.be...oocooooonoooooooooolouoo ...-o.no.000000.00...cocoon...to...coo-coo..-coon-0.00.0000... OODOIUOODIOIOOIOOIOCOOIOOOOO0.000.000.000000IOIIOIOOUOOOOOOOOD ooloo.nooooo-ooooo-oocooooooclooooococonut-0.0.0.00.-0000-...- 0.0.0.0....a...oIce-coococo-o.o00.00.000.000.00000000000000.0- 00.0.0.0...O...I.......0.00.00...OIOOIOOOOOOOOIOOOIIOIOI.IO... .IIIOODOODOOII.OillIO.DOOIIOIOUOOOCIIOOOIOOOIIOIOOOOIOIOIOOICI OI.0.0.0...I...IOU...IOOOOOOODIOOOI......OOOOOOOOOOOOO00...... 0......IOIOOOOO...-IIOUIIIII......OIIIIIIICOOOIOIIO0.0.00.0... ......Cl...OI....00....9.........OOOOOCOOOOOUOIOIIIOIOO....IOI coo...I000.000.0000..0......OI...II0.00.0.0.0...IOOOOOOIO0.... cacao-on......-ono...noon...no...000.000-InlooooooqoooIon-coo. coco-.00.......-coco.noboo-cocoon...-cocooonnnooooooo0.000000- 0.00.0.1...00000000000.tootoon...too-000.0...0000000000.0.7000 0.0.0.05..-soooo-ooooc.auto...oo..latooi|o'...ol.00looIto-o... 0.0.0.0....noonnot...o-no.I.onno...clouooooooaoooooouoocoo...- c0000....tout-o.000000.not...ooooon000.000.000.00Ioooooootoon. IO.IIOOIOIOIOOOOOOOOIOI.0....0...-......IDIOIOCOOOOOIO00...... 0.0.0.0....OOOIOIOOOOOOOOOIIOOOI.I.........OOOOOOOOOOODOOIOO'O 00.000-noo-ooo-oooucoclcnocooloooouloot-looooooooooIn-noooovoo coo... ....00.000-.0........CIOOOIIIOOOOOO...IUOIOOCIOOICOOIOO cot-o. can.cocooounoouoooooooooooolcococa-0.00.Olooooaoooooooo 0.0... ......O...‘IO.....O........O..............00..0........ C I . 00......COOCIIO...-......COOOIOIGOO......O..l.l...I.......l.OO ........IIOOOOOOOOIODUOIOOO0.01.0...I.....I.....O......l . ...... .-....lll.......................I.......IDCOOIOOIIOOIII .00.........0...0......00000.I.....I......IO..........I....... OOOOOOCIIOQOOOOOIOOODOOOOOOO0.0000000000CO...OOOOOOIIOIOOOOCO. ......I..................................l.................... III....0.........OOIOIIOIOOOIOD........O.............II....... OOIIII...........O...........O......I.....I............'...... ......I00............OOOIOOCO...O..U.................O........ ..............I........I.......................C....I.....I... .......C.IO..IO..........OOOCIOI.I.O.......I........II........ .........OI......OOOIIOIOOC.'IIOOIICOI......O...............II 00.000-O...0.00....OIIO...IIOOIDOOOOO...IOOODCOOOII.IOOOOOO... 0.0.0000...0.0.0.0...OIOOUOOOIOOOOOIO......I....I.'.'.OOOIOODI III00.............Ol.IOOIOI..........I......O..........I...... ....C...I..II........I............I........C...........'...... 0..0.00....OI.........I'...’...............00.C.......I...I..O ....OOIOIOOOCOO0.0.0.0303...IIOIOOC.000.00.000.009.0.0.00.0... ..I......IOIDOOO..IID...III......I...I.........OOIC..I...I...I .........I..............I.I......0...C..............I.....C... .......0.....I.......O.......I..'..........I.................. 0.........l...’00............O...U.......I........ICII..I..... 0.00.0.0.........0.0.0.....90..........OOOIOOOOO...0.0.0.00... I..........I.........O...‘I....I.O..I......I.................. ......O....OC..I.....IICC..................I......DOOII....... IOIOOIIUIUII..O...........I....0....................l......... OI.I...8.0.0.009....0......I0......O.I......IOCOIOOOOOOOOOOOO. ...OOOIOOOIIOOIOOOOOOOO00......O.....O..IOOOOIOOIOOOIIOOOOO... ......O.I.....C......I............I........................... ......IIIODI..I.....I......II...’........I.........CCI....I..I “INN N \I'Nk. N N (INN Own) "WN NwN u wa Lu DIN NUN w 807 806 805 804. 803 802 801 800 799 798 797 796 795 794 793 792 791 790 789 788 787 786 785 786 783 782 781 .m—~—-~—-----—-—~_——~—n—u—n—u—~——u———ng—-lu-——-Iu—n—-—I—~r—u———-...—I-lu-n—I—n—n—u—n—u—p—U-Iu-au-u—u—n—v—n—a—I—I—H—I—u—~—_—~—-—————_—-~—_~—~. JATA MARPEU IN 2 LEVEL) 221 Table 13 (cont'd.) PREPARED FUR FRANCIS ". UOMOY BY THE GENESEE/FINGEN lAKES kEGICNAL PLANNING BOARD REblUNAL INFURMATION SYSTEM 47 FITlHUGH SI. otThEEk EXTREME VALUES UF r.0 ANU AH))LUTE VALUt kbhdt APPLYING TD EA(H LEVEL MlqlMUfl HA(I%UW PERCENTAGE FKEJJLHCY Ltv:LS 5YMHUL$ FKCQUEWCY rJF T‘IIAL Ah OISTKIEUTIUH LJJ VALch 0 SULLTE I '0. (.b( 5'.3f JF LATA 0.60 1.29 VALUE HANut 5C.90 APPLYINo 1C EACH LEVEL F(lNT VALUE§ IN EACr LtVEL Hlbh VALUES Il...... 888883838 ERBCRHGBG 8808 NGGU REUBGBDGU [83888886 2:1:3i::==:::============2===—==:—=-_-=_.— SOUTH 1.20 MEAN 0.F1 51. DEV. 222 Table 14: Low Preperty Tax Revenue Loss, High Development Cost, and Low Aesthetic Index "I ZICATA SET 607 T 1 CAN |.I K I\. r—éN Pg 1’ n. IAbN 223 Table 14 (cont'd.) Jim .......C ....I.,. ‘I‘I‘v ... (I J" R. D... b 3’.th OON (P'V QUIN Our m o—oU‘N P‘fl’v NU’IN NU‘N O WUIN \fi UIN \JN ‘I OWN WM NUIN C............ 0'0... \1‘ Ln N ...... ...... ...... I0... 807 806 805 80" 803 802 801 799 798 796 795 794. 73‘. 783 782 78I 780 I I I I I I I I I I . —__-~—~_~_—_--~_—~—-—-._.—-——_—-—_~H_—~_—_——_—--.-._._——._-—~——-...~—.—-—_—-~u————~——-——_—~—-——————~—~——-- 224 Table 14 (cont'd.) MAP 7.5HEET I'DATA SET 1 ' I I I I I I I I I I I I I l I I I l I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I i I I I I I I I I I I I I I i I I I I I I I I I I I I I ... DPHN r—‘M mmm N N N N dNKI N ONN OWN w W mun) bum Vin-1N w NWN (Du-IN III...OOOOOIIIIIIIOIIIIIIIIIIIIOIIIIIIIIII......OIIIIIII 5n7 OOIOIOCUIIIIIIIIIIOIIII....0...IIIIIIIIIIIIIIIIIIIIIIIII 807 IIII’IIIIIII..IIIII.II.III...IIIIIIIIIIIIIIII.II..II...I I...IOIIIIII.IIII.........III..II...I......I.....I......I..........II...I... 80° 0Q....I‘IIII00......II...I...IOIIIOIIII...III.I-IIIIIIIIIIIICOIIIIIIIIOII... 806 ....I.OIIIIIIOIIIIIOIIII.IIIIIIIIIIII...IIIOIIII..IIIIIIIIIIIIIII-IIII..IOI.I OIIIOIIIIIIIIIII........III...IIIIIII..III.I.......IIIIIIIIIIIIIIOII.IIIIIIO j‘)5 I...‘.II...IIIIIII.IIIII.I..OIIIIIIIIII...I.IIII......IIIII...-....II.I..II. 805 I.II...’I.I.II..'.I....II......IIII.....'II.I......I...‘......‘I............ ......III.........I.....I......C..............I..'...........O.............. fiIAI‘Q .....UII'...................I.......I...-'I...I.'....'... I...‘......-.-.... 80‘ I...I......I.III...‘..............I...I......I.I....-.......C......I.-...... ..IIIIII.I...II.........l'..l....-lI...‘I.....I...I.............I..I....I..I ‘43} ...n-noo..¢-..o.-.nnooooooon.use...coco-onno.no-ooooooan0......ooognuoo-oooo 803 ......I'..........I................IIII..III..I.....I.............-.I..--.... ..IIIIIIIIIIIOIII..III...I..III.I.I.III..I......III.......I.........I..I.... "Id; ...-..n-uouoo.nun...non-.........-ooo-oooo-IIOIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 802 IIIIIIIII..I...IIIIII......I.I...II..IIIIIII..I............I.......II..I...I IIIIOIIIIIIIO.III.II......I.....I...III...I...‘.........I...........I....... ......IIIIIIIIIIIIII....II..........'.........III.........II..I...‘.I...I..I 801 ....I..II.........I-........'I......I.....'...................‘............. I.IIIIIIIIIIIIIIIIIIIIII.I...I...II..II.........‘.III.........‘I...II....... I...‘...I....'...I.........‘I.....I... 800 I IIIIIQIIIIOIIIIIIIOIIIII.I...IOIII...IIIIIII.IIIIIIII.III.IIIIII-IIIIOIIIIII I .<-—-—.—-——.—a——.——~—~——.—a.~.>——-_.—-r—.—.p-—...—.—-—————_—_—.—MHr—~—H IIIIIIIII-IIIIIIIIIIIOIIIIIIIOIIIIICIIIIIIII-IIIIIIII...O'IIIIOIOOOIIDOIIIIIIIOI 797 -——>—-— I I n I I I I I I I I I I I I I I . I I I I I I I I I I u I I I I I I I I I o I I I I I 0 o I 0 I I I 0 O I I O I O o I I I I I I O I O I I I I I O O I I I I 0 IIIIIIIIIIIIIIIIIICIIIIIOIIIIOOIIIQIIIII-IOOIIIIIIIIIIIIOIIIOOIIIIIIIIIIOIIIIIIO 7C)“ —-—----’—~—'—>—< I I I I I I I I I I o I I I I I I o I I I I I I I I I I o I I I o I I I I c I I I I I o O I I I I I o I I I I I I I I I I I I I I I I I I I I I I I I I I I I Fl'l, III.I.IOOIIICIIIIIIIIIIIIIIIIIIIIIIIIIII.IICIIIIIIIIIIIIIII....-II...IIIIOIIIIII 792 7‘I GIIIIIOIIDIOIIIIIICOO-IIIII-D.C.IIIIIIIIIIIII.IOIIIIIIIII.II......I....IIII.II.I 7ql r’“! III-IIOIIIIIIIIIIIIIIIIIIIIIIOIOOIIOIIIIIIIIIIIo.IIIIIIIIOIIIIIIOOIIIIIIIIIIIIII 7‘39 7‘77 IIIOIOOII.III...000.00.!IOIOII'IOIIIII'COOIIIIOIOI' IIIOOOIIIOIIIIIIIIIIIIIIIIII 787 OIIOIIIIIIIIIIIIIIIIIIIIIIII 786 T’C‘W III-..OIICOIIOCOI.0.0050III.IO...5.0.8...UIIOIIOOIIIOIIOIIOCI .lIIIIOOOIO... 785 O O I .‘ICIIIUIIIOOOOII'III...It...IIIOIIIOIIIIIIIIIIIOIIIIIIIIIIIIQOOIIIICIIIIIIIIIII I I FF“ pnnacI-uocoo-II-Icon-III-IIIII...IIIIIIQIIIIIIIIIIIIIII00.000.IIIIIIIIIIIIIIIIII 784 1 7‘4: lollO.IIOOIOIIIIIIIOOIIIIIIIIIIOIIIIIICIOU-II...IIOIIICIOOIO‘COIIOIIIIICIIOIIII. 782 ...........I.'........IIIIIIIIQOOIIIIIIIIIIIIOIIIIIIIII...II..III....0.I..'....Q ........IooonoaoIIIIIIIIIIIIo-noannnoooInInoc-cu..-...-anooooolooooooo...no.9... 1 181 «L-l ....g...'..tuto.....IIIOIIIDIIIIICOIIIICIOIIIOIICOIII IIIIII III-noooIoIInIOIIIo.. Y 00.000.000.00...IOIIIIOOIII.-III'II'IIIIIIIIUIIOIIUIVOIGIOIOOOOI-ODIIIOIIIIOIIOC OCOIOIIIOOIIIOIIOOII'OOO0.0.0....IIIIl'IIIIlO..UIIOIOICDOOIIOOVOOCIIOOIOOOOIIIOO .OIIDIOIIIIOCIIIIOI'IIIIIOIIOIOOIIII'II...-IIIIIIIIIIIIIIOIIODIIOOOIOOIOOO'IOCIO 780 IIIIIIIIOIIOIIIIIIIIIIIIIIIOIIIIIIIIIIIIIOOIIIIIIIIIIIOIOIIIIIIIII c" 4 L Q L S 2 . 2 2 3 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 J 2 2 2 2 3 3 3 3 3 3 3 3 3 9 C l 2 3 ‘w c 7 5 ‘3 I" I 2 3 ‘- : e 7 8 Hu—«HHM—H—H—qHfi—flfifi I I I I n I I I n I I c I I .~_——_——~H—h—HHHH——HM—H—H——~————_-—HHHmfl—H—o——n—u—.—u—_—»—an~——.._.--._——-———au—-—v-——mu—c—H———c~m~u—~I-~H—~m~—~mH——~mn----- )ATA MADPEU IT-J AUSILUTE VALUE MINIMUM mnleUM QEKLVVtNTQuL PM“ 225 Table 14 (cont'd.) PREpARED FCP FRANCIS N. DUMUY ”Y TFE GENtStt/FlNuER LAKES REGIONAL PLANNINL BOARD REGIONAL INFORMATIUN SYSTEM 47 FITZHUbH ST. SOUTH HUCHESTEko N.Y. Z LtvLLS PETntEA [XIFEME VALUES OF 0.) AND 1.20 MEAN ; 0.0 ST. DEV. = 0.0 RANut APLLYINL TC EACH LEVEL (.0 (.60 0.60 1.20 TLTAL AUSQLLIL VALUF hANbE APPLYINU TU EACH LEVEL S(.CC SC.00 FKCJJfihpY b15TKIHUTIFR IF DATA FLINI VALUES IN EACH LEVEL LLd VALuéb Hlbh VALUES LEVELS C l 2 3 I I I I. II 0 O soosuaaae ......... SEIKIIIDI SVMoULS .... .... BEBE suns FPEQUEVCY 226 Table 15: Low Property Tax Revenue Loss, High Development Cost, and Medium Aesthetic Index '71AV HT! t 227 Table 15 (cont'd.) a---------_-_--_-----_-------------_----_---—..----------------------------_._---------_-...-------------_--_---------_.. ...... ------I b H-bru NJ‘A: wJ‘N b fr“ 1‘ t J‘ :‘N blw \J'IN UWN «wN N u‘N JIM LnN me \I‘ 0‘ N C) O O .... l\ U 9 U" 0 I I I I I I 9 C' I I I I I 5‘37 807 I L506 IIIIIIIIIIOIII.IIIIIOIIt...IOIICIIOOIOOOOIQOIOOOOOOOIIOOOIIIIII. 8C6 505 IIIIIII-'1'...I.III...III...II.....IOOOQOICOIII.IIOOIOOOIOIOI.IODIIIIOIOOOIO 805 ”2“ IIIIIIIIIIIIIIIIIIIOIIOIIIIIIIIIIIIOIIIIIIIIOOOOOIIIIDOIOOOIDO'COOIIOIIOODI. 80‘. ”I05 IIIIIII.III-IIIIIIIIIIIOIIII'IIIIIIII'IIIIIOIIIIIIIIIIIIIIIIIIIIIIII'IIIIIII 803 .—<.—.-—<_.—-.l_—._.._—<_..—-—~.7—,...—H._—.—p—..fi— I o I I I I I I I 0 I Q I I I I I I I I I I ' I I I I I I O O O I C O I O I I I I I I D I I O O I O I O I U D I I C I I I I O I O I O I I I O I 0 O I O /a'; II-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIOIIIIIIIIIIIIIII-I 780 N \J N‘ N r I \ui‘r‘, C t (.7er Vb'v 0 £1?“ ”DJrl U" ww ! kafmy U‘ ~4er w I r—c J "h Nx‘r‘u o O . n I . o u C . I I I I I O . l u I I I o I D O I I U I y I C I I . O I I I O u I I I I U I I u ... I I I o I I I I O I I a I I I I D I O I I I I I I I .m-___-_~__-—__-—~_—_-~u—I—.—.—-—.-—-—._.-—_—..—-—-—.-—<-—-u—-—a.—.—>—-——n-—.——-—-——4—-—¢——>—<—-I—-—Iu—-—Ip—u-n—Iu—u—-—II—~———n——u—~—~—~—H~————~——~———~—n~ L-W HAP H.5HEET IoCATA SET 15 (cent'd.) A I I I I I I I a I I I l I I I I a I I I I I l I I I I I l I I I I I I l I I I I I I I I I I I I I l I I I I i I I l I I I I l I I I I I I I I I I I l I I I I I O I I l I I I I I I I I I I I I l I I I I l I I l I I l t I I I I I I I I O I I I I I I I I wt -. 4!} ,5 10M __ __<___‘__‘_H,_,_.__H.___,_.—-_._._.._—_.».._._.,_._....-—._-—-__.._—_,_..._._.-_>~—-—<__-—-,_—“HHfl—fiHH—qH———~——*~——~fi—fl .fifil—M_a—‘..fi .->-.»——.>—~—-.—.-— ... {I ~" I‘- OWN) N N "J A) l'v N KAN?) N N JINI‘L NN' (3'de «INN «A h) h) N (I h, "J VDNN N w NWN typify ‘A-JU 'v cwm um w 'v ou-m h w N ~4'AN I) I...) 'w 807 806 805 806 802 801 800 79C) 798 797 795 701 790 7‘3‘3 787 736 785 78¢. . —-~_—~—~fl—-H---~—-—-~—~H~—HHH———H_H-——“—-”H-—‘-—~——*~—-~—-H————H_——-‘H—~———~_——-_—————————H-— u—a.‘ 229 Table 15 (cont'd.) PREPARED FCR FRANCIS “. D'JMCV I‘Y TI‘E bENEScE/FIN’btR LimES Riolt‘IAL OLANNIM} IIOARD REGIC‘NAL INFORMATIUN SYSTE” 47 FITI4UUH ST. SOUTH RJCHESTER. \I.V. )ATA U'tw'PEO II 2 LU/cLb LLH-EEK tXTkEME VALUES IF 0.0 AIM; 1.20 HEAT: 2 MC SI. piv. : C,’} AB‘S‘LUIL‘ VALIJL (AND;- AQFLYINI; IL EA(H LEVEL "1‘1,"qu (or (..(‘C' P‘A(I“UM L 00') 1020 PER-*"TJ'.IE -r TQYJL ALSVLUTE VALUE FANUI Ar’F‘LYI‘I.) TI) {ALH LEVtL H A‘ C‘P.CC ‘1' I ¢r\14011.\ ;F JAIL PCINT VALUt) IN tALH LEVEL LGd VALdtS Hluh VALUES LEVtL\ C I P 3 ......... waamxaaa ”...... MOUSQMOIQIG >HIUL5 .... 8R8! 8G8! “881080“: ......... councilman qulr'dr 230 Table 16: Low Property Tax Revenue Loss, High Development Cost, and High Aesthetic Index map IITLE LHH ‘IAP I I I I l I I I I I I l I I I I I I I I l ...—V 91 SHEET 2.!)AIA bET c...——-—————-—_...———_.———.—--.._._—.-—.._-._.-.—-_—.—.-———‘_...———-——.—_ I I\ \. «L‘N‘ ,4 ‘1 .8'3 .8“ III III III 0.. III III III III III III III III III Old III III I.- III III III III III III III III III III III III III III III III III III II- III III III III III III III III III III III III II. III III III III III III .01 .II III II- II. III II. ..I III III III .II III III III III Cl. III III III III II- 1" I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I l I o I I I I I O O l D I I I I I I I I I I I I I I I I I I I I I 0 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I o I I I I I I I I I I I I I I I I I I I o I I I I I I I I ‘ I I I I I I I I I O I I I o I I I I d I I I I I I I I . . I v x I I I I I l I I I I I I I I I I I I . I I I I I I I I I I I I I I I I I I I I 0 I I I I I I I I I v a I c I \ybm Table 16 (cont'd. III I III I I III III I III I III I II. I I II I I II I II I I I I I I I I I I I I I I I I I I III I III I III I III I III I I II I O I O I I I I I I I I I I I I I I II I I I I I I I I I I I I I III I I I I I I II I I II I I I I I I I o I I I I I I I I I I I I I I II I I I ' I b O O I I I I I I I I I rm sII‘N 1 1‘ I‘x.’ DJ I'K.‘ \fi U” VIN. ‘J‘UNJ 807 800 805 ROI. I303 I I £- O F... _..__HF‘_~._.~.—..._.MM——__~———I~————I-uq——p-Iu-II-II—II—o—I——I-‘———-I—~_I-II—l—I——h—-—I~_~——~— ._.._H._._.H,_. ._flH-H~F~FHfiH_ 232 Table 16 (cqnt'd.) any 9.3HEtT I.LuIA Sc! 1 fl ......................................... ——_—--_----—-—--——_-_—-—_-------—---_---———-_-——-—-—--————————-—------——----—--—---—---—. I I I I I I I 2 2 2 2 Z Z 2 2 2 2 2 2 2 2 Z Z 3 4 Z 2 I I I 2 2 2 2 2 Z 2 2 2 2 3 3 3 3 3 3 3 3 3 I I 4 C I 2 3 l. 5 o 7 U 9 C I 2 3 t. S o 7 8 l I I I I I I I .....-..............o................................... I l ‘)7 IIIII-I'IIICI.......I...O.I....CIII.I'ICU...3.0'I......O 807 I I .......... .............................................. I I .I......OCIOIUCICII...I.C......‘ICIOIIUIIII..IOC...I..C.O.......IUIDICOICCIO l I \I'W IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 806 I I ............................................................................ I I ..... ....... ..... ........ ..... ....... ........ ...... ...-... ....... ...... ..... l I “I" IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIII 805 I I ............OCIIIOCCDIOCIII...III-I..IDIICIIIOOOO.........OIOCUIUOOOOOCOI... I I ..IIIIOIOOIDIIOUIIIICI-C.........-....I.....O...'...............'.0.I.C..... I I ‘ I ..........-.....................-............-......u....................... ROW I [ '.-.'......'.'I......'.‘.....'....'..........I...‘....'.’...‘.C....l........ ‘ I COIUIIDOCUI.......UIUOIOCUOCOOCIODIIn......-ODOIOCUOIOOOOOOIO...Q.....II.." I I ‘ . IIIIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII.IIIIIIIIIIIIII-IIoII-IIIIIIII H03 I l OIIDCIIOOOIIIIIIIOIIIO...I.........IOIIUD....I.....O.O.C......OOCOOIIOO'IIO. I I IIIOOCOICCIQCOIOOIUUOI....‘OO0.0.........‘U..I.OCI.-...I........I.C...'...II I I ' “ IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 802 I 1 ............................................................................ I [ ....IDOCCII......OOICCIOO......‘I...IC.IIO..I.O’......OQOUIl'...'..I..IOIOCC l I ‘I IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIIIIIII 801 l I D.D.CCIOIIOIOIOICOII..I...I...0...........ll.......OUICCOICOOOII...".O....I I I .. .... .... .... .... ... .... .... ... .... .... .00. .... .... .... .... ... ..... ...I. ... I I .......................u...............................--.-..o.............. 800 I I ............................................................................ I I IIIOIIIOII'UOIIOI...'O'UQICOO..'IOO......‘C...I'.........I....li...l......'. l I I," III-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 7QQ I I ......................-..................................................... I I ................................................................................ I l I)‘ II...‘,'I..Q'O..........O...‘II.........U..........C..........-........'........ ’96 I I .....................................-.............-........................II.. I I .................................................................I.............. I I 7'; ..............o......-....I...-II.......I..........................IIII.....IIII 797 I I .................................o...........u..............................-... I l IIOIOOIIOICIOOOOVIIICOIIII.IIIICIUIOVI.I......'..IIOP..QCOO ......‘DOO‘ICCIOQIDC I I . ................................................................................ 796 I I ................................................................................ I .............................................-.................................. I I * ................................................................................ 193 l I .............................................o.................................. I I ...................-..........-.-..................-............................ I I "4 .........................-............................................--...-.... 7Q~ I I IIIIIII...IIIIIIIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII I I ...........................................................-.................... I I I. .... ...... ...... ...-.... ...-....- ........ ......I ....... ....... .....I. ...-.... ... 793 I I DIDCIC.....ICIIIIIIICIOIDU....0......-......IIOIII..0....CI...I...IO...'I.O..O.. I I ...........................................................-......o............. I I ................................................................................ 792 I I .... ..... .... .... ...... ..... ....I ..... ... ..... ..... .... ...... .... ...... ...-I ... I I ................................................................................ I I H‘1 .......... .............. ......I............... .............. .................... 79] I I ........................-..................-I....--...-......................-.. I I ................o.......................I...............-....................... I I iv ..........................................................-..................... 790 I I ................................................................................ I : I'D!I.IIIIOIIIIDOIODIUOIOUDDODIVOOOII'IOIOIIO.IOV.IOOOQOIOIOIICIOOIDIODIIICOODOI [ I I . .......................................-.................................o....-. 759 I I ........-....................................................................... I r ......I......................................................................... I I l ............................................-..............................-..-. 7H8 I I ................................................................................ I l {OOIIOOCOOCOCOOIC.QOIQUCQC‘......ID..II.10......ODCJOIOOGD‘OIOO.IIOIOOCOOOQICUIO l I I . ................... .............................. ........ ......... ......... 7A7 [ I IIIIICIDOOOIII...!III-IOIOOOCOII'IIOOI'IOO'QOOI.l'00III-IOIOIOOOIOQOIOIOO.OIOOOO l I I l .....IIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIII.I...IIIIIIIIIIIIIIII 756 l I ...-IIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIcIII-IIIII.III IOIIIVOIO‘O'IOIOICO I I ............................................................. ................. I I .IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIIIIIIIIIIIII I I IIIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIII IIIIO|IOIIIIOOIIIOOODIOQIIIIOOOCIIOIIOOOOO. ! I I .JQIII.IIOIOIOIOIIIQOIIOOOIUI.0......IOOIIO-IIIOICUCOIICI...-IIOOICCICOOICOOOIOO 7"“ l I .IIIIIIIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII..I.I.IIIIII.I-IIIIIIII I I ..II.IIIIII..IIIIIIIIIIIIIIIII-IIIIIIIIIIIIII-III-IIIII-IIIIIIIIIIIIIIIIIIIIIIII t I II I-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 753 I 1 ................................................................................ I I .............IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII. I , ..........o-..........u...oo.o.o....-uo...-.........................-o..oo¢...o. 732 I I ...........................................................-.................... x I IIIIIIIIIIIIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII.IIIIIIIIIIIIIIIII. I | «'“‘I IIIIIIIIIIOOIIOIIICOIDII......OII...-I.OIOOIIIOIOII'IIIIQCO‘IIIUIDIOODOOOOOOOOOI 781 l I ...........o.. ...-...o-oIIIII-oo. .........ou--¢.o..........-I. ......Io.......... I E IIIIOOQODIIOI.......COODIIIOOIOO.00......OOOIOCOOOIIIIOOIOOIOOOOOOOIOOIIO'OOIIO. l I 7‘1 ...‘.......Q.QIQQDIOIOIOIQI‘OOIIIIOIIOIOIOGIIIOOOIOIIOIOIOCIIIIOOI'COIOIOOOIOOII 780 I l . .............................................................,................ I I I 1 I I I I f I z t L 2 L J . 3 . . J . ( L . ‘ I . I _ . 2 L 3 I C P J ‘ I 3 3 I J 3 s 5 x I ‘ I I ¢ .‘ - ‘ b 7 “ ‘1' C I . J ‘ a c I I I I I I I I I a 777777777777777 - ------ ~~--v--w-*———v--~»------~--‘**'----"*"—'IIA-**"'I~"-**"* , *7 77777 »-» ------------------- -0 233 Table 16 (cont'd.) VHLPAHrU run IRAHLIS M, mummy MY IhI IJEIIIVEIf/I'I'a'JEI“ LAP‘LS HI:I3II_NAI PIAHNIHI) HDAHI‘ kIIJILJuAL 1 IrahquIIIIIN 5Y4)IrM «I FITZHU(H 5T. MHHH KUIVHESTLN' N.Y. JIIA nngLu In g LIVLLD ”FIntEt thIFHf VALWIS r 0.? ANN I.zi MEAN : D.Cf ST. Utv. = 0.03 AHXHJWfi VALIL‘mW.w h‘VlVanIh IAN-IgVLL Mlu HWW 3f r.b5 MAIIMHI C.u\ .2“ “t’r—IfimIAUL' .r I‘IIM, AIM» LIIr VIII]? I‘AINMI AI’PIVIIII. II Lv'IllI LI‘JII “.{L ‘WJW FH*,Jtu'v HiyldlnuTILn I LAIA LIIhT vALUt) In LnIr LL :L Lu“ VAIUES HIDH VALutS ......... tcsmzmuus 314\HI\ .... .... mums mama ......... RWMDuEUEC ......... Easuneuae If9> I 234 Table 17: Medium Property Tax Revenue Loss, Low Development Cost, and Low Aesthetic Index 1'1: FLtaln LULATHR : 1') Table 17 cont'd. FT L r~.1 I w J I I J' _r‘ ..- C \7- l\.1 J 1.»-.......A-o...-yo».u;-ou-u..----¢.-..........1n~~uc¢.o..-.a.~.. ‘ 1 1 .o‘uivvu1-ovn¢--o.-..u.'~...oanucn-u.~.-ou~v 1...,1-..- o- ... -.q-.o..-. 1......oo‘c.oonu...-0.00.41scan...¢s.n.-.o.n1vn 11.1- .Ivaltwvh'l-OIIOQII‘DIIOOICICOI¢IIA1l .o-co‘.uo...... .1.c---.v 1.. otlivoa ‘ .. .n-..nocaonoou n. .....o... o... ... - no 0...... 1" no. - -.--. . n 0.. ... ...-on. ”l1“ vcso .1 volc'. .... ..u-ooou--o - a-o .1... . - ...-u .o.. n. .. .... . .. .u - .. . .~0.. .1 o. .. 1 .. I... c a. 1 ... .......-..-1 ...s- ... .. on ... 1...... . .. .1. o. no. 1 H1 v U-t- ... not IAoteo....o-ooooc-‘o»ocabaopu ...-o'toc- o-ooc .. u . .1 - .01.. In: OIIIII J v. » I wcv . I. t. 1. eon-urn. nan .- a... n - 1.1- u n e . nu: no: a. I... o an. O. . .4. 1O 0.. .n I. , ‘1 - . a: I... .. u- a. nu - II! o v- on o... lib. 1. ... Ol~v coo u. o 1 ...-an. .5... . ... ... vet-II - v . u v: score: I. III. 3... on... .... .000 . 1 . 1 a. cg... . .. A... . . 1.. ..1. 1 .1 n . . s . no. ».o ,L 1 n. I. nun... [Cilia-10llifllllt -..- ...-.1 ......n no - n.1,.- .....u...u.....n.‘o.o. ‘1 ...... WW. nr‘l .1'IOIpICUIIDIID".‘"".O.."‘DQ-U O‘Ilicbl IOI~I.VOI‘10’ hI-- 5- ‘¢IO"- ‘ OI’II...?UIIOI...."U..".I'.‘.')O'OCD'DNO .- D vl Q. 1 v ...-I. (v. 0" ‘ I.ain’t-{l-COOlull-AIIOIIICOOOIIIOA‘DlnotnI-Q-Iflv00": IOCI'..IV.vI.IlII.D. (In.......IUIDOOlilo-IOOIOOIIOO-OOO-OO-III-010!..l'OODOOUVIIDII’vaDDOnQQD-IO __HH_flHH__HFHHHH__..._...-_._..—._»o._....._-_..—-—.—-—_.—..—~.—-—-——~...»—._—..-—-—H—nw—p—‘HH-‘—-———-_—>—cp——-4———_—————_—_—_—~——_ 1 If. 1 ............... 4V 1 1;on-eo-n...Ito.uooooonco-.0vo-o.ntoo-ocoo.-...- .o:.-.uonua-o. -. ataoIIC- bo-s-tsloooooclovcncouonoo-Iv-OUclot-v~~O-c-ou .1 o.......-........ o ......o 1 it.‘QOODDIOOODI’CODOIIOOOOltdcoillldoolcoivbolltvt'C-oph-uon.» .......va..yo 1“" 1 1 is.-IIII‘OICIIIOllIto-OI’O.Ioooooloulo-IIC~QQ- --..........-... . ,...¢;’... .o>.-..--o.onuuucon-no-uoa...........au.»-....-.1-c- ........-o~. ..1...1-.1-¢....1...u¢. n.r...ooo.--.uouuo.oo-uooono...opoao-onuaopcaoun~190-1.. . ...111...-..0..-- I...o¢roonoooovaccoooo~o-Iboucaounuuou.ac0.-~41-~v.v.-..-..1.- . - --oao.-. ‘ . our.J-IloooconoaIC-Iutbonnahoulollllulcu-I-bIIII-navtv--| v-.-1.¢1..1vvnno u-v....o..-.n-ouo-o.o-o.......o.ncuunn-n...<.q-v-q-no-..-oono-.‘o - ---n‘--- ..................1...................1... 11....... . 11 o-..--..‘...oru.‘uv...-cvnuva---c1...»......c. . .... ...... - . ... ... . ..,. ..........u u......... .1. .11..oo.- ~. . ....1 . .... 1. ‘1 ......t-noooooolozueo 1.1.....1....1.............- 1 ... 1.1 ~ . . ... o “ 11o...‘.---.-no...o..o.:-..a. 1.....1‘ «......11......1 .. a.-... . 1 ..... n..o-o.v.-...-.-oco-.r..~u.o----oo.~.po-.-' . . u-~.. -. . . ..1...1 ‘ . ...-.uu.. ... so....-nau..n1...-..o.-...-.-.. ... .... .... ....1..... 1‘1 ..o-vono....1......1.-...-.....co-v-no-aoonoone. ........1......-. -.-- ... v...cans-.auvoe-co-uncu¢.-oo.q,.1.... .... y:.-~...-..1 .. - ... .. ... Inn v.v10..ycloclollIvvottncoucooI-u'cno-voOo-uo-l.~v u-ew-Qr-o. .1... .. . . . .-..r..--.-o..o.a---u<-.-1--....... ...ge...... .. .. . . . .,, .. _. ,.1............-.......-... ..~ . . .. 9.. .1 1 . .1 . .. 1.1.4... o, 1.... 1... ....11 ..1..... ... ... . 11 . 1 .1 - . 1 1 .......-......oaunoc.-.........o.;oo.oun-«u .;..1.»1-s.-.. .........1........ .......-.....aou-nt..o¢as-1uc-.-.-oo....o.u.-.1.o .....1.... . . ,... ....... 7‘10 pa..l~no.4caDUI.cotvIl'ultflocnytln.ovv.Coc‘pooolvo.-‘.....1. . .....1»..‘.... r ...oo-pup-o .not~los1~v.1qo.v.-.ou ..., .u - o c- ~-. . . . 1 ... 1. ...-....<.-oou..~.o...-.........o.-.--.-.-..o ......1. 1 ....-..1... 1.5 1 a......-~.....4o...nc.....c... .... .. ........ .... .... ...,. , .. ,.......;.uuo.-pgoo..acoo.-.4..—. .. . .... ....... -.... ..11. ...-... ...............nyo...c..........1.1.1.1... . n... ......1. , . 1....1.1 u. ‘ 11“ 1 1 ......apu-n...1....uou-ono....1. ......ou.1 .....1...-. .. . . . . .. .. . 9o-ooaooo‘.1..‘-.-p.1.1<.1-.a..-..-. ...........1 1.... n -. ... . o .- , v 1 1......oo..co¢a-.u..¢-......... ...! o...a-... ........-.., . 1. 1 1 ...-............o...-.....1..--.........‘.. .... . . .. 1. ..... 5 l I 1 .1.no.--o.....o-oo-aeuo..........-- .1 . .1 1 ... . , 1 1 ...-q..:oocoooo-.a..u1..~.....oo..... .CI‘D'.I'~I- -~- 1 .- --.- l ” I .~on--..1........c.o........ .11... 1 «. -.. 1 1~ . ....1;,. -.--coouo.o.ouo--on........111- ......1- H... , ~ ....-. I ................................. ........ . .. 11 . _ ... I _ OBI.cfitOIDDI-IOIOOO-bloulb-IDII-~y1uya1.01.... -- . . .. . .. 1‘1 l .. .. .. 111 I 11cv..vo-.-..vu-.-.....~.o...-.. .... . .. 1. 1‘ ....,.....,.,......... 11...... . . . 1. I 1 I 1 ‘ 1 I . 1 < ~ - 4 ‘ 1 l . v 1 1 1 v 1 .--,1, . 1 . 1 - 1 - - -.__v—-‘-~. Am) 11‘1311EET 11 I I I i [ l l l l I I ”11119 1 R1|\J 1‘) 8 II.‘ IIII III. III. III- 0... III. 0... IIII I I I I I I 4 I I I I I I I o I v I I I L I» F\.' '\.If\ P\.1 VI Cl'. (‘- |'\J m I I I I I l I I I I I I I I I I I o I I - I . I I I I I I I I OI O O I I v I b I I I I I I I I I I I I I I l I I I o I I I I I I I1 e I . I I . - I . . I . 1 I I I a I l . I D . I I . - I . . 1 . I 1 1 I . . v G . . I 1 I . I Table 17 (cont'd. -..—-...._._-_.....-.._1.....—._--_-‘---..__---_-_-—------_--—-—_—“--c-t I I I 1 . .1 I I I I I I . I I . I I . : I I . I I I I I I I . A I 1 . I I I o I I I I I I l . I r I I I D I I I I I I I I I . l I I I I . 1 I I I I I . I I I . I I - I I O I I I. Ia..4..1¢ )II.IIIuI-IIIIIIII III... II. III .11....114 II ..I. I‘Dv-ll:6ltn«ldl . ~.I-. I191. IIIt-.-IIII....I....II. I|IIIII VQO‘OIIOUI...~-l ...»...IIavoIoI Irv-IIIIII-III .Ia..I-o-.I¢.II III-.1-IIIIIIIIIIIIII.IIIIIIOIII DUIODIIIIIIOO...II. I V’IIIIOIOD 'IIIII1III.IIIIII-IIIIIIIIIIIII .II-Illllltol. I-IIII .I- II... ..II. II IQOIIIIOJIIOEIIIIOIIOD .-..II IOIIOCO .IIIIII IIDAIO-IIU IIIIIIIIIIIII¢.III«-II-IIIIIIIII I-III-I .III I.I»I.--I...1I.III-I I.III III...IIII.I1I¢I .I-1IIII I. u I o 1. I I 4 - I I . I v - v . - v I I I v o I I I I I . . . I I I . I I I a I I I a I - - I I I I I I a I I I I O I 1 I 1 9 e I I 1 1 h I 4 I 1 I . I I 1 I . ‘ I I 4 I- . A I - I I 1 I1 I I I Q I 1 4 1 . I b I I I I I I I . i . . I I . .1 e . I . 1 ~ I . . I I 1 I I I I I . . a h . I I I I I I o _ I I I h I I . I I I I I I I I I I I I . 1 1 I I 9 v I I r 1 . . 1 . r . 4 . . 1. . I I l I I I I I I I I I I I I I A . - 1 1 < u n I ~ . 1 I I I I . I 1 O . I I I O I - . u . I u 1 I I A I v 1 I I I I I I c I I I - 1 I I I I I . I . I x I I . I I I I a 1 I . I I I I . - I I I . I I u u I I I I I I I I w o I I I r I - I . 6 I I I l . . I - I I I I . . I I I I I . I I o I . - I I I I o . ‘ I I . I - I C I o I I I I I I I V I - I I 1. . I . I I - . I I v I I I I I I I I I I I I - I I I I I o - I 4 I I I I I I I I \ I o I I I I oIIIIqIIIIaIIIoI_cI- -oIII0IIII I. .1 --.1- l... u'l'.b..do IDA-I DIOOOOVOI‘DIDOI'O'n’CGIIQ I I.-I-I.III l' -I.‘.II IIII. In... -. A . IAIII.‘ luavuo-Io- .... ..... . . I.I ' - II1I .. 1.1 1. « - I1 1 ... I. a-I' I. a. . . .. 1.. I‘ll, ‘O‘V' . .1 I'Ollltil'CV 1-4 1... .11.. . - Ill.-1hb ...... .. 1 II... . .1. .1 l .1. 1. . .1. .-.. I 11 a. . . .I I... - A. 1-- 1 . I .« ..., - u U . ._ .. . U . 4 .. 1 .. . .. . . In... - 1 . . : 4 - u. . 1. .1 . I ..«111. 0.. . _< I, 1.. . . I- ‘I’§l 1 I - I .n.. . .- o1 ‘ . .. . . . -. ... I .1. v ( c .. -~- I.-. I I . - I . I 1 , . . , . . . . . . I . - 1 I - 1 l . , . . . 1 .. . .. , . I < . . . 1 ".N 607 do ‘1 ‘H‘. w r402 r301 v1 f“! 1“er Pia ,. ... .__.___ ___.,.._._.._.__.._I_1_.._._._H._._._._..__.._~..q._~._—~_~H___——_—_~——I—-—I—_ ’I—v—IH—Ho—H—I—‘I—I—Iuo—I—I—oHH—wh—«HF 237 Table 17 (oont'd.) 12:11.11'1..i NI. "A'1l;52"11..la Y. ‘ 1V,1'L . 1 1 ‘ 1 ' E 11 I r 1 .‘ l ,1!11é11‘.l .11'1"_\ 1' 3.11 11 I» l..l ‘V'ALEH ,. .... fiflfisfiif‘fih‘xkifl 1 . . . fi'L-Itb'thX'l .... (03M mm: 11.. fihfifitfibafi .... ”(Mu-31.1111» (.Ub 238 Table 18: Medium Property Tax Revenue Loss, Low Development Cost, and Medium Aesthetic Index '4Ar' IIILE 239 Table 18 (cont'd.) :-_____.___._____ IIIIAIIIIIrIItIJIT-ovlLJIIIllllllll‘llolllllilllllfnIllllI‘Jlin: '01... r s a . JOICOOlhl ..nor. {y‘lljllxnif‘lil‘ . . . o c u . c n a ¢ o o n o v . . . a . . c . n c g c u o . . ‘ v . . . ¢ . . u 240 Table 18 (oont'd.) ‘IIIIIIIIIIIIIIIIIIIYIIIIIILII.Tllfnuulltvllliifillllllllltlill]IIIlalll‘Jnlulolll1 1‘ |.I‘[][.. 241 Table 18 (cont'd.) ...... t‘“n'-:(i’.‘.;<"~' < , 0.59.0 3334 \‘C "'5" ‘-'-_“ 242 Table 19: Medium Property Tax Revenue Loss, Low Development Cost, and High Aesthetic Index Table 19 (cont'd. 17M) Li.5f‘;[r ;.‘Jl¥l’£\ 51'17 l a --——---—-—-—-- -.._-.———-—— —--——-4_-——.-—---——————-—-——————————----—-————-————-————---—--————----——-——-————-——---—————————————-——————--—-—. I“. » 3“ I r J. 4 J . [A r J‘ _r \J" l‘\‘ 2 I J. p k. J r. s a u v, I s « , ( n ~ » . u o l R . ~ I v I o C O n a n l c. u . o . . r a a I I u . a .. u , ~ __H__._.._.—_.H._.A...—H._-—-—-._.-—._~..——o—-H—s—H—-—.—u—o——o—u—._.p-----H————~—-~——__ ‘ . . ....... ............i........_....... V . l I , ....u.......ro...............-..........‘...... ........., ..... .......... v, ....... .......... ..,.......... .- .... . ... . l ‘ x » ..“. r .1 ' I\-..'~.‘. .l. o. . .~ “ I '. i. ‘ v... “ .M .. ,... . M..." .... ,.~ .. x. 1...... l . ‘ .. .... .11.:(- . . .1. .. - . ~ . . . . . ... ... I I . . ...,.... A W. . ... _ ., ... . ( - ..‘.v. , \. .. ..,.. .......‘ .. -, ....... .. .. .. . . 1 9 | . z t r . o _._.,._...—‘_.._d..._.._.__._.._._p— ‘ 'm 1 i.....‘...r‘ ... ........,...... .... ....... . ...... ., (» , E HAP IZISHEET IIUATA SET H05 IL 4. J-I a“; ——.H——HM.—.——.——.._._..__»..—._H._.._......._.._.——__._.__.—_.....-.,_.-...4....—._.,...—._.~H~__._——.__H,_._._H—d*~fig— \A ,___‘—._._.._._.~H_._HHr_.._.._.._.v—Hh._fi,_._._w__‘___H I I I I I I I I I I I I I I I I l I I I I I I I l I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I l I I I I I I | I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 0,—fo O'HM C)?\)'\J N HAAK- N (\J h, 21w N W'JN 0... O OKJN gm)!“ N ...-.... .I'OOOOI 0.0.000. NM!“ (1va CNN ()hu '2) O'a-IN 0 Table 19 (cont'd.) “1wa ‘Jl U‘w’w DJ NWN U ......C... O... I... .90. I... ‘1er 0.0 0.. 0.. DJ 807 806 805 804 803 801 800 799 796 797 790 795 793 792 791 790 789 7%8 787 780 785 78“ 783 782 731 ............ ---—------------~------~-—----------—-—---------------t .HH--_~_-MH--—~——_H-—~—~—fi-_l—d“MFG—I—I-d——D—1-—4——F1—_I-!-I——_I—~—-—--——~—W~—~__——_-~_ 245 Table 19 (cont'd.) JlJl V II u... o .- u n- ‘I - Ml-I KRNNNFXMH IQKBQVMEE $03.14 9‘31»: QAGKBB$JU 0th XII-'81": WNW I‘VV. 246 Table 20: Medium Property Tax Revenue Loss, Medium Development Cost, and Low Aesthetic Index t . a n I . l I . ‘ . . a » A I o . o u I I . u . . n o u . I n o . o O u a . u , 4 . . u I . . O - . , . . l . I I . a I . v a . . . . . . . A I . . . . , v e . A . . o . u a . . . . . o . c u . . - . - .. . I ~ . . . . .. . . . . . 1 . . ~ . . . . . . . . 4 . . I I ~ . . I . . ~ . I » - ~ . I a c . n . . . . . . b . . . . . . . . . . . - n . u u v ........ .. ., . . h . . . . . n .. ... » Av . .4 ..I .,¢.. I . -. ........ .. . .I 4 ¢.-. ..-- - .-< I »..c. ...--- . a. o o: I .. . ..« - 5 . .. . . .... - ... .~ . . J n .. . . 4 u . 4 o . u I s . V n ...4 .4. (Vlrvv .Ictlu'ld‘ us, . r . - III .I.- .... ..-.. .... _ ,. v . .. .0 . . - . V... . u- . . § . .... .‘Iu..‘.‘. - o-¢.-.\.c-lo IIov-p . I I ,g. ,. u- .v . .... I .u . ., .p .u I. . -. . ‘- . .A o- n .- a . . . . . a II ... ». . - v I f A I I" I ..» ... ... .A. ... . - ...v .. . III 0 . o . . . I . . t . . . a o v a u . u . . I‘v' 1A: 1‘ l I I I I I I l a I I l u I I I l I I I I I I I I I I I I l | I l I I I O ......— II II. I I I I . I . . . . a I I I . I I .I... ... I..\ . ... .. .. . ..I. ... II .II I I . . I I I I , I I . 1 .III I II. -:. IL . . I I I . . I I . I I I I I I . . . . . I I I I . I ..I. ..II. I. I. .II. I I I I I I . . I . , I I I I I I I . . I . I 248 Table 20 (oont'd ‘ I I I. I I I‘ 1‘ I‘ , . N I. A ‘v 7 If) I ll...ll'l..u...h ...Illfi I.II.IIIII ... ..I I II IIII .. IIII I-III..-. I I I I . . I I I . . I l I I I I I I I I I I I I- I I I I . . I . . I . I . . III...I I .... II.. II. II. I..II I ... .... . IA ..II . I~I >I. .IIII.... . I.I...I ...I--I~ I‘C‘~.O . III-I .... I-..I-I I .IIIII IIIII. . I .-I.II IIIIII . I III-IIIII..II.. . I . I I . . . I . . ~ I I . . . - . . - I . I I . . . I I . I . . . I I . . I I I . I . . . - - I . . , I . . I I - I I I . - . . I . I I . I - I I I I I . I I I I I I I . . . I I . I I , I I < I o . .. I . I I I . I I I I I r I I I ~ I , . I - I . I I I I I I I I I I . I I I . . I I I I... ‘IIIII...I. I .........II ...... I ..... .. ., .I ...I-I.....III.I.I ...-I II III. I. .II......III-IIIII . I... I , ,. I I.I.I. II I, I....<.II I ...II I I d . I I I . I I . I I . I I I I - I . I I I I . I - I . . I . . I I I . I , I I I I I . I I I . III a . I I I I . . I n I I I , I I x l V I I I . I I I o I I I . I I I l I . I . I . _ , _ I II I I . I , I . . I I I . I I I - I I.I .. . .I -I I .... .I I. I I .I o I . I I . I . n I , I - I o I _ I I I I I . l I I I I I , I I . I n I 1 . I I . . I I I , . I o . e I a I I I . I I I I I I I I I I I I I I II . I .....I I-. - o I I I ~ . I . I I I I I . , I I . z . I , I I . I . . I I I . I . I IL; -I’l ..E. .I .. .. .. ... I . I I I d I I l I: j 5441‘. I . I I. I ,. I II I. ., ..II. I. III I.II IIII. I I III I II . Iv .. I.,I, ... I~II III . oI-II. I... MU \- ,_. , H.- ..I 249 Table 20 (cont'd.) .. .. OAI-l‘ i~ ‘ I<>'C-L {In .\.§fL.LUT: VALUI' FAvat AprVIr-w I" LMH LrVLl r-0.\L‘ 5F.C0 ; IN (ALH I’VIL Lud VALOCS NH)" VQIHEJ F A r? T» IA D ......I.. QQO‘QNWGNN ...-II... RNNQQNSO” \angL) .... .... ERIN»! GXRG ..IIII... fififikflflfilfifl . I . . .... . éfififllfllumfl r~~,JFWLY x 1V~C lo 25Q Table 22: Medium Property Tax Revenue Loss, Medium Development Cost, and High Aesthetic Index IIIIIIl 255 Table 22 (cont'd.) ZICA'A ihr l 'tT MAP 1>I>H 7 b 5 6 3 Z l 0 9 8 7 6 5 h 3 2 l O 9 8 7 6 5 4 3 2 l 0 O 0 0 0 0 0 0 C 9 9 9 9 9 9 9 9 9 9 B 8 B 8 8 6 B B U 8 B 8 B 8 8 8 8 fl 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 25.! 2.37 2‘46 2&4b 2:.5 2A.5 24.4 22 2L.Z 2.31 2.51 2.50 2.30 2.49 2 59 2.58 2 GB 2.h7 Z «7 Z.«b 2h 5 Z.«5 2 #5 2.h4 2 «A 2 b 3 2 A 3 2.~2 2.~2 2.61 Z.«l .2L.0 2 4C 2.99 2.J9 7 b 9 I I 2 l U . I A I X . w I n I r 5 a J 2 l x w m. .3 n a I I n n w H .c/ w h 7. w u M .m M H H H h n 7a m 2 1AV 15.3HEFT III‘ATA DET 1 Table 22 cont'd. I----__---_--_-----_--_-------..___-..._-_.._----_----__-..--_________-_-----_----_--------_-------_--_--____..---_--------------..--_--_' Pu N '\I '\J N N f\. "\J N N (\T n '\ '\. ’\ ‘_‘ IV (\J N N V,“ w Tu 4“ y .. ,_. " I "JV’V'U rx‘ AN , \J‘mk |’\.‘ N b.- I" 0 ‘1 ’1 L ‘3 1‘ ur n N I ‘ 4‘7,‘ IIIIIIIIIIIIIQIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIII-IIIIIIIIIIIIIIII 806 ‘ I“ IIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIIIIII IIIIIIIIIIIIIIII BOW '; IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII P101 'IJ III-IIIIIII-II-II-IIIIII-I-IIIIIIIII-IIIIIIInI-IIIIIIIIIIIIIIIIIII-I-IIIIIIIIIII 7" lIIOICIIOIIOCQDIIIIIVIIC......IIOIIUCOIInl‘loifllIOOOOCII- IIIIIvIvIIII .IIIIIIII r Vu~. IIII-IIIIIIIIIIII-IIIIIIIIIIIIIICIIIIIIIIIoIIII-IIIIIIIIII...II.IIIIIIII-II-IIIII ‘J‘J I-yIIIIIIIoIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-I IIIIIII-IIIIIIII HHfi_mHg——I—~—-I--I—I-—a»-«——-—‘I——~—~——u—--—-—-~——-—-—~—~—‘———-'-—'-‘I-——WM-q—M———~—~—*——I—~——_——~ " III...IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII ("l I0..-IIIICIIDDIOIIIIICOIOICCICIIll-IOIIIIICCQOICI'IIIIIO...IIIIIOIOIIOOIOIOIUOI. IOIIIIIIOIIIIIIOIIOOIIIIII.OIIIIUICIIQI......-.IQCOOIOIICIIIIIUIIIIi.IVUIIIOQOII ,‘ Yul ‘ Ii'l‘ltlOOIOIDOOIIIOIIIIIDOOOO.IOIQOOOIIll!|..‘--II.0.Q.OIID~IIIIOICICUIllI‘IVQI' 1 ......‘....‘..‘-"..'-‘..‘..I..'..."'.....“t.... ‘C".-"""l..-)‘O‘IDICO‘CIOQ III-......IOIOIIIIIIUIIIUOCUOCOIDILOO-IIIUIIIOICIIIAIIIIIotl.llu.v.lnllolol-'llh -I ‘ CIOIICOIOOIIOIIQDCICODCCIIOIUOCOUI'IO9COIIQODIADOQIItalby'tlI‘IOCOIOUOIIDID'llci {1‘ QOIII..I..II.O.'IO.II'III'OI'I'IGI‘CCI.I‘DDIOOIOIDI-I CID-It'OOCOIIOCIDIOII ...I. G.A......'C.-..."‘I'.l....-.....I....C.Il'.l"I‘. '10llIII-IOOAOIQIOCCDIIIIO’IQ .....I.I........I.......I......II........I.......... .,....................... /’ I‘...‘II...'.'..‘...I.'I...'..I'...I.IIIOI-C'...I.9C."‘..C‘l"lU..V'.. Q... III I 70H 1 UIOIIICICQIOCOOCI'.................I‘IIIOOIOU..’I’..O..OIOO'IIDI'DCIOOOOOOOOO... ‘ ‘ ...-I...’l.."l.......'l......I..'C".‘-Q'U...‘....I-I......."‘....Il...‘.'...' I 7 III...III-IIIII-IIIIIO-IIIIIIIIIIII-IIIIII-IIIIIIIIIo-III-oIII-IIIIIIIIIIIIIIIII I OIODII.O.I'DIIICIQIOII’QD.IIOI.IDIIIDIIICOOIODCIOOIIIOI2l...d.|l".....l........ I ‘ III-IOICIOIUOIIIII......II......-CIIDGIOIIIIIIIOU-OIIIUIOIQOIIICCIQOIIICIQI'OII. 78?) I IICI'OOQIIIQIUS‘.‘........UCI..-'...I.ICCOCIII ...Il‘-.-...I“.' I'D....I.I.'..‘ I A OIOIIIIICDIIIIDQO‘....IIOIICOOII.‘...IOIIOIMIIIIIIIIIIIIDI-III—AOICICQOOIIIIUDD' I ....Ill-................'.'......‘o..‘......'."00. )0. I‘ll-ClI-IQUIICIOOQOCICI 7.1% I ....‘....'.l............‘....-...I..-.'......l...0‘.“'....-.‘l.......‘.'..-.... 1 (IQQIUIIIIICOIOOOOOOOIII...-IIIODIICOIIIOIIQCOSIIIIQIIOIDIII'IIu-IIOCIIIIIIII...I I , H 'H ............................................... ........... ................... , . I . O'DIIOI...IOIOIOIDIUCIOIII-IIOCOQIIIOOCIIIIIOOIOICIOIQCOO-OOI IOhIOUI ......Clbt ~IIIIIIIIIIIIIIIIIIouI-IIIIOIII-II.IIIIIaIIIIp-.III-CII.I I‘oIIoII bwlt‘OIOIIDOI ] ‘ j 7211 ‘r 'ItIIIUOUCOII'OOOOICOCIIIIIIDCOOICIIIIIIOIIIIIUIUfillocolooluu IIIIIlI-IIOISOIII I IOO'IIOIIOO-IICOUCIIICOOO'IUIOOOCIIIOUO‘OIIIll-IIOOIOOOIOOIODIO-IDI‘Istl-I‘D.I.) l IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIIIIIIIIIIIIIIIII 1 II T ' IIIIIIIIIIIIIIIIp-IIIIIIuIIIIvIII-IIIII CIOCIUIDIOUODOICUCIIIO'OGIIIOOIIOIIOIIOQ d l IIIOIIOIIIOIOOOOIOCOIIIIIODII'OIIIICODCICI!IIOIDDOI.ICOCOII¢Dull-III-IIICDIOI’CI l 1‘ ...‘I'.'................‘.'I-.I.......I..O..VD.ll‘.........O...I'....-..‘-'..'.. I E Il'l .I'OOOIIIOIOOICOII.OIIOOI..OI...-IOOOIOICOIIOCIIIIIIUII.lllhIIOIIIIODOOOOIIOOIII 78.1 I ' OIUIOIUODIIIIOO'IIIIOCOIII...CIOOOIIIIIOIIIICIOOI‘OOOIIOOOI‘IO IIIIIIIuInIIIIIIII I L ...}...D'III'DUOIO.OIUIC0..........IOOOCIJIIIOIIICI...-GDIII‘OI-IQI......CQCIOOOO I - ‘x ' .IIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-II...IIII-IIIIIIII.I.I....II I................. ’1‘ I III-xIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII-IIIIIIIIIIIIIIIIIII.I IIIIIIVIII-III. I ~ .‘ V T T . . A _ . . . ‘ - , . L . - L , I ‘ - ' ‘ t A 4 ‘. 7 1 1 l x . I l 2 v, . . - , _ ‘ 2 ‘ V _ V ‘ I ’ . C 1 I A .. . . ,. > 4 , ' , a 1 I ’ l J____,-,_ _, H4---_____--—<-—————-—— ————— —v~——-7~vA-—-——r—-———7-- ————— --‘- *~-- ---f_ 7 2.___.--_A__‘_, ————————— F————4AAV______-_.__-. )‘l m. H W14? 1‘ ‘K Table 22 (cont'd.) Prt 'M? v r 71’ «11‘ N'fllr , * ‘7 > .,\u‘. f‘ ‘( > [r l-.. .'»l ‘ r ml “ 1 r E11 Mfltl'~ " lkr {‘l‘yr ".“I‘Al‘l: (L . fiotfiki‘NYNId . (‘NNA'XK’K‘IH . Xfikx NAfiM . (Hi1; .‘1 .|\ 2‘, 3'? i . 0 C‘ x L Ric: 3"" K .(,M . . {a ‘ ‘_. \‘Y' \I.‘(a w." | ,‘ IHIII 258 Table 23: Medium Preperty Tax Revenue Loss, High Development Cost, and Low Aesthetic Index Table 23 (cont'd.) Mr“ 1r..)11A.-ti ZoLixlq BCI i l———----——-—————_m.m—————v—w—--—'———------—_-_—-——————_----—_---\-———r--——".--—-'-——'v--’h——————~~—-——W-w-‘uJ—---— A I 1 1‘ , 2 z z _' 2 ; z 3 .‘ ,_ z _‘ A A, 3 _ I v V 4 r 1 1 LI ‘4 v ‘A 5‘ A ‘ 5" - ' x l L 3 I i‘ O / "A ‘/ 7 l g ’A AA I . A... .. A. A ., ., A . ‘ .. . AAA...A.. AA- A .. A. . A "|A ‘ "'01-“ I... '1‘ .-hal¢".ril‘v~fli.~ CA‘L4~I‘.t‘ .) 1‘ A 0A. A AA .. .. ......a:... ...... A A ..A- A...A .A...-A.A . A A 7t L w‘ _A.A;.. .AA..AA~. .....AAAAAA. .,,.. -A.§A74.AA.. ..Av. r;..~AA | .A 0" AA J“) Y . .AAA. A .....AAAA.A..A.AA.. A A ... .. .A A..... .. .A _. , ‘ ‘ ’GIOK‘OI‘AIIIIl4‘.05.I...I...L-I11......Iiii'ICIII...’.‘...H.|ll.....FCJUUIIIDI A - A . s ‘ n. A ‘l A A ...AA. A . _..,... . A. .A .. A . .. .A..A .A W. . ., ,A . . A A:A ...AA .,A. ...AA.. .. A. , A . n A A I , A A - o . . A u .A . ~ . I .. ~ A . . A A A . A A A a A ( A . I A ~ A c u a o a A s ’ — A o I o l A A , A A , A a , A A A ‘ A u A v . A - u '1 a . ' . A I o o A ( . s A . a u o o AA . . . .A A A A A, A . A A _ A A A. u . . .A A. A AA A A . A . . , A A A - o A u . .- . § A A » A a - . A . . A, I u 9 u A I 0 . . A. A A. A . A A A A A A ~ . ~ . A . A . A , V . 1 A - ~. ~ ; - s a A 3 ~ 0 \ A- o I 3 a l 4 A o u A A o I u e u o . A c A A . , A a - .~ I - . . A . A 1 A V ‘. I . - A o i A . . ,. a . a a , - . o .A . . . - n o l A. A . . - A . ~ . A A A n . A r o A A - . s l v . . . n A l A n A A A . u - , A A . . . A . . A A A A . A r n . v u 4 r . n I h n n , K 0 - A g a u n . A . o - . .A l 3 ~ AA .A . \ a 1 A A ‘ . . .A . . A .. . v u A 1“ 1 A a u A A u . l n u u r n A . u - u c a A A . . . a a a J u u 4 o L - I 'I a u . - ‘ a A - A .- u o I l A A A. . . € A . -. A A A , A ‘ u l a . » u A . . . a - | n v 1 a o v ‘ A a . :A o a a o b A. x . v \ A o I - ~ o A w n , A ‘ n. u n . A J n § - o u ~ A , A A. a A A 4 A A . o n r c 1 A . 1 . J 9 u l A n a I ~ v ~ A . A A A . . A. , . . . . A . - . . - , 4 . A A ‘ ‘ . A A I . AA . D . A . . . A A A - o A. - r A A A u A . v A AA . - - . A A A A . _ . - l A - V A . ~ , A . n 4 l . r - , . A ~ A A A g . . A . o - A A A ') ‘ A A v A . n A - A .. . . .~ - a p u n u a c A e . r 5 ~ v d L A A A u . . s . ‘ 4 ~ I A A. A . . A A A A A A , . , T . V t ‘ ."A A A . A A ’ . u a A A. A o v . A n . I v I l - A A . n o . A a A .. . I . . c A . A A A. . - . n a I A A. . . u . u . . a . u u .. t u a A . - , A A u A A , A A I J . A . ,. . - - r e o u o . l - . - o . A o A . . . I A l . . A A A A A . . . , I .. A A. . A A . 1 - A s a . I a V I ~ A O I ‘ A - . A - , . A A A . . A A A . . A . - - I u A A A . A A- A . A A I A - .~ . . . § A A , . . A , A A‘ I A A . A A« . . A , . . . A A , . A A . . . l A - . . A A . A . , . 7 . A , _ ‘ v . - . A , u - u u v A - 4 A o s v - o - A A t . ‘ s l v . A . A A . - -A A- I v n A . - A t r o 0 ~ . a . o n o . - A . A l A , v ‘ ‘ . , . A v n A A . . A h u A y A a o v A u . . u a u I D . A l . | l , A , A , . . . . A u . . A . A - a A ~ I A w w - A o 4 A ~ u x c . n . - A $ - . r - A A v A A . v A A A ~ A A A r . A , - A I n . A , . ~ A u n A u a . l - o . . - n . o . . . . 1 t I . A~ . . A A . - A A A A , A . A / .. , . - . . I ~ g u «A 9 n A n o a - - u v o - 0 a A A 4 v u N A . . b . A : . ‘ - A .. - - - AA A A . A A A - A n u . A I . . A o - . A . s - A b I . a c a o ~A . . . . A A . A . A . - A A A , A A o . l A A - A. . ‘ . . o a . v n . c o . . A A - . u e n . n . u . - . 4 ~ o .A I A A . a .. n n t § - o . ~ A AA . A A A 1 A o - u . c . l I n t a a . o n a v o . I .. I n o u c c. o 9 :A A - u 1 u n y u ‘ u u u a o A ~ I' -A A . A I -l .. . ¢ l A I A . A A A . ’ {f A: b u. . A . a . n n u n u - o u a u A n . A l v r 9 a a n h a V n A . . n . . u . A a . o n A a A o A . n . u - - '~ A - . A . . A . I A .‘ ’H‘ l i A A o u c I a I A r a v n . . - a u l . n u a o . . o a t o 4 c . . . . . o , , o A I A , . A A A - u - A A .A A D I “ A "A .\ AA 1 a n n o a A l A, o c 6 ‘ A I v Q - n o a u o a I I o 4 u o n A .A - ‘ A . u . . c I . - r u . . I . . ~ - A . . - . A a - . A ~ . . A - ~ - A A A . a A ‘ A . ¢ . I , n | . n A- n ’ A A A . - - . A A l l - . l A. A . . . . A A A A l ‘ A V A . - . A . - . A - . . . A A | . u . . . n s . - . n - . v s . ~ A u - - , u - I u o . . A | I . A .A a u . . - . A r o - A. . A A , . A . . - A A , . . A A . A A G u v ~ A A ~ O . «A . ~ \ 1 o o A A . . . - . A A . A . . . A A . . . . A A A A A . . A A . I A A A A . . A A ~ A A a . r . o - - A A . ~ A A . A . . .A A A A g A . A A . A- A . c . I u A o . ~ . : A . r . o . A A A A - . ~ . . - A . A A . ' A . A . . . v . I . .A . - A 4 , .l . A . A. . AA . . s l A . l . . A A , A A . . A , A ‘4 . A n . . I . l 1 . u o v n o u v . - . n . . . ~ , . A A I A l A A l - . A A 4 A , A A - A A A A . , A A A A A o u - . o - . A A .- ~ . a . - O A a . . a v . A . . A A A ~ , A A A A . . A A A» A . A A . . A n t o o g A A AA . a u A A a . a A, . . n A. u A A A A t A . A A A . . -, . , , . ‘ A . A . A D A c u . I o A o - . . - l A . A , , A A A A A , . A - , . u . C a . . . A A A . - A . A , V . A . A . A A - _ A A A A AA . , A A A A A - , . A A A . A . , A _ A A A z n A — A A A A . A . A . A A . A A - A A A A . A A A . A A A , A A _ A A . . . . , A . . A , A A . A A v A u u . A I . A . I . - . . A . A A A I A . A n . A . . . A . A . A A . A A A . , A A . A . - A . A A A. . A A . . n A , A , . . . . . . . . . . . A A .‘ . . . A A A A A A , A . . A . . . A A » 2 - ~ - A > - . A A A y r A I , . A A A . . A, A . A A A . A . I A A . , - A . A A . A A . , . . A o A - . . v . 4 a . . . A A A I . : A A A - A A A A A I A A . . A . A A .. . . . A , A A A n A A o A . A . - n o u . A . . . . I . - 4 A ‘ i A \ . , A . A , o A L A . g . -A . A u . u A . o u . ¢ I n o I . - n 4 A n . a - - :5 N I‘- >- ~ A . - - - A . » - - - - . . . c > A A . AA AA A I A A A I A . A.,.tA.A .A ..J.\ 'AA A A A . . A A o . . A . , . A A A - A . s ‘. A A . A A . A . A . . A A . . A A A A . A .q ‘\' . . A A A A A A . . . . y A A n A A A . . A A A . . A A A . . A ‘ ..,_.A.._.._.._____A_._A.....,___,_. H.__ A—._..A_.._.A-.._. ....— ,_A._. L o . If . - v I .v . o a v I .I L A .... CV I «.4 n I... on . n. D -n .. A A A. v o 9 . . IAAA I I l A I . 9 . Q A . v u; . v! uIc-o II I —.. (I. .u o. . --. . l IIIOU. I I I o ..... I I- v 1 I o A u I 1 cc .- l I o o . O o A Table I to. A c I o b . .4 A. AI .. AAAAA Yil I! .r I . A.- .I . ¢ I § A . C --. I. 260 23 (cont'd.) I I I A I I L L L I I 1 L J L I I L i I l l t I L I I I I I I l I I l I I l I I I I O 261 Table 23 (cont'd.) 262 Table 24: Medium Property Tax Revenue Loss, High Development Cost, and Medium Aesthetic Index chnLTIvt\ ‘JSH, rIH~ Irll) NAP 263 Table 24 (cont'd.) 1 ZIDATA SET HAP 17.5HEE7 807 EC? AAAAAAA.AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA-AAAA A A A A A A A A A A A A A A A A A AAAAAAAAAAAAAAAAAAAAAAA... um 802 801 3C1 0 9 8 7 6 5 a 3 Z l 0 9 B 7 6 C 9 9 9 9 9 9 9 9 9 9 8 B B 8 B 7 7 7 7 7 7 7 7 7 7 7 7 7 7 A u 1 7 a a a 3 2 1 7 9 a 7 h u 4 v 7 u 9 4 w 9 v Q d j u u a 7 7 l 7 7 7 7 7 7 7 I 7 7 I 765 782 781 761 130 0-——-~————~_—~—-—~H————n._A.——-—A—q—-——c—n—A—_.~—~—A-——A—AM_u—~H—H—~——~—~fi—H_-——A—~fi——Mbat—.—A—HH—_——-q--—_——~H~—-~ 71H _____-__--_—-_---_--______----____—-—-.A-__——--.A—-_—-—--_..---._--------—-—_----------‘_--. -- ------__--__-—------_-—--_____--_-___- - ,— 0min: 00000 0000' 000000000 000000000 000000000 (~f‘q A ”MN 000: 0000 0000 0.00 0000 a... 0000 .000 0.00 a... 0.00 0.00 00.. 0000 0000 0000 00.. 0000 [\I Mn. «I Table 264 24 (cont'd.) m I‘NN N O‘NN ‘ 0000000000000000 0000000000000000 0000000000000... 0000000000000000 0000000000000000 0000000000000000 cocoon-00.00.00. 0000000000000000 0000000000000000 0.00000000000000 0000000000000000 0.00000000000000 00.000-unconsci- 0000000000000000 0.00000000000000 0000000000000000 0000000000000000 oo-noo-Ooloo-oo. 0000000000000000 0000000000000000 Iooccvoooodoooct oaoonuo-concnvoo cocoon-0000'...- oooono-uoooooooo 000.000-IIIUIII counter-3.0000.- 00000000000000. 00000000000l000 00000.000000000 000.000-0.0.... ooccuoolloolo-uo 0000000000000000 0000000000000000 00000000000000 0 0 00000000000000!!! 1 00.000.000.000 0000000000000000 oooouoonctolulo. OOOIIIOII-OIIOCI nooocooo-aoooooo 0000000000000000 00000000000000. 00000000000000. 00.00000000000000 Ionian-ooooooloo 0000000000000000 0000000000000000 l00000000000000l0 unsavoooootooloo nor-00000000.... 00.000000000000- 0000000000000000 alloovvnoolalioo 0000000000000000 0000000000000000 0000000000000000 0000000000000000 0000000000000... 0000000000000... .4 Pm P.) N '\J \J" N r~. ? "4 (\l NA) N 0 0 0 0 0 0 0 0 “J 7\; er 00000000000 00.00.00.000 00000000000 00000000000 00000000000 00000000000 00000000000 0000-00.... 00000000000 00000000000 00000000000 00000000000 00000000000 Oooovtuoitl 0‘0000000000 shoot-co... 00000000000 00000000000 loo-Ions..- 0000000000. 0... 0000 ...-l 0000000000 0.00-0.00. 0000000000 0000000000 00000000000 00000000000 00000000000 00000000000 vototoouoll 00000000000 00000000000 ...-I000... 00000000000 0'... 00000 0 00000000000 000000 I 00... INK; NR: OwN 00000000000 0000000000000 0000000000000 00000000000 00.00.000.- 0.0-0...... 00000000000 onus-0000.0 00000000000 00000000000 00000000000 00000000000 00000000000 00000000000 00000000000 00000000000 00000000000 3.000000... 0000......- 00000000000 00000000000 Otto-lacuna .0... 00000000000 00000 coco-coo..- 00000-00... 00000000000 ...-c.0500! ...-0.9.... 000I0000000 noun-...... 00000000000 £00000 000000 00000000000 0.000....- U) (\ILAAN k» w ‘1'th 0 0 000 000 000 no. 000 000 006 out 000 0.0 00. 00. 000 0000000 000000. I‘ x_'\.: J‘ I,» rm UJN NWN INN 00000000000 00000000000 0.0.0.0.... 00000000000 00000000000 00000000000 00000000000 0.0.0.0000. 00000000000 ...-00:000. 0000000000. 00000000000 00000000000 00000000000 0.000.000.- ...-noun... 00000000000 00000000000 00000000000 00000000000 00000000000 00000000000 00.00.00... canoaoooo-o \A.» ‘4 I.» P. w 807 806 805 804 803 802 801 800 799 798 707 796 795 743 792 791 790 788 787 780 785 784 783 782 780 I I I I I I I I I I I I I I I I I I I I I I l I l I I I I I I I I I I I I I I I I I I I I I I I I I I I I 0 ..‘..._.§ — m.” - ._Mififl ' ) Table 24 (cont d. PREPARED FUR FRANCIS M. DUMCY 8v YHE GENFStE/rIHGcK LAKES RFGICHAL PLANNINu BOARD «tUILNAL INFUKMATILN SYSTEM 4? FlTlruJuH ST. S‘Ufa ROCHESTER, N.Y. )ATA MAPPED IV 2 LEVELS BETwEEh EXTREME VALUES 0F 0.) ANU 1.2? MEAN = 0.00 81. Utv. = 0.C3 AoSJLult VALUE HANbE APPLYINb TO tA(H LEVEL MINIMUV {.0 C.oC MAxIMUM C.bG 1.20 PERCENTAGE OF IUIAL AIthLTE VALUE PAKGE APFLYINb TL EALH LEVEL btoCC 5F.OO FRLJUENCY DISTRIBUTIUN JF DATA POINT VALUES IN EACH LFViL LON VALUtS hIGF VALUtS LEVELS q 1 2 3 ......... [00080000 ......... 00.000880 SYMOOLS .... .... 3000 8080 ......... 000000000 ......... 000000000 FREQUEVCV 0 ICSS l O 266 Table 25: Medium Property Tax Revenue Loss, High Development Cost, and High Aesthetic Index 267 Table 25 (cont'd.) 4A“ lj'jflftT i'UATA SET 1 ¢_--------_----__-_--_----_-_----__-____-__-_-__-___---_----_--------___-_--__-_-------------_--____---_-___---------_-_-_------_-. I\J {\J "\.I I\. F’\ N. n I» l’\ \ !\ I ., \_r r‘ g) 1‘ I I f. i J Y J rm 1 ‘u‘ III-looonOCIh-llbdltv-1c..¢l¢hi.o.ow»uti.‘b.nl..lv.--Q~O ..t. A- L‘C I IIn...OIIOIO-IOOUIUOOO.......IBJIIIOIIIIIUIOIIICQODOIQDvOIVI'aAA l O-tIIIIOIqooIIOOOOIIOIIO‘IOI'luOICOIIIIIII.Io'.l.6.l0l.ol.ullniyn .r,.e. ‘9. \ A . n u n o n .. 5 I u I I u u n o o o o o u o c o u n v o . a o o o n n . o r - . '- n . l o e ¢ "’1 _~_,_._M_._.___._.H._l.—-.—....__~._‘_.—r—am—H—u—H——~—H—HH—-—o—_ ICIOIIDUIIJiIUIIOCII...lll‘..lrIOIC‘IOIOI.‘...-I D'IIIIN I‘lq ' «Iv-....v‘ ‘ .4....'.r'llh..".'..".’....~.."J."..‘...4..'4....' ’~‘ v 9‘ 0‘3“ DI" . “ OOboItOOCOHtIIII.lCltltnol00on-llclln41t...‘on4.a..p. ..4 . . .,‘, v. ., “‘ l . .....o-o-co..on-u.ll-Iaoo-.nac-na......s-c»...y~anv-.a-- .‘... . . . , I A uvunu-otnnnnouo-oIo-ocIto-on...o.Aonvwooo..¢.-u....ru.u;. ..u--- ... ., I ‘ ‘ IIIlloo-OIJIICIII.C.IUCOOD‘II'IDCIOIOllttivou-OGDIII—lt-I' ,‘.~..¢ - . V I l . ..,.....................................,._...,_.,,‘. ... ... ,‘ - .. . I , 100'IIOI~UICDIIIOIIDIOlfilICOOIOJI‘Iulpl.IUOOI1'O>-,.-... . ...l .... .. ‘v f V ‘ IIIIUOIOOOOIOIdltoO»Il-I.o‘lyoaoIv-I-ncrti .aI-yu.<.. ... n . . - . . .. , I .II................"-.-.‘.H.....4...-.'V.."...'."~"h’Il l D .4-1.‘h-,v‘.’ l ' l . I'D'....U.6.‘.'I......OI'ICI'CCOOtICIODOIDIO‘DLII'O,'_D c.0-¢.. ' I C p >. ‘- " puoo-ooooooguu-I¢Ioouooutao~ounnouo.-aI--ocucoop-naocnoo4vn¢o a --.ao~uo-¢tv 9“ I na-I-u..eccouoc-nun-Inna...ao.--u-nuv-na...au.-..o...- -.».~ .«.~. .-.x»:.-. I ‘ I InQIIIIIOOIC‘IIICICOIOODColvl-nollhb.-lh-lbl.0v.lIlinav- ‘.. ..-..~. i..) ‘ / ............................... ..........~.n...... ,,.,_ .... .. ... a. ‘ I , I'IIIOOIOIIICO'IIICIIIIIII-IOIUI|BIOOPO"I‘IIIIJOJUflIMt'ohllr D. ual lflool I t...IIIOO'OOOIIIIOIOII.lll.ll'.l"'|0l!bl0'|-In...-|Il-IOD-oll‘n o ....i, ,. l ' v c ‘ ......................................... ‘.;.... ..... .,.,.. ..,4 VA. A. I u..--.-u-uaa-cna--.uo.....ouo.o«uos.u-uo . ... .-' ..... -. - ... - . 1 o»bl’.-Dlt~.'l- 10.... O-dldl'o‘a Do. A a i , ‘ Oil-00.04.10. I!M...I.fi....'h~l4lf I l-. A. II‘ - d . .n ‘ . ‘ .v....................-..........-.... o . ... ........i., . ‘~ . .... .. I ....V....-...............m......m....‘...... . ..g.‘ ‘, , . .. I ' ..‘..'.¢...—......-......-...o.o..o.......-.-. .-... .. .. ‘ i a - .. I on...,uc..x--on.o:oo..-o~...u....~. ...- A -... u..- .. . I o-A tillOIOIOIDICIOOOQOIIOCOOOItutti-1Ir I .: - .‘ 4 .7 i 4 I III-ol-II'DOIIOIvbaIIIClooclosno'.¢-~.--:41~-...QAeoav .~ ~. ‘ ,7 .~ .. “ | 4..........-.I-uon.aoa-oooo.-va-cn.c..-I. . .....‘ . ,... ‘ .... .‘ T A ....I‘IIIICOI......IOIOC0CCOI.........Vl'l...,h-«,fi.4~ : I 'I‘l l‘)‘ a v I ‘ ...... ................. ...... ........-........ ., . ,_ p . i.. r ‘ a..-.oco-no-g-o-Ilnono.uonou..o~.uo-~ ~....¢su....o.nu - 7.x - .7 i.. i ‘ nun;can.beeonaooc-IIIo-Obuo-oo-uoannon-cop-. ....oo.....-‘... .... -.- .,‘ I ‘ l,.. I"" L -.., IOOOIOIIIDCOQIIS......IIUIQI-Ol0004000IOOOI.|On...--.apuuccuo-ov|pvu l ......‘U‘.....HIUOIICCUOC"C......O'...Il.D.-‘.l.u..-IIU .'—."A‘-.'.)".ul' I I ‘I’\ a-OIOIOIOICOIIsOOOA|halaloaqu4-Iuvoaunlouovo¢v§ebo.¢-I ...,r.-.:- Dial-l .r I I I OI'0’.o’vl...!OQOQIDO~OOOOOOJIIC§IIOOO’I.CIIOVHOQOIQ0..ewlio¢b.cot§uhn0;Oitl I I:ot-ttno-nooo.‘no-1on1nanny-.0400....oloccno.ooust-aooI~-uoo-.vo.ayccoto a l l . I- S I ‘ J OIIOOOOI‘IIOCDOAOUOI.ADI-I'lIOU-Ouovono!v0'-00:0.0-II...JIIOIIOOIODIIOIOoI-o “(I I I 'I......I'...‘I-l"IICIDQICCIUOOIvIICIO‘I I....DO'OCU‘UIIIIICQUIGDO0.0.6-C3l0 I I ......COUICC'I...‘.'.....'..................-............‘OICI..'."'...‘.'. 1 fl ‘ ‘1nI-sot-ua».n...-an..¢-4..ua-uooln..‘ 4 ;noo|.xnocop.ao-1n-o¢. - ...... . .3.“ I o.....‘ll.lh.‘II.'lo.-0IIIfl'iulIIFQIICCUIOvPUJDQI tulx‘...n)l *Ao‘vl- CD...- I ‘vOI-haoa-I~.-oaa.o-- u.c.-ooo.onlco.-.o. n a .-.,. --o . . . u a. . I ‘ ...aa-c...nonau-o-u-oc-s-III-‘ua.av~u... a.-.-‘.‘...o-‘-.«:‘-9 ‘.... 41-— N’j I '0....fill...‘....'.l..li.....'IJ".‘\...I.‘.h‘...'.l.g~'0'. ‘l“‘..|“'l..li I IIC‘ICODCI........‘l......... C...‘.......l.‘.....IOCOCIOOO..IOCC.‘I.COI.I‘O I I .................................... ..........................-,.......... H02 I Ll..Iovuo-nooanu-o-talloovitlvuvvll'olv.I-- ... .....4.-oa...- n:--~noooo.«n I ‘..l.'.‘.-.-l'"I'C.....-‘~......"'.'.I....‘.F......5J‘--.QI.‘.‘..I..'....‘ I I I I 1".II0I......-¢u'..l..llI.."..li'.'.IJ.:.I'I.‘).'.CD‘I~ o.n--c.....).«.ooo.. L'II l ' I I UIIOCOUIIOICIIII.III’III.HCCICIIIO-IIOCDOIII.....DIQDCIC.JQ O'Ch’."‘ll....l IIIOIIIIfilCC‘IIIIDOC I....‘.‘.hu..'-‘".......‘."'l.,"....“'.‘..u‘-".. L‘ I ‘ P I I‘ll-DI......Dh.‘.l'..'l-I.........I..III\I...1...'..IJODOOO'OIOIICO.QD.QIIII “()L’ ' ‘ I I IIDOOQQOOCIU.OIll’I'IOOOIOOOICIIOIOOI‘OIIOICQIII'IOO'ODIOtboloo‘lo.00.60.... I 00OOIOOOOIIOCIOIIvIOIIIOIIOOIOCIICIOIDOIIOIIOOIOIIOltIIIOIIOIIOOCOOOOOOOIOI' I , l‘ I 1“ IICOCO-ODOIOIICIIOCCIn..-IIIIOIlofivollvliaAniontlivlilhluclvowill‘ot.....‘.v 7" I n I ..ao..cuo-.c...4:-~ao-o.u«not-oaoa-ooonuw-tn‘...-nunnu-.e-.no. Iuh-fil'IOOUOII I I ¢I.II..O—IOUIIIIIOIIOOOOOIII...‘C‘....I....llii‘IOI-OdvuI-Ooxv. .' DI .-.O..I"' 1 ‘ " .9...nlllllllongooau...-.030-OOQDCOOIluv.III-OoooosnllioI'll-JO--scnnltl'loooovo 7‘b I ......u-uuu-ooI-uu...coat-n.0-I-unn-oo-ons-anu~ n Quyleluoilucbituol.nsnlllantl I I CIIOOIII'I'II'IICU...-....FC.......I-‘II'IIIF.ID‘5 'D.\..O“IDII.I' l......i'|l. l I ;«J .........................................H. . . ...... ..... .... ........ 7;] I ..ICI...........‘O.fi'.l’.'0...‘IIC..'.I........'O.¢'"UOIO'Il.Dl.9I ..4“l..'." ] ............05....IIEJ'Q.IU.'.I'.~.I..Il..ufl‘...¢‘-I~0M'lx‘v h. vilii'll‘051'l0a I I ...............................................».....,.\.,.................... I; I ....... .....WW .. ..... .. I I .............................................. “W. .i .... . . ,...., . I I I . A a;.llplutlI-AIIIIOIOCOIUIIOIIu...'c ......c...-.a--.-o-...'¢. «.... ..‘4 ,A...... I}, I ll.‘U.IDIIODIODII.I\‘I.l..u-llI‘E‘wh‘lvllIL..I.ODI-Onlvtl‘ ‘VD‘JxllM k- I IOIIJV [ ....un-oapu-oq...-ocannvluunaaon-so .0....¢o.uonu--oo..au ¢o~....... A:..-v--o I v ‘ ‘v~ ........~... ....l...........a. ........... . . ..-.-.........I. .. ... . . 1‘ I O‘ICI“‘-C§...JQI.O‘IIII'OO...‘.ID.V‘~’¢.’U\.QI IVVOJI'IOL .I'~ “\CU..-l vi D. 1 I ......c.-oa-.-....o-oto-vuo.c.on.-.-ouVout.v.o.o.on.uoou-o..oo- a- ....004torp.' I I 1" --.o--cuts-anus......-aucnucno-Ilc...-oouoo-uc'u-o-coon-ooa--..o.-o..~.......... [13 I I ICIIOIICOQIIOIUCIIUGIII....I.....'I.OIII..IIV'IIQIOIIOICDIO'O‘COD OIIDCII.I-b.-l I A IIIUIIDIIIDIUICQQII...'O.II.."'IOD"O......"CODI.I‘OVIO.O ..L.‘OIIO'I‘VVI..II.I I ‘IOOIIII.IIII............."'......IIUI......Cd'IICOIbfi.IUDI t. "‘.'a‘.".‘... l’ I 05"!.IIIUUUICUDICIOICQIOCCICIIDI.’0-‘I'.".l... ..II‘IIIOIVDII. ‘...-|‘-"...‘I‘ l ‘ actual-obuolloviouvl-I-Ulll'lIIOOIIICOvocuInin‘O V>§II0II ... ...: .- o un.p... I ‘I . ...i....»..a.-....‘-...... .......o...‘......... , . . .-‘ . .... .. I. I 0dbhllOIOQOICUOCISOOIO0.0QIOUIOOOIIIO.'IDO.§IVI N I‘.l4 ‘§u u-h ; h ' .7 . I ...,....ua. .... ... -¢-IIO.13-1OC-ool-~¢--¢ o . ‘ .. . I , ......H...” .......... ..i..........‘.. ...... ........ .. ~ I I w..-.-‘.-¢..v.-.-..uuu...«.....Itnnoooo..-.~n~------~.---»- -. . '5' -.;--v-I«vo I I ...........-...... ............,... ,....‘ "...... . (... I ‘ v .......1................... ........... ~..4 ... . A..... . .. 1%! I I ......so...u--u..no-o...on.. .....u... .....n;. ,_ .A4 ¢.| IaILI ..-u--~v-v- .- I OIUII‘.Cl.l...§"l.¢dll.\h‘lo'IIO...ID-I‘.‘ LO-I'HleFOIlOOO-lel u .- ssgAnlyp l ‘ OCIICCIIOIIIIIIOOOIIIOOCCDOIIIIIIJOIIDIA-uoo: Déygoo-Ira ..... .I I -—-.—._.. ._H~»_ 269 Table 25 (cont'd.) Inhrb‘gll‘t \ r pw‘ f"»\.Hl\ H. ”UNIV Im ». ,. wr'l ,, ,. 1,“. , ml‘ rm .1 I 1r» 1‘» ” «L }AL IHF‘ “fillh‘ ‘V,T W Hf flffiHnLH LY. Syd'm i","-..'1": thLWp HIV. H1] 4 ‘Allr’r‘LL‘ ['_ _' {{yil ) {Wt}; Ll’h LATI r H; Vfll lH‘ ‘. J 7. J nr 1 fl "'CH‘ ; 7. :an AL)“ all I' “Hum “whim, It 2M»! {Law WI.T“J‘ (.’ (.‘r hl\ldnl .L. l.fi' 'L“ I) L w T } L \\ ‘(\1 Vil" *Arh M*1‘|‘\ I I‘ " I .FA w‘. 4 r~‘~ "J‘I’ Y [)l“).v*]“)wlll ‘l ' t‘A‘l!‘ 5:11'.‘ \VullJL 1 IL ’AKV' ‘ v'l LJu VALH35 blur vALUrQ fl LTJLL‘) a l 2 5 ......... EQXXfififlxi ......... fiuwauxsxx .1 ‘wt. .... .... “6&6 EEMN ......... éfixfiflfibfix ......... VJKKGViK< 270 Table 26: High Property Tax Revenue Loss, Low Development Cost, and Low Aesthetic Index Table 26 cont'd.) MP 19.5HEET Z.UAYA\ sEI 1 ' fl_-— _-__-——--—__—-_-—-__-__--____------__-_--_-—-__._-____———-_—___-—-_--_-_-_-___—_-__..__..i---_—-—-—--_---———-_-——----—-—--———-_-_. -—<._._. A ‘ -.-pon-.c--nn-.c..~.u-.oouo~.o-uo.-~o~-...xu.-.-rav ... A-¢. r HUC ~ V ‘1 Inuit-liuyttol0lIIIOOQCODDOIOIiQOIOO no.1.1ulza.y:lonv~-‘.-ooo~n... nl-Oa..¢ "OH . t u a o n n a n I n o g a C o o . v o . u - s n n v C . c o t o u a I n c .. n. q | a c n . c I o o v u u ‘ I v . a ‘ .. -.——.-—._HH——__p—._‘-—~————.—u—~H_—p—.p_._ AA 1 ‘ n.’.<....-nnoucua-u.o.zo-‘9o-.A‘..uu......-..\ nouA~vuxau..-;-... ~ av. .... “a l A Donn-unaouotlhtuloonilI..v.-IQIIIIOIODrfllIIQIlwv.rooovpoJI-Io-tcIvoluplfittoo l A .uocan:ncooovnuu¢auounuo.o-oven-v.01...ouooo.o.so--.cooo.aoouuu-Ioao.-¢o-.l- l l“ cool-IOOIIIIIIIIIUIOCO0IOIICICIIOIIQPO.0"...-llor-IIODIIDOlboilntlocc.‘II... l’} i v «...-aoucuuo-oca...-yvuaua-o-aovgnoqen....-cums...;u..o-».uq.n-v.--9a~-uuou. ! .uu-g-l-z¢¢-ogyucca-Ice...-..u---0oOL--u'-n.q.o..to~g—.....g., ..... .....I. I ’ vCOOOtittfitOleIOUvIQIIIICDIOtIOIOIDIOIIOIQQOIOIOOIiOIlItt'th a.. ...,un an 7‘" I aiooafilll-uocuopnu.4 a...n.noc-qa-o¢;uqro-onAc...-o.n-o¢ o‘eqo»A--......A,.. I ‘ O‘DIIII'QI-ouIoIQOII-I-nelu.Iluunlco.~pocuacuua...love:‘40.. ...4 -.. .nnu.,. i A" IQHDIIQOCOCIuIIOII‘vutbllrtllhtoodocuiccunslnlovo.tlooinl. Aa-..v-.¢.. ("1 l doc-outno.l|no.|¢lha.ltloauoooaxuosoolau~Ion»... I’lh-OOIIAQ. A ...A, . -~.\ [ ...............................A..........A..... ...... ... -, A A. .A.A.. l . ‘ o-Iulaoatvl-IIIIemoI-II'IOOCIOIIIQAfiO-tItodcc¢..«I ..on:n ~rea .4 0 ...-...n- ’4W 1 ...-..n-n:no.-o-~ nv- our: -v¢.‘-aoO--A-- Otuuounnno‘o ...A,» .A- AAA.-.u.-. I lw'luvylttoDIJU-Oacu0vthu-leotqloyll-rltc-IQIO».¢v.400qu- .4 ~..——,.. .. l "" oo-ovolIIOII-ool.llcnotclcolccou0.1.00.5.-CO.rOo§-)1¢.-¢ Ivy - (ya ...n.‘»-. {1‘ I .......................................................... ... .. . I ...aon..-auuoooaa.~.auouts-nnnnn-uo-I.‘....x....q...J«A.A v...~. . ~. ..A... I ................o.... .....A.....A,......... ................A . .. . .A ’ d ............4...................-.....A.................. ... ...A .. .. -. I ..........n-u-ou-nouu-.....n-o-...-....a-vns...-o..‘\o-..4....A ......... .A. i v‘ A A ' flOIIOII-IOQDIDIIOOIIUUOOIIICIDQIIII'OOIII'l-w-dcilv’QOD‘JoI «~cn.-'.-4c-I-o 1’ i ‘ T . n-c-uo-o..--uovco-uo-IcuI-I-aau-nooeov¢.--o¢nalconv.y...-.... ... n--~v-.A-.A ovtotilhtltdtl‘l00...:vQQC...II$I'IOIIID¢¢IO«~Ia-uvuvuo“u .... . ...... -. l ‘ .-..A...................................-..-....‘.»..4.... A .. ., . F . ....g.u.o...-uo-.-nou-rn.conn..n:-..:..ougn-...--. ‘--. ... . .A.. ..A..-., 1 .......................A...........A......A....AA..A....... ... ..... l A‘ l l ....nn-.-..........-.s~4.A.4.. ........-.A........A.:.o-.. . AA A. . .........A............. .. .VAA.. .....A..-....-. ......... . A . . .. l ......u .l..p.‘A....-.‘... .. .AA.‘ ..,\ .. .v A . ‘v .A‘ - . A ‘ ...»...u....4.u........c~-.4.n¢x.--,.l~u.o.o. ,.-.. -.... A.A. .. ,. ‘ l ......c.a.--.n-n..v-.4.-A.v.uu¢ g».-¢.-.-o.-‘vv a‘o~o:uo ...e- ...A. .....A. - A ...................... ......... H... ........,... . .... .. l “- ............ ..A.......A.. A...«,..A,AAA. .. ........ . .. .A ..... -‘ I A .....opp...-..-....A........A.....»..... ......A. ... . ... . ...A A ......oo...‘ Al...-».|- ... u. .1. . .. ... . A . . A A7 A H" .. axrc-a- Ahilav-O¢¢qac.t-~I.n ween-rAvo-~o g ...... -.~.. .. . .‘ ‘ ‘ ................... .AA . W. ..... ... ..-. A A.. | } O'CIiOQICIIIQIIII'UDIIIIO¢¢~vll1-'II-'vi'O‘I ’I!x'*7~I .- « . < . . § ‘_‘ I {A ........o..--.-s...n..p......-A.... -.-..;.o.... <-... '... . .A ...A . ~ I coco-too-annovou‘uoo-uoao.‘4u<.<-a..-¢-¢nrv.. en. t‘Q-bt-anvla- . -A‘a.o , I \ I....DIIOI7IOOODOIOJII.I.IU"‘IOFO‘luv!tIII'OI“lII\I(-ol v 0- ¢ .. .‘.. - I w ....................................A........A... ........ ... .A... .... 7n 1 ....o-u..a.-on.-......a..~.laq-...--~- 7: 0r ..xaca. . o .. . - . AA . A A... ....... ......o....:a. ... ,.... .- o.» ... . . . A ....‘ . AA . 'J L ‘ ..~.....o..u....-.sa‘v~.- .... .rn-v--. ..... .A..- o .- . ., , 9: ................. -.......,.¢u............. .. .t.....~ . A . . I l ‘ ‘.¢.An.nun-no-r-«nqu-u...-ouuu....y. . ,vu . :.-.~. ... . .A. .. - A :‘A 3' ...-.----.z.A.-v...—.. “A..-.... ...~ -. . . a .~..~~» . . A ,. " ..oothbcfiublieu §~IAIFIlnll1vIdoula . 4 . .... A A -a.ucv. ...-4... .A--‘ ~-.¢ .....- v. a. - A A /_, v ,,,..,.._......o.o...-- ‘.-~ A...x .....~ .. .AAA .. ..A l 7.A A. A ...,....c.~.- po.......-. ...-.... .... Av ,lA ... .. , . ,_ A ..........A.........................A. ..A. .. ....... .VA. , 1 \ " goth-cuscooIoIIUuup-vont-«ooo'.QI-u..-0.~ -—.. .A.- .a -. I.» n- 1 "M r oo-e-uoo-nuuo-1....nunuou-unvu-uu.....ao...o......a. .g....o .. ~-~ -. . I I-IcoolIIOOQIIO-ovvo.‘lrlc‘tutelaoan~~90... .... .....A ..,,“ 1 .‘ I 3 I". COOOIIOOIOIDUIOIQOIII'UIIC'I...-Iolulo-I«J-.qlu.'A4‘ .x- .- .\ ~ ..A .. I‘ I ,..o¢»¢Io-co-no¢.-‘a.anu.oo:oa-.as-~-..-u.n~~-oo 1.: ’A ~ . ..A I I .,.,...............r9A. nuAAA. r.-....v.~ . , ... . . .r‘ . I ‘ A ,,,..............A. .......¢..AA . .A... .o.-......- . A . .V A.. " ' ...-v-o-o.o.o.‘-...u.n... ...... A...- A~.AA—». . . ,A..A A. ,R .. . 1 A I l | g _ A . . , A I .| L‘ ..A —. . A A. . ,_ * A J , ’ 1 ‘ A .. n 'A , A A ,1 1 272 Table 26 (cont'd.) 2 I I 'amn ump. 1 z 2 .5 2 2 z 2 I. 5 n ‘l INN ON“. (1..» ..u. Nur— mun. uv U.SHEET I‘DATA 5:1’ 1 I l I I Z 2 Z 2 2 2 2 Z 2 2 2 Z 2 Z I I 2 2 2 2 Z Z Z 2 2 3 3 3 3 I ‘7 C 2 3 h 5 6 7 8 9 C I 2 8 l I I I l 807 807 I I l H05 806 I l 1 4A., 805 I I I H A, 804 I I I a. q 8’): I l A .A-_; an: I I I A 801 l I 1 I). 900 I I I 1.. 199 I l I [Id 796 g I IvI 797 l I 1 7 ,, 796 I 1 7A,A 795 I [ I (A.- 795 l I 1 I” 79’ l v I I" 792 I I l 1,1 751 I A ,H ’90 I I . In: 75" I I I ,.,, 768 I 2 ,5, 737 I I 1 70’) “’5 u | 1 ”A, 7:45 I I l ,A... 15H. l I I ms 753 I I | In’ 762 I I I III 781 I l g 74) 79° I I l I l I I l l I . ... 273 Table 26 (cont'd.) \vu LI.»' HI.,Ir L‘ 1” JII ; ‘A, A . Am I II I II' I AI‘ II V’J I ‘I I‘ b I - H LH «L Ls W I r I ‘ I“’4I ‘11 I, I L 3 ., . banh‘Klfi .... {MWCPhfibé ... A a $4 .. . u .‘.(9' I 274 Table 27: High Property Tax Revenue Loss, Low Development Cost, and Medium Aesthetic Index 13* gl*.)r1-EtT gnarl- 1 \—-——.-..—--.—..——-—-___--____.._.. v T a I a . , - V . . n . . A , | A. .- . ‘ . . I u , c v , L I ‘V I - .. . . . . A A I. - , , . 4 b 4 . ... .. .. A I. .o . .a n- o . a .v . . -. 0. .7 u. 4....- ,l. a A o . u . c o . . A v . ... ..A . .. ..A n. ,, A 4 . a n . b I 9 - I . .A s. . .. . A. . .... .v o . --~ A.. u. .. . .-. y - . . . n 5 I . . s . Iv . l - 4 u o .. - . u u I l ~ - | . . . v v ; A v a . v - v . A . s - o ., .Ap - IA .- - ..A n r. . u . I. n v u .c .- 27 Table 27 . u. .n . ......n.rs¢.-VA II. . ... ...... . A ‘ u o 4 A . .. . . v ..A. A . A o n :- . . . n . I cont'd.) A . . A . | . 276 Table 27 (cont'd.) A A y I 1 , I I .~ .A . .IA 0 . ~ A . ' . A ... I . ... . A ,A. s . .... Av. ... ..A. . . .. . ..~c.. . . . . .o o n.... u . . .....-.. ..A... A . . -~ - Olhlfi . ‘.-- . . A. .‘ n o.- A... » . > .. .. .... _ ... . . u .. . .o . .-. . , , . . .4 . . . . . 1- A a . . . .A A . . .. A ,. . . .. o , . .. o 277 Table 27 v ' ‘- q»-»~..y ”~\""...‘.-%S ..... . . b i-i L‘ N l'. x“ 9'. I" i" .4 (cont’d.) 278 Table 28: High Property Tax Revenue Loss, Low DevelOpment Cost, and High Aesthetic Index Table 28 cont'd.) H" 41.5HiL' 3.1,ATA bcT 1 .--__-----___—----_-_----_-___-..---_-l-_______.._____-_-_.._--_._-_---__-------___-____..,f-lke___-_.-.._,_-i--______-..--_-_--_._. ------t I"\. N \) Vv '\ (\J (x; N ‘ ~. ‘v .a x R) \ W 4‘ J a J: .... r A M I v ‘3 \J 4...... ‘ I‘lpvlolcocoooou.....Ioocvu«lat-i..p-oovninrnlla-uoooI-nnal-nvn .v..--.v..-- ‘ Anlvunnlloaovno-o IIOOp-00~|.llxnlolycco cc.lulu-..voovuouuvo‘u.lv .....u.‘. l IIOOOGOfiOOOQDIIOO'CIIOO'OCIOOnIIUDIIII!IOCO'IIIDOIroot-Os...lbinlulhlvOlt‘vo I .......u...o..:. thlto-tlnc‘0~ ... .‘-.. ; ... .... .. ... -¢... ,_ .‘ l ........................... -. .. - . .V . .. .. . ...... . [ .., ..V........ ...... ». . s . .. .t.. __. ‘.,. . ] .rto‘ooennotoootdo stow-CC¢-.COO soc.»-‘ -. o ... .... r .o ... ... " I .A......-.. ......o-..... ....-.;. . .. . .. . ... ..... .. . .V... .. ] ... .... .................-........<......................... i...:........ 1 V ...........«.........--.. ....4‘. ....... . .....cy .: ... .., .... ... V. I ...-............. ......ou......... .‘......,..-.........‘.. .-. ... ..l.... l ‘ . ....l.....--......-‘.......,r... , ... .‘ .......‘..... ... ..., ‘ ,.-. I . .r. .u. ~-.voy.o...4n-~- v' .. ..- .. --. . .» . .. . ‘ - ..... ...... :- ..., ~.. .« .. ‘ p...-.I.'.|v , ..,., . [ ....~-.c..oo..-..-vo... Ino~vl ...-.-...~. --‘ ...,.. >.. .T . ... , I .7... .. ....... .... .... o n -. ... ... , . .. . ‘ ,. ' .V..Ao.....o..c....n.......‘.... a- -~-... - ‘ ‘ . ... ., _, , II-I‘vlwvchuv'lo ...... ....- ...4 . - ., . u ......4 . . . .. J ' ...i..................................V............ ....... ....... .....h vwr I .-.--......l...-...........- . .. — .7.‘ . ..t .. .. .. . . : .... ~o.....no..-.-....n.-~...s-¢-v -‘-o . .... . . .... .c i. ‘ i . ...V......u.. V.......‘..........«. ..... ...... .. . . .. .. . “ i v.1..........-~V¢:-cc...c.o..¢..Vp.-.:o- . .. .-«.. ... . .. . . , , ...... ... 'ap‘IflrD-I-Ah 1"..4-1'1: .n V . . ... V V .V . . ‘ ‘., .... .......- ..........«-o.....- «...... . - ....i. t .... ‘ L ....-..... ...l .. . .......-‘--l. .. an-o‘ . .. . ..- . l ......u -.ooco¢.“..uu.p-n~.ac.--:Au..o.....- .. ..... .V« r ..v... _ . I “ l ‘ au-n-olI-ou'ooacI-II ...-0.:nnnuuo- aloInfi~u.n-l o--- . n- . - . ,n. .r .. . . o«'-. C.>JI.'I.QUOIIVVVICC.‘4IDIV~ .uc ».~ 4. . .,. . . , . ...--...-......... ........... ...V . ....‘VV.V.V-. . ..~ .. .. ' ‘ ... o...A..-..a......-.- ..-l.-c‘ ... ... . ... V. .. . .. _ . . V l . .--~........u....-non...v---.:.-.aIu-.-..nA l-rv .. . V. .‘ ... ,- , V .. ...,.......... . ..... ..V .. V V ‘ T .‘, . . .... ‘.. ... ., . . .... .. . .. . . .. . r .. - .....- . . , .‘ ..... vv ....... ...... .. ...T .l .T , r ‘ . . _ , V.. ..,.. . . V. .. ..v . . . . . . V L ., . .... .. ~~. .. ..‘. , . . ., .7 .. ...... .... _. A. .. . . . ‘ W. V. ,. .. . ...... .~- .- , - .....-.... ...-..‘. -. :.......A- . -.,...V» ‘ . . . . I ‘ .......~ ’.a..-. -...... .. c .. ... ~ .- ~ . . - ...V.-..,... .... . ........ it.... . V . . v- i . ; .. . . ., n..-u--a....~..- A..-.~V‘.' .. ... .. . A ..A V . . _ ‘ ‘ o.-..¢...p-o.pn4s-..u-n..-.»;q-...-~-. .n. .i ._ . ‘ ,,__ ‘ .‘IAOIOIII-C.IIIV-I'I.ll...‘-I.III..‘OQDII.>-'Iv . .I.I w “'3 I .I . ...... ~v I D I 'u {I .0, ' ’. ...... O. IIII‘O. ~ 1 O 0' I ...... O. O O Q ‘I 0' ... o .I ...... i. O .‘O... l l . .. ‘W I .- l I..I¢I .. a . I .. I. - o "I o>¢ato .I-I a~.:.. 0 had I I II I III-II 'I I o I -I .5 III I I. 'lCra- I'm. .I.Il.~o 4 I V I I. I oI.-0. «I o . . .I .I ... h .I lion). .II- I :,.- 6 I I . . .. . ... .... .. .. I .. . N31 1 ... . ...... ... ..... ... . ....... .... ..... ,. I V ... . ...... .- I . . .. .. . . . IV. ... l I ‘ kl‘ I o 1. I ...III -. l . I o. .. ...- . «o .-o..o .... )LI.I. . II l I. I ...... O. I I. . I. 0. CI. I U. 'l.l.i .... ...... 0 l ‘ I I D II I ...... ~C . I . .l I. I.’ . .. III... III. ...... I I'I 7‘4) I ' I II I IIIIII II I o I II II I l . D. .....- .I . I-I~0I I L ... . ...... .... .. ... . .. ...V. ... ..... . I V O a. I'vllu a- u c l u .. ... . AI ... I ... , I... .. Y “’ a II I IOOI‘I I. I o I I» Q. «. l I. Inoan~ -.-v ....Ion I I,“ I ... . ........ .._... . .II,..V... . -.. . I I a II I IIIIII II . I .- oI 4. I). ll ’I|\‘K .1.» .-- u . I V", I I on o I-ao.. on I 0 ~ '1 II -.. . II... I. , ..V. ¢ 'I I O I. U ..‘l.' .0 . . U I. ' ~"v V I. ID‘~.v ID?! " a 4 . l . .. . r... . .. . . . I. .. .V . .V .I... ...... . 7 j I . .. . ...... .. . . . .. .. .. I .. VI (.. o- . .~ ... I 7“? I u b II I IIIooI II ' I o to II II! o .p ... u~ Inc. ---I. g ‘ ... . ......... ...». ... . .~. .‘. . ........I . I . .. . .......... ...~.. ... . ...~... V....... . I . .. . ...... ... . .. . ... . . . V. ....,.. . l " I ‘ I. . .. . .I ..l .. - I ~ - .. ... a .. ...~ V .. . It»; . .. . ...A.. a. . . . . .- . r. . .I .. . I I . . .....u .. . . . . .. ... . . .... . . . . I ‘ I" I II I oI- In In I f I 0' II "~ g If III I ,.I,. IDIQIJ I. 7‘! l L o I. o III-Iv -v I o I .- II -II I on I-IuI- I I ‘OIII‘I I i I ... . ...-..... .... .. .. . ...s . .. . ...... - I w 7 I > I I- I III-Ir I. o o I v> (I (I. r o . <0. .. I ..- I " I D II C I'll-I O. C O l t. I. D-~ I .0 .Ilv‘! Iv. 3...]. J l I I I. I ...-I. on I Q - . ll ... . ‘l ...... ..A) .p .. . I ‘ C II I J..I'<‘ l- I I ~ II .- n .- .~. , v I . .. . .. .. .... . . ._ . . . . -. I ... V. . 4. » . . V ‘I I ‘ l C I I- ~.4I do I a - I ‘0 III " - . - l , I II I «vu«-. a: .V v .I . v.-I . .» .1. I .V . I. 4 l . .. I. .... . .V . . u~ .. -. ~V .. . . . ‘_V V l ’ V I I ., I .. .rr . . . . . . ~~ .V.... .V . I . . A . , [ v I .I o aha-ll .. . a I o - - 4. .~... , I . I. . L 1 ‘I-I, .‘I. T I I I I. I III-'- a- n I. I: -~ .y o. r -. .... r .» - . I ... . ...a.. .. .. . . .. . T.. .-.... ., .. . I ‘ C. O 0.01.. I.- . . IK I at p‘ I . 4 . I' _ 4 ’. ~V I A ' . .. . ... .. .. . - . .. V. . . ... .... . . . I J I Y I I II o III-cu .u I u .9 II caI o bl -... -I.. .-u.. - l I I In I ArbIA-l. -~ . u I .- c. Ia¢ . < .A.- ,_ ..vl , I If 7x4 I I _ 0 II I ao...I I- l . . ea 1. ‘70 .I ...y;- , , -...V I I I .s ‘ c-r... .. . . . .. I. . V -V. I . V . I .. A... . , . , I - l I . . ... . - . V .. e V , o .. . ...... u. . . .I .I . I V ... k . .. . .I, I. . . . A _ V I o .q . ...- . .. . . .. . I I . V VV .... V w I r . .. . V... . .1 -- I . . ,. . . . V . I . O .I l IUOQIC ‘0 ‘ - h " *4 . I s (Iv. I V! ~ “I 4 f I 'M. ‘ l.\ . .. . ..I.... .. . . . ... I . V , .. . I I I . .. . ”...... . . . .. .. . . .. . . . .. V . . J l I II I ltl... .1 I A I a. -. I;- I ‘1 II. vs I . ...-.g s I I I II I I- a no I CID... c g , . . 4. I. I .- .-~ ,. ob.‘ .. ... . 7 . i 0 II o ...... ... . . V. A. co 0. . II III... C‘OI . .III c . l 7). . .. . ...... ... ‘ ... .. ... c .. ....... ,. . ... . 7“; l I I ‘ . .a o one-nI I. C - .I .u .1 .> . -- .... I.“ . ..V. 4 ' I ‘ . .. . ....... .. . .. 9 .1 IV . » .. .... A . .. .. .. g I ‘ , l “ ’ o I. I IDIC‘. vv 9 I 4 , ~¢ I-I b .4 ----I . >~ .. rdl J t . l ‘ o I. I o.aI.. .. . c 4 ‘ - I, . .,V,.» . .. . . I I ' l l V A , , l I I . . I v , I 1 m U I 7 1 j V4._-— 281 Table 28 (cont'd.) Table 29: 282 High Property Tax Revenue Loss, Medium Development Cost, and Low Aesthetic Index 283 Table 29 (cont'd.) czv. Juurx. Z ‘3 7 HI“ 12~SNEEI ZIOATA SET 1 I I I I 2 Z Z Z 2 2 Z 2 Z 2 I 3 k ’t 4v ‘v 5 5 ‘1 5 5 l 9 4 b 6 7 Z 3 5 b 7 I I I I I ”07 807 I I I 600 um I I I 3" 805 I I 1 5“" 80’» I I I ’1‘) 803 I I I '3)! 892 l I I “"II 601 I l I .n‘yn 800 I I 1 7d? 799 I I l 791 798 I I I 7‘~I 757 l l I 7436 79!: v I I II» 7‘15 I I I 7%. l§4 | I I IM! 79) l I I hm 792 I I I (41 191 l I 7, 790 I I 1 In 759 I I I I‘m THII I I I III 781 I I I (In 786 I I I 713 78') I I I 73-» 7“ I l l D15 783 I I I H“ ”I I I I VIII 7!” I I I In(’ 780 l I I I I I I I I I 284 Table 29 (cont'd.) “A“ zZ'SHEhT IqEATA SEI I Z 2 Z 2 2 Z 2 2 d 2 Z 2 2 Z Z 2 2 2 2 2 l 2 2 2 2 2 Z Z 2 2 2 3 5 3 3 3 3 3 3 3 ‘3 C l 2 3 6 5 I: 1 d 9 C I. 2 3 b 5 b 1 8 (“‘7 807 500 806 60-) 805 50" 804 | | (1(7) 303 I I I In 1 I302 I I I "-1 801 I I 4‘: IIOO I I | 7w 799 I I I I‘m 798 I I | I17 707 i I l 7'7" 19». ‘ I I ; ['31 79') I I In~ 7‘16 I l 1 ['4 s 193 | l I 7": 792 I I I III 74 I I I [On 790 I | | Irv! 78“ l l I liw 788 I I I-I 78] I I I 7.50 7Hb I I '. I05 701'; I I | “M 73-. l I I 7., ~ 78) I I I (’4! H2 I | MI 781 I I l 7du 76L I I I I | . Z l 2 .‘ .3 .. .1 I: l . 1 .1 J 2 I I 2 z (I 2 2 2 I .’ 2 z ' 1 j J 1 i ‘I J l I a 0 I 2 Z A 5 b 7 B 9 ( I 3 ‘9 I: . I d I I l 285 Table 29 (cont'd.) 286 Table 30: High Property Tax Revenue Loss, Medium Development Cost, and Medium Aesthetic Index 4A9 d3.$ntLI §__-_----.‘_-__ «#HHfi—t—nro 3 Table 30 (oont'd. f z 2 2 2 2 g 2 ' Z 2 2 3 2 ~ ~ 1, a 14 w ‘9 ‘5 H w ‘ I Lv ‘7 i F I I 3» ~ 5 o 7 8 9 ‘ I z .J'IIJII‘II'V‘FQOIv.....‘I..‘"IC..'..°‘I...D1 ‘.I~'O.l“ .'0'--v1.6-.....I..‘.."’......‘.D.’UI...ICO'\'O.“.“’-O Ins—IIICC‘.'COO.~...I..I..I...uI...’.'.C..fi..ll‘§...... "I ’\ .......uo¢‘lcuovlcooottloobIGOOODIIIIIIotcot'vttotbclbl ....lIIO"".....‘I-..I'.‘II..-“.......III.I.....ICCDOO ..ul‘l“ ‘scitc—u-u-uunoouuuoyvao.a-..c..-uoa«-o.- ... .. ‘oe-I-uu..Ion-‘ounuoogooeIon-oo.‘---ocunqr-g.¢- .0I.Ilr ‘ -.I‘a~ 0959....Oll~l...-VIIO-~>I a I..'? ue.--‘-vo . v.- oto.aa-o_.IIl-.Ivv-oo~.u...onuoc:onun~uc.¢o 0\l:-oc o-.«-.-.-.oocIo-uo.aoosln.uno-ooosna-~-..uvuop,-.u.-ooo . Jul'ICQOCIO~II...IIQOUIOIOODIOOQOOOI‘IIall...‘¢ ...-o.- l‘uvII.ICIIOIOUOIOIaIIOIJOIOIIl‘OQOO.fillitol'tln-:iII-O . .I... .;-a..p-o~-n~~-ao.o......o v.0;4' u'vv .. ,.. I: ...-..4.......-.......-...¢ua-n--.;.- cA.‘.|¢hi\I-Dl.lv I. H not."vtl1tluan...’n.ll¢4.ll.00u.¢oll-to..llnl-OO~.OODCI .....i....a.-an.Ioou....u..-.....--.gn-......ua...s¢o.o \lllCivil-IUIIIII'IIOOIIICIIa.....IOIOIOIOXSIOIOOl-Ifilili ‘ at'viilqlllfl COI'I"DI".....III'~ I‘I“...-"I"‘.l6'. IOIO‘OIOICLIIOI....IOO......‘U....‘IIUIIOOIICIIOI‘III'. "'9'1IDI..lh."..llal'."'...‘a.‘U........I‘o."-L..... " n.noo¢..----.oo---.oo-a--oscopuo....-.....nnuoauaou.u.- )ICO‘IAlhcdiilI....--........‘.‘."...l..ll'.l.fi..‘..‘s tin-II.OO’IIOIUIO‘OIOIill.)...-...IIIII'IIIIDII‘IO’...l "r wil-t-IllllietUFO-III-IICIIUIIOIIO.IO\'IOIVIllluvldIIOID -I‘ ‘CCOI‘IIIOI..OOIII'.OOIOIIC...-..IOIIIOIIF.~~ilvl'l ~0II¢I¢II ri-I-OI..O.C.l'..III..“I...UQOI‘IIII -:I'v~"- I ...v... ... .......n...~o.a-.oc--.-...u n.e..-.v-..o-I.ov IIIICDCDIDOQIIJIII'D...Ii.-I‘OICIIUI..IOCIIIIIIIII"UI.‘ ...u.....-.......o...-.u.o...n..-.-oa~...-Inn..I--a..oc ‘(l- .IlIII-CIIIOI.C....-......Cfill.......IIICIIOOACOOIICII' \.'.¢"......‘.l.‘.....'..'........'.....'.‘ CIOlCJONIF ..."-.I..."..'.".'.'-.'...I......'.".'..‘V.."‘.... ' ...-o clout...lullvco-‘olauoooo-llau...onlotoaO- «Ioaoc 1.1I...I..II....'.III...I.I......‘I......IQ‘IIII....III al vial...ulll..l'.'..l\ll'l".........OICIOQ'IQ>...'I V I ..~‘.-.....“ ........uo..-.-on‘o-t.-anu.u-oa... ...A. . .,..,, .. .................l......... ...A\-.. . .-...-..o.q~.o--..«o.-oo ..n.-.- . ..~.I..... » .. .... .....-«oI...,-a¢on~..-uo¢o....u-~.. .v..c..- ..,. ..~-< a...:u«o¢.~.-.-....a..oo.o...-.v-~--:- u....u.-~-.e ....-.. ...I..-.......uao:.-.o-......x.‘.I.p-~-.«¢u« .... .....v...a.n.v.1-1..-.a..-upuuvo.uuno v-5I0l~4 . a»: V: ...Iat....-‘40...vao.:suoooII-Ishop-o.--. ...-I.. - »-- r,........(.........-.-.....a....coo.¢..........-...I I. '4 ‘ ‘1'A..‘ICQCI.IICQO..".'.'IIIIUICICOUII C’l-O‘ -\l.oA-' . . ..u.lIIu'oaalI-v-ola-ouonod-0.0....Iu- ..I....w. .-. -I1‘OIUO‘O¢|.QI.U ou..-.co.--o...cono-.‘.a-r.~-I~.--9... I I ‘ ..ivCUI-IIIll!I.III'IOIII'IOCIII'QCQIIIIQIu)...l~-0CI( IIIOIIIDI‘CI'IIUIUOOOUUDOIQIII.b..1-..'.IllI-JIAICIIOII IIICI‘OIII‘iJOVUIIII‘I‘IO.UIII...IOIC-.AQIII....- ...d. ‘ 9OIGI~IDIIIUIIIIOv-nil-IIIIIIIIIII'IIOOBDICcth.!Ill!' . . ..u. ... unnuo'oOunur-poOIQI- altr- ». -.....a~-.-y . ... ... uv-on..a¢onoo.uooooob-;lcv .VV. ...... it. , .. ... I. . ,..--...a-n...-.-~-o..o...--r~.a ..,. .,. .o .....I‘.‘...".'...'........‘...’.".I. . ‘lIDO. . a. p AA£I.I‘.".1'.......I..KII.....II O‘---I.. l.-:A. I I .....r--...'.-.ao..onnao¢oosccuo'cooora~._.;...xna. ... | Iflall‘lui'FI'IIOICIHDI'IIOOOIIIO'OOOI..|- .... .. ... ‘0‘.)I-lll'IOI‘ICODOOCCIOO.IOIDVO.l‘lll'. OII' CIIKOIO~ . 'I'I.‘..‘...0....‘..'.I...-.....".".J‘O"“..' IQ..-.‘ ['0I.III'...I‘....II...|..'......OU'IOOCH‘JOI-IIIIUIII'I [DI-CGDl'II.....'.I-ll..‘.‘...-....IIIIIDII"O-CIICIOI- "’ D'UUOI......I1IIIOIUUUOIIC.I...CUOOIIllglfith-IIIC‘OI‘G li."l...'l.ll..D-‘ICOCQ‘IIQDI‘IOD.I‘UOO "'MIA.C.I“III Il'rI‘QIIIOIIIIICII’CU....IUOIOUItIWIOICIIOl|10I.IOO00I ,‘.| DOIUI...‘.C....l"U..I.'Il..-....U.'...I...'DIOO.."UO. .0!r“...5l......l‘l-COCO-0.4IOICUIC-Ilcu lOlluOlc 1“... o D l l I 0 l I o O O O I I C I ' O C ‘ O O I I l o I l I o - n O O O D u I l I I I I a I a i a Q I O O O I ,‘ I I A V V _ _ x i . A ‘7 - u, a n . r, I , ’I ’ ‘ ‘ I L ,‘ w I r( ’I 7 II I \ ------_-_---_-----------------------------------. 2 g I Iv n \n 9v ‘ fiOb 'o"~¢ao-In¢c.uuyncao o;cauuoo-occ.oovonI-§ {ICE IOIOIiIOOIOIOI...-..n ...-uo'uooonaoadlooio .. .i......~......... “CG -‘0 IvV~4va.‘lllC'lIJ .. .|¢ .......,9.- - r .... ................ mJI .oa Il‘c’l.‘l.l“'..-' Inlet-OIO|IbObIOIIIIC :......... .......... H03 .ou.u--u.-. .ooo..... ..... ..... . \.)oloa ......n..--vo..¢-nnno ‘(u—c lloaoocoou-a-uo-ou-Io MI ~9¢nv.«04o~'auunc-sva I7 ...-CII‘IOQVOOCDQOII. I ll4£~.ll’.lI~.llDI.O ................ .... 7Wr OII‘I~‘~OI-l‘¢l)uD1‘D.. ..IIIO.“IO~D.IJO.IIO§ .............- ...... I05 .a!‘.’4‘..£l.l.'.lv V ...........,. .a:~~.. ¥.ClI-IDC.F-"I.'hlafil f,“ ...:‘Iidl-‘IDI l.=.-I. I-C'i ...-IIIID§IDOOI 0.040....CIIDIIIOI... ..... (I. .... .,I .. A ... .. . III .. . . . . ., I.. l‘> ‘COICDl-‘: UI.I l’iv‘ ’I .....II....K‘...,.... .;I,.In . .. ...A.. ‘\ ,...I.. .u. Qo.|.J-"-DO '| .... ..I...v...,... . ..... .a.... ... ... TI“ ..."...-....... ...». ,... .....‘ .......g. . -q...- ‘ I'll‘l‘o‘. ......I.............. (:7 _ .. ..............;... 7 o I. . I....,..w.. .... A. , .. .......... 'I . , ..-...IDO.~IV- “ .Illr- -Ito«0.--..'Al .. ..I.. ............ »... ......... I.I;‘.4' I ~O...l'.3' .-........ .t...-... (W) ...‘IICIIICDGICCI ... I.“~PI.!~DIQI..I.I.I.. vwfi 'I“‘~.‘tl'..0..9t..l “{, .III.. 1 I. ‘ VIA? 25ISHEtT vaATA SET 1 1—-_-———————————__...._ ---_-_-_.____-__I_.__ .— H,_H——.._1p«._.-—.._ U . . - I u . -. cu m a I. - .- ..o- u.- . a . . 4 3 . . ca 4 .1 -- e .\ . r I ,, I o . . u u o n . a .. l ca .a . ..u no o u -. u . - .- I . . . . , - . I I» - u - ... I , I . .. . .. -) .... 4 . I. . . I .. . I I . I I . . . - ... e on. I an I. 9.00 I 0.. - .o u I. - o. I . . u. . . .. u h ._.. .1. : a . . . . u a .3 .9. an. o c- .u - ~ I v .. a u» .- u .0. n u ‘ r I! - 1 o. o . y r ..I o I- n: . \ 1 . a D a . . 5. - a o. o b n u . I . u . ; o . . I - v I. - I - A . ~14 . . I . I > . 4 l - a - l4 I t o. I- nu n o. no I. u~ va 0 - u . .I- . 4 0‘ ... I L . , . 4 ,. n a - I, I ~ - I . on u- n a > no v - v .. .0 o. c . n. n I o u . . a - v , on u . .~ I .. . o . .. . 1 ‘ v u l - I q o- n I- vac nu: ow ’0'. a n - a «I . O or c . - . I. . . I . n ,. I. .., I. « I . . 1 o'oocnnotacc-uoJuly-cuuu-uso-uo-~-.auIw....... ....I..... Ovulttltoo-Illiooull‘Iunvo-v.‘o-u u .~..>--.. .--I..,. ... songocgun.can-tn...u...c-u..aoun-vo.r«upooo... ~n...p.-t ungo-uuuoaonoun-atou-noo-uc...:otn-~..----...... ...-u . u u i n o o n o o a n I u u u o o 0 n o a o o u n a - I .. . v n . p - I. - I c u . v o 4 a u I n . 4 n - . . . o I n l I o I I I l u I a u . I u t I u l o o a n - ¢ 9 o u . v v . ; c u - . a u n i l , v I a o n , . - n u . 4 n .. a a o a a o l - u o . I A . o , - . - o - . . 4 ~~ I . - . . I I 5 e u I - r . o u u u o c u . I u . o . 0 . u - I. . I. 5 . . u . . I. I. u -. . n I l v « v . . . I . .. . . . . . I ‘ . I v u . . I 2 . a a . - . . . . .- I - o . . « I . VI . . . I - . l I I u o . . u I I u o I I u 9 u - n o u n o . . . u . . a u n u . I . . . . - I - o q. a . I n 4 . . . -~ 0 . .n - Ion-.n-cI-nou-ao-u. Iblm41¢.a.AlIlM-¢yI-rilun‘llvuohsll ‘.. nocooan-a-ounc-no-caov-nnt~~-< Aa-IIIAA-o-unov ...Inoo-no I‘IOIIOIOIOIil..lo'~‘-.IIIOIOOC-Il.v-t-cun..p~pn u..¢n... ...-tnolsdfiihlmibtl.ouOOI.o.A-I|.....II‘an~v .0 I -~.: ..a...-qnouc.o.;.nou.~.u .-....o ‘Doulolt¢-Oo-.bl ..':.. . Idlhtlutoloontlont-Iocno cannuoa-..o oaoo.o.--.-.auu..-. ....ll-OIO...-Incnon‘da‘.n~Ico<->uno.alo~nnnn- ...-... .o unuoou.noa....a.n.n..-..... .. ......»I......n. ......n... ..............c..-... p~I.-..-..-....I......~.....:...... ............-.............._..............I.. .u...-...I. ICCIHIIOOIDII(JO.UIQOOUOOII...ICuhO-Itb '.'4.u‘..fl otlJ-It C.......'.'."...'...uo'..lv0.1..II’. CV’Ihi'Ifi’vW‘rIb4yqq, I..."O.I..l061¢fillICIDD!OUDI-Dvll‘IU"OQIOIleIIOI'V-fiiD ......(IOOI~IUCOOOUIQOIIIOI’UOCV‘QO..-CIQI'.-..dlan-fi v: IUOOQIOCPII'V’vll'cifigluvo‘d'l-'\O~-o.¢I.vIIca<¢~...4-.IQ. .1 k 4, A A. « n I V e I 1 . I I I I, f I ‘ v I . _ ('31 III’I [ - o n . l o u H.._—._._-—_—PH~—~—-——q—_H——H—tn—I—u—u—._— o I . u n - ‘ . n ham...»...—..-...—....H_..—.—.._~—I_I-——_-—‘-—-._~—-— IQI‘ o . . . 4 u y u I n - 9 +_.__‘_,‘._._._ - «I v a c u ‘ I - “Hat—1H.- « n o a v . o u o . . v o o . v ‘ tun... 1" o..-...... A . . t » n n .-._—-.—..>—- .H—mflHHHH—a——_—¢ 289 Table 30 (cont'd.) PRU’ARFI) FUR FRANCIS M. IM‘MLV HY IMF (JFV.[3!L/FINM5‘ l/U‘lf: PriJlf-f P \l "(ANNUAL [H.Akll LUIVNAL IAJHCNAIlth svsum n fITZInIbh u. suum FUCHE5TLK, mv. ‘ )AIA MAVPFU IN 2 LLVELS utla‘mh {XIIIEMK VALUES In -. ‘ ANU l.A\ MFAI. : (,(1 SI. UtV. = C.0 AUSULUYE v/ALUE «MVGE APPLVHM, 11' tAUl LEVEL 4 1.” f , minim)“ (.523 1.20 ‘ PEKLEHLZLLE Ln: TWIAL A1;AJ|.LT[ VAllJl: RANG- MPLYIVv ‘1, LAN,” LLVEL ’..""‘ 56.0) FKE JukwLV D131KIEUTIDN JV [AIL H [NT VALLvE') [N {ALP LE'V‘L 'ln VALUES hlGH VALUES ‘ J LtVEL> l 2 SY AUUL 5 ERACKMWWS Fruth'aCY 0 )05b " 290 Table 31: High Property Tax Revenue Loss, Medium Development Cost, and High Aesthetic Index 1QV Li‘vJHttI J.L_ATA 5;T 1 Table 31 oont'd.) a----__----_---_-_-___-___-______----_-__--___-____-_____--_--____~-____-_-_____--.-_-l--—___~__-_l_l_-_------_----____-------..__. I E l I I I .' , _ _ I O I ¢.ua-Qoo.u '.,‘. Alli|~»-~.; . 1.1.. .l .,.-.o; :- ...-- ...... . . n . . . . . . . . 0 - _ . o - o o 1 . . t I ; x o . t . A . . . ¢ - . o . .. , e . . . ~ . | a l a u u u . . . - . . . . . . . . . x . . u o A . . ' . ‘ . . . . . u , u . . u . - v . . .. o a . o, I . o . n c . . . . - , . u . n . s . . - . . u » i n . . . . - . o . . . ‘ . . . , . . . t . . . . . . _ . . , . I l . . . A . . . . ...). . .. . 10‘ . :nntkl 1‘, . s nu:........ .. . ..... .. . non-.001 ...A...- ...,, ...... 'A« oc-a‘. ...-u..- ......,..... --.:-~--.~--~-~ u .. . . . ‘i .. . 4 o ‘7 - ¢ - . .. .. . . ... ..~ .. .... u-...a..-.~ ..... ....... .....«.-...- ..- .a..... o . .. ..A. ..u. ... ..v.. . . .. . .. .. - . . . . .l.. .. . ¢ . . . . . o - a . . . . . o o . . a o . u . - 4 s. \ . . - .v .- . .. . . .‘ . n. .. .. -. l. . . i , y. . . 4 l -v. - . ... ., . . :r /. A v .. 1‘ H ,4 ‘1 ,. l _H._.—-¢._._—._-_.—-__———_~_~——.—— Table 31 (cont'd.) 1-- —-fiv———-—..-—-----~—_—«—————-—————.———~-—-—.—-.——--———--———-———-—-———-——-————v——-~——--~——---—-—~——--——-———~--——-——~-———-———---————~--—«-o—— ———-—--—-———‘ V f A J 7 7 7 2‘ ) I 7 ' ' 1 K _ l ._ . ,_ A. l g _ - l c c K A) Z > V 7 V‘ A I A I A J I I . .i _ A) A. . I I ‘ .A A l x r l r A .A A r I | . * ' I . w h 1 AA 1 I A f w _. h I "a A ...........-.a-uoo..cu.-...oa..o..........A ....o... ... I ‘1 If]? ...9‘....'..'....l'.l...’.....l..llI’IP'. .- 9c :. A: ‘ ... .‘.-...o.a....4..-.....o....‘.4A.. .... ..-... A.. I ‘ ........A....................... . ...AAAA..A. ._ A» ~..A...... I ’I‘f :---...-.n~n-o...--.. uav‘-.ooA... ...I. A .- A A. A O¢I.lfl \. .....A.........................A... . . ..... A A. .. ..A.. I ............................A......-....A.. . ...-A..... . ...A......... I ,x. .................................. .............. ........... ‘05 I - IIOII‘......II-l‘...‘IODOOODIICDDVIDIOOC‘I¢|t9l'0‘...q'¢9 ..‘l."n..’.l’.... i ' I - ......‘II...O.I...‘I‘.II...I.'...IC~....-iii.........l'lh..".vo...l‘4.l.lil w ...........A .................A..A..............A....A,.A.. ..A....A.A...... “In I ....ILOIOCII..IOCIOOIIOIIOIIQ.....lljhvfiv .‘I.. l ‘epII~‘->- ‘ u..I...Ch.D. I A................... .............A.A. . A . .. ..A.. W I I-O y-AlIl-‘IO...-IOIIUIDCDIOV...-I ...fil'll . .0 4- by . 'o-n I. Il-VII I '13....IIOIUIO'CCICIOOUUIIIODOQDIOfiGUI-VIII."U l..l.\i I 'C'O.r-‘V‘IC.’-I~U’OI l ;..........-..u a-----«-.A-~.ooon»c..1~- .«.---‘--A-.-A- ~‘.- A. r ...-u... [\i’. I l"V'.C."..........'...-.""".V".“I"'I'I'-'- l-I‘l.‘ Iv--‘Ifll‘4‘l.u~|.‘l I A.A...... ..A...................A.......A . ......A..A-... I A‘ “F I I. l|.wlcolfiyll0CI‘Q.O-....IIOOIIII. JOI.--4A.q I ...A...... ......... ........... I A .................................A......A AW A . A ........A..A. I I OIQCA.¢I)VII¢I.00....IIIIIICIIIODSOvaOOIIO' I. I Obnrlfil u n; I: .u..vo...p:|. I .... .A..~........A.............A... ... A A . . .. .. . A . ........A. I r ...... A. -.,.....-....» .. .... . .. .A A A .AA. A ..A ... ...A I'w I ‘A 74’ I C'I.’Il~l'.ll...0lII.......CIIOIODOIDSI‘C.'I‘.I 4."‘I¢III‘£IDoIa-MOIIOCVIID‘I'I AA... ................. ....A...A..... .A AAA ... ,A . .. , ......... I ................A................A..A.A . .. A A ........A. I A. ... ... ...A.......-.---.. .-.A\n....~.. .qr A. A ... A . ,, ..A A ...A..A...............A...A.........,......AA .....A......A .. . ......A...... I 1 .;. ... ...At.-............o....a....A.-:. ...... . ..A. . A ...A. ., . 'u. I ‘A tth~lnnuc~'llih‘hlulblII-Ollllvl-IQIIn-n--~ h~nu3loA nib . . O ‘1 ‘h-{I‘ I ... . .. A ~...-. . ..A~..~..v‘o . A A . . .. A A . , A..... .u.s.-.. o.-- . . . . I ..A. AA... . A ............ ,_A, A.. A ... .. . .. ..A. .. _ I I A...A..-.... . . .,..A......,.‘ ---.A... .. --- .-....,,..... - .--. .... A v ......A~. ....»-~..A ....AAA. A A. - . A. .. A... A v ,_ . ... . .. b ..A.. .... A. .. .A . . A . A. A .. . A A .A . A A A .. A . ..A‘ .... .....ndl ‘ ...¢. - ..‘u \I--‘ ' v v. A I J r . ,. .. .. . .... . x .A «_- A .. .. A. . .. I I ..AA .. ~...».... .A.. . ... . . . .A.. . ' I ,» ........ «...-.A. ,A...... ... .... ...... A. .... A. » \. A.. . ...A.A...A............. ...A-........ v .. A. .A .. AA .A AA..A...-A.. I .A.... .......... .A.. .. A... .... .A . A o- ..A.. I _ I- I ... ... ....... .A . ...... .. .I .A . .,» A A . A..... . . A. .. . . . . ‘ , . .A A. A _, ... I .I..A ...A. A .- . A ... ....A—.. A . .. A A. I I .A A. .. . .A...AA.. .. .. . A A ‘ V . A AAV.A... ...........A. . A. A A....-~.A ... .. ....on......-. _ - ‘ . A . A AA .A ... ..,...,..A.... I...........A ,. . A 7 . I ...A-....u... ..AAA.... ...... y.... .A . . . . AA . A v ...o-u......vu .........u...-o-u..,...-.-4A.-..... .. -. . ..-l. A I lh.l'B...‘I..II..'.'..'..I...'II.I.‘I‘.I.l' 9 C-1 ~ A.. ~ .. I .~......-.IA.-..o.a............... ....--. A‘o .... .. .7 . A. .... A v "..A.A......A..............u......-.~.. -. A. - ~. . . . . . . A | I I ... ...........o....u.-t..o...o-A.A... ..,;-.. . .. . A. . ..,,, . ‘ ........ .. oc-o-»...z¢..-.... ...-..A . ... . . .7 . .. I ...A.........4...I........-.. ...- A A .A I A I .A ...A ‘ l ‘ ... ...........o..:.......‘-..........A .. . A . . . , ...... . I v poQAa-u-‘IQ—vlvfio»4-lvooa-.1.'.'¢-...- - .A AA . ,,,.. . I v , A.___.v.-A~AA- 7 ‘ . rvr 77 ~ ~ 7 ~- —-—~ - - - -AA AA A. _A ..- ---AAAl_,__--___-. 293 Table 31 (cont'd.) A A t I‘ ' Ir II I AAA II I‘IvH I. A ‘ 5|.tlr III I A a M“. IAJI‘II‘ I'. A/ Ir‘vm A A'IIAwI.’ -7.;,. ‘: .‘M‘Ir' I . 1. r I‘.‘ ‘I. "J. ’ L.“ AfirAILII‘ .A‘.-'AVJ AA~.| A*>"'-I .7 WA >"" 'Jl'l“& 7“ ' A: I . '1. ‘~~ *IIAA, uI., .AA I A I‘ 'I . . .....u... I \ DI‘ ' ‘ . BI‘I.» .... .... L". Em‘. «..A-A. «A . . . . . . . . . I'L'ida'n‘fn‘fd '- 294 Table 32: High Property Tax Revenue Loss, High Development Cost, and Low Aesthetic Index Table 295 32 (cont'd.) fiAP ZboSHEET ZICATA SCI 1 I I I 2 2 2 2 A 2 2 2 2 2 2 2 2 I 3 k 4 k 4 6 I. 4 h S S 5 5 | 9 F 3 9 5 6 7 8 9 0 2 5 7 l I l I I a”? 807 I | 1 33b 800 I I l 5“» 8C5 I I 1 80‘ I I l 1’i 803 I I I I I v 802 l I ' I ”01 I I I H00 1 I I III 799 I I I lvfi 798 I I 1 7,7 7»? I I I 74A 796 | I | Iv: [95 I I I la; 1 I I I l ’1; 793 I I ! ,, 702 A I I ’A I91 ! I l I 1 I. vqo | I I l I I I 789 l l l I I I I‘A IUR I l I I I 1 AA/ 157 1 l l l I 1 I' no I l l 1 I I 7. 755 l A l l l l I'- 754 l I l I I I I 783 I I I ! I l IAA, 7:12 I l I I I I I . 781 l I I l I I I4- 760 I | l l I I l 1 l l l I I l I l l 1 l I l . Hm r u I n I ....ummuuaua.. 1 z T w wt. “— Table 32 (cont'd. ..AI. cu ..- . . . l ¢ I o . , . . . . , I - - - - . I ( . a v . « . r . . . o . . . . . I a . . . < . . c . - . . , - . . 7 c . 1 o . I l . I . . I . . . . . . . .4 _ . u . . I . . I . . - . A . ~ 0 . u . . . . . . . r | , o - . . . , . .. . ’~ .. . . v A u n o » a l . s . . n . . . c - . , I I c u u ' , . . . l . I. . . - ”I. Wru‘.‘ ... ... .I, .. ... ... ... ,.. ... ... ... ... . . ... . . n u , o - t . ’ . o u o . . , . I\J j I L ., I, v ... ‘ ... ... .- ... -‘.r.-OI ‘...- ' . .. > u x .... I . I , ~. ... , . -.- -. .. .... .0...- o<.I-....a. In. a... ---I- . . ..AAI. . . . .. --III . I..I .. . . .. .. I ~.. II I‘VI . . . ... . . c . » . . ‘ K ~-, I. o .. .I .I. I . .. , . .. .o ,,. I .. v I .- .- ;o .. n. o. .. I. u. a. a . . ‘- . r u o u ‘4'. 1 _r__.__._---~_ -| I III I “.LI‘ I" I I ‘ I 4‘ I I, ' I “ ‘I -_——___—_--—_—-__---_-. ...—1HRHh—.__._-_H~_._.—H__H4.—._.—~.__._HHH—__—-.._.—__.__ _..._. Table 32 III I l ‘H II,-,I - , L II II ,I I II\>‘I, .“ ‘_I - I I.“ |[ I- I II I .lI I IIIII- I'E‘I VI'WII‘ I‘IIIII I-v a "I'r.'l".lr'.'..:flml3‘ .... 0.IIEtT 2.:nTA St.[ 1 I . I I r I . I I I . r . . l I I I a l l I I I I I a 1 v . , I ‘ D v I . A I . l I , I . t - . L I , . . . I . I I F . I - I . I . I , I I I I I I I I A I L I . I . I 1 I I I l I I I . ‘ I . l . I v I o I I I I I I I . V I l . I I . l - I I . . I v, I r | I . I I . I I . . . I - l C . l I I , I I I . I I I I I § I I ~ I I I . I I I I I l I I | I I . I I . I I I I I I I I I ‘ , I I I I . I I I I C . I I . I I ~ I I . - I I A . A I I I . C . I . I I I . I I I I I I I I I I I I I I I I I I I U I I v I b I I a I I I I I o I I I b o I . . I I I I I I . I I D I . I , I I I . . I . . I § 0 V . l I I I n I t I I I I I I I ‘ I l I I I .. I I 4 A ‘l I ' I - I I I o I I z I A I I . . « I I l I I .. . I l I I n .. I . .. I \ L. I . ~- I I I . 4 I l I I I I I I . I a 0 I . . A I ‘ , I . . I , . . I I , o I . _ I , I - I I I . I I I - r . . I . - y l - . 4 . . D I I . I I . . I , . . . 4 4 I . I I I I I I I I I I I . I I l I I § I I I I I I Table 33 (cont'd.) . .... . ,.... I...... ....h....... , ..-. , .~""~““|‘.... ll. ltlfhufllo-‘O IIOOCI .. ..-..... . ; ... I..., .... . .. . . A . , ..T .w. .. ... ,7 m ‘ ..v ... . . , . .... .. .-I». ...... ...... .Ihl ltad'! - '01... ...-...... ... .- . .. . ...... ,. .... ...... .... . .(I .... ..‘. , . ‘,... . I ,‘ _.. . . A. .... . .. .1.-......-..\-.... ... ,... l. , ‘ .t.. . .. .......... ...... . ,I .... . ... . . .... ,. . . . .«I‘ ..,... ... ... .. .....~... ,. I. .... I-I‘\'\ I... 2 ........}C.‘. .. . .. 4.......L'-1_s\ .. . .. . ... ,~ I - ....-.M...t. . .‘ .....‘J._ ‘ . . ' A to: I I .‘ I .. I‘, ,- I. I. l.’ ,I I 9. l . I. l I 0.. I h Htv't 300 Table 33 (cont'd.) q__.._____ , .IIIITIIIIIIIIIYIIIII .[I1IlIIIIIIIJ.JI TIETIIIJI.I.1T.III,.IJI1|.III.I IL .lv\\, .II 1.. I III I r . II I I II . I I7! I. I I I II I . II II I I II I. I I I I II . I. I . II a .I ..I .4 II II III I I. .1 I I I II. II .I I I I I . I I . ..I a I . , . .I I I . I III I I II . . I . 11 I I I. I . . I I . I . I III I I . If I I. I I . I I I I I I I .I . .I I II I I. I I I . .I I 4 I I I II . I . II I I . I . . I I. I I I. . I w In. I I .. I II . I I I . I I I I I I I A I II I I. a I I . III . III I I . . I I I l 1 I I I I . I . . I . I . I .. . I I I I. . I lllllL I L I 301 Table 33 (cont'd.) 302 Table 34: High Property Tax Revenue Loss, High Development Cost, and High Aesthetic Index my l—---—_-—-_-_--———————..--.._——»A-»fi-_— .V‘ ‘wl 37.3HEhT ZVEATA 3&1 v .. , 111 'v 1 v . . v . a . , . o n n . o . - n a n . I . _ s v t , . o o v ) r u u n n c o w n a v . . s . n - n c . . n . ‘ . I ~ . u v . u r o o c a . n . . o . . o . . a . . . . ~ . i n , . , r a A a n - o . . . . ~ . . u u . o . o n o u o c ‘ n o u o I o o o . n - o v a a , o o n r . o o l u o I a 0 4 I v o o o 3 o o . o o u o o n . u o o u o a u o - o - . . . . - n n ‘ , a o - ~ 4 . v u . . o o o i u . . I u u n n . . . u o o . . . r o . , . o . n u . n p r . u , ¢ . a . 9 . u n . . o o s o o u u o v o . u I n a o o o I a I . o o I‘J a o v . n u o o i o c . a I o b - o a u . a . t . . . (- I o . . I o x t l n a - . l n 4 4 o . n I u v . . . a u r . , . , v , u i . . v i n o . a . ‘ . . . , . . u a o o I .. a . u - u . , . . u a . a i o Table 34 (cont'd. __-__-_.__..-..--.. --,--_----l---__i--_~-__-----fi ._.—<.— R f‘ 7 a o o v o o p n. I I n o o u o . o o o o s a o n o a O t a fl—-——I—-H——w-——u——-—>~M.—— A..‘ ,~ .... A - ..ovctiva , A! I )5 II‘ l*- '3 ‘ . . , v ......~ \ i. ‘7 ..... .1..‘7 .......» l nun-OII-z\b-nrn.unn‘o>-‘OOOOOI "‘ 1 .I‘..<'II.IIIII.‘¢IO> GUI-I... I ...r....... ......~........... 1 “ ~.. 4...... ,7 I l..... . . ~. ~. i ......i.........i.........., . l . ..i .3.“ . -‘ | {........‘.,..AK.‘,-....-~. I ,. m... .i ... i I _ , .- ,ra . o .I I v r , . ....v-‘» z-Q.‘ a I . l .. ,. A . , . . .. i .. .ev.‘ .. -. .. .‘ . I ‘..~~. ..~ .. . ~.. A v i. .: .i. ! 'r'III ‘ .--4 ,u. no Ilvio " I i 1. Cu... Ari .- II! A ‘ . ..,. . . a .. ,. I r ......h.. . , .......i.. , . .... . .. , . . '.o>. t.' u . . - l I wil-vyl 1. .- ‘.. ... .-~.9 ‘4 . ., M W , .... l ,7. . ....¢.................-........ .«1 . .....«T ...... . r ., 1 ~( '-.. o A ~ . ‘ -4 .~ .-.- .. -. I . ~ . V . . t I . .. ,‘ ,7 . . nClfl.'l..n";r ‘ - ‘ l‘ l v.;'..‘ .. ,. i.‘ . l 1 ..ru.n 4 viva C». ‘ . I1'v-'- l :L I u up) .I 9. .II, I ‘1 .... . . . . . I ‘QG . - . . 4~ 1 , . A .. l ' \ ...A......... i, . . .‘ I .......... .. . ,.. ,:_ . 1 ....,.'........- ...- .7 .' .. ................. .\..> . .- ... .‘.~. .... . .......h.. .‘ l .. ....,A...................‘. I ..... ..i. ...~.. .~..... .. l .; ..fl. .. ... .i. . ... 1 ¢-,...'. :1 - . b v arse. .- I . ...‘........ ...V ..-... . ,. ....... ..i . . .. .. .. I ‘ J ' i Table 34 cont'd.) Iw' ZTI'MItEI II'H'II': I. ;-_._-.___._-___-_----, v-__-_-_....-_,-----------.._-_-_-___....--—-_-__-__---_-___--__-_—--- 4__-..___..,_-___*r‘ru _.......w..._..__._._—__..._.._..- H m p I I I I I . . . _ I I I ' I I I I I OOIOI‘CIIO‘IOIIIIOII...IIOVCQCIIIIO-IIUIIIVUIOOV‘IQIIO I. 1 I ‘I y‘flf I.OlibvtiooooooluoaiOttcaDI-OQiOCII-Alubllbuj~lycbltlv4bn , I I.IISIOOVCIOOCIIIII.ODOOOOCUICIOOlltflOi.|‘¢lvQIIOOQIQJ'A I I .........I.....-..a..-......I.. ....I......I..—...... o..4 . . .,. I.“ I . u . ’1 It‘ll-IOICDIOOIIOQIIOOIOIUOUIQAQCOII.Illa ......uoo.n ...A...-. I“.... I H ...... ........4-.......... .4... ...... ~.. ....» . ..V .,.- :., [ . .t—IOAC-llthovltuotrInna!ItcolI-lI-v I-g.uu.-I-oo,.as.--aoa. D‘-o’-I.IA’C6D. I I II g1". c....-oo«.-I>.~I.I...|t IIIOOOO‘IIO'OOlo-I -.oa.-I-. ..4. n. 4... 0001- II IIV I nouI-I'IIIIII....ruaauvuoIoIII-II-II.aI-..I...II-oIon-II.-IIII-~II.I~II~n-»Iv-OI I I OOICOODIIIOO.Itol’lIIIhIIIQCCOIHIVIIFI‘I‘IQOLOld ODIOGIhOILu|~ .Ia..~.ua¢a-ao-. I I “ ‘ (..A....-;~.II. .vv u~ ..-.. -. -.4p.. 4- II... .,.. .4 II<. cuo~.n:I I' I I rIl-oooli4dl--.AII .n-.I~ ,._,..I .....I .«. I, I. ...IV . . .7 I .I4.... ...... . .... . . .... .~ . .. , - . ,...... . .... . . .4..,.‘.. I I I ur -- .... ........o.-.I--.II I..I .. .,,.. ,‘an 4I. ..4 . ....I... I j I , . ...-4: I. .n- Ioo.~....I-..I........ II..II.. ~.... ... .-I... .I........ I I ».I >........ ....I I.......¢I~- . 4... . ........ ...I. , _,.... .,. I ................. ..... .... ...4.,. 4I.. ... .. .,,..... . ...,‘.,. b I .. ..I....................‘..I.4 ... ~.... ...IeoII......... ....- .... I ,._,,..I.. .......-..,,..,......I.I..... ........I... ,II. . .. .....I..- . I ... ................-.................a..4 ... .v.I-I.,. .-.I ... 4.., “LII I I ....._I...-.................-..-........ I... .....I.;.....v..... .. . .,.. I ..4..............\........IIII....I...» .‘I..........o- .... .........I..... I I -tI-a-u-oIoIIII-IIIllnI-coIoI-III COIDOOOIOC'Q...’l'lo.'tlwilll"l‘IIDQOOGII ‘3‘){ I I I DIIGIIIOIDOIII'00....OBIIIIIIIll-IOICOIICOOCIQI.IIIIIlsa-OOIIOIIII-Ol.tkdll§ I I --I--I-ooI-o¢.au.uonnag-Iout-Iaolouuuoa-IlnncoIIowan-novoIo-III..iusoI-vn-II I . II' ll1§IlelJICOOCIFU‘ICO‘CIOICI’IUG.O'A‘IDCIIIJ I..IIIIQ'III'II‘1.'I\ .p..-aod:n ’4‘ I ‘ I IO.O‘ODI.I9..-I|-lllDIOCltulcaOUI ......4.. 5‘.- .«vv- -A.IIlIl.-Il . ...,..,,., ‘ 4....V.......I.... 4.......... ....Il... .. 4 . ..~. I.. . ..- ......... I 1 I4 _ .7.II .« ..I.... ..... I. ~I....I.«....I...I .. .. .. . _ .. .. ..... I: I I .4.. ....I ......I....I.......I.¢.. .,...... ,. I ....-4....;... ....4 .I... I _ .......-.............~.............I.~.I...>.....I..I.......,I...... .... I...~.. I I ‘ I’ 4 ......I......-.....,....., ..........»I. . 4‘.. M. , , ...m, I j I ...........................-...........4.. .I .. W. 4. I ....- ..............I..........~,..... ..HW ..... . I I I II ...1.......A..............................v . ..I..r....,4..._.. . ..I ... H4 I .. I ....I..................I.........-_ In», --I .I .. . I..... ... .. .. .. I I .... ..IoI-I- Iv..a...I....-.....c..u...--~. I‘u‘..ll‘l 4~§l.~l-.‘ l I... .,.. I ...... ......a I............I. ....I... ...AuI—4 .... . . 4. .... ~ I~' I .4................I...... ............I..v ....I 4. 4 .. .. ..... I ..A..4.....,.........‘, ...... ... .4 . . -.. . ...I I I .......4I.. ....I.......... I. ..~...4. I.....r . . _ . .. » _. ..I..... K' I A .................,..4....A...-v...4 ... .... MW. 4‘ .. I .A...V..............I.._,..,-...I..... ...... ...... .‘ ..... . , I . ...... ..... I. ‘I. ... a. ..... I... . .~ 4 . , ... . ....‘ ,, ._- .. ...4 ‘DV"'4tI .4.. ~- . I . - . .I I ........................I........... ..................I.............. I 4 I I -III*BC-I.....“'..‘.."‘-’......"‘-."0...‘HI’d'lyll’y1‘.£I'll~lklb‘tl'gv ... ..IIIIInn-IIn;....oa...»v.u.usan.cao»n--u5a-n...-u .....ho... .IJ—IVII ~~..... ... I III-.. II'Ial‘DollhlollIIAOOt§...IIOIQ¢‘ I I'.I . ... . I ..-.,I I I V“ _ I‘I vu-o.V'I'Ddoo.il...-Q...IIOIIUIUIIIIDIIIIIICIIIQIOIIOOIOOOJVIUJI vvlfl-IDIOIIO§.IO I I I I .....r................I........I........ -.a...,‘ M.I..-... ..... .. .. I... I I tt-Ipll'IOOifllibobltI'rltslllll'fi-DIIOQOOOJI‘O---II-Ilrlfi~~0-<,I r.- -.".I"' , I. 4 I .....,......I. ..........4. .....I.......I....\... ...I... ,,...,I.'.4‘. .. ...I. II I I ......I;.......4..~....I..»~.II....I»,..I....... ......I ........ ... ... I 4o I. I . .................,..................... ..... .I..4.4.4 ....‘..... I v‘ ......I..:.. ......,.................4... .... . . 4 .. ,. iI I .. ....I..... .. ... .I ,. . ..~. .4 ... ., . I -. ‘ n ‘1‘. ¢.- I.I‘~-AA~4D'A‘*.AIIII| -<. ., . I A I I ., . I A- .I. ... .. .....4..-- .-.»-.n. . I'lv ' I . I. . . II . I l ... I‘“ A I . II ...I... .I I -Iu...I.. .......~ 4. 4. . .I.....47I......~.. fil‘.‘ ,.~......I...... ». .. . . . I4 , I . I II 4...I.......................................... ........... .. W... I... 4 I Ina.A..-A.......o-no-nonuooo..-sna..a.-..o...... u.........‘ .A. I. ..I..I I-I, I A.IIII.AQa-Qlldl.be-IIIIIDIQ‘QDHDCOIIl-‘t.vlh I . .......-... .. . .,.4.._, I 7, v I I ~DIQ-IGODCOIIO.I..’ III-I aO-Ioto.u..«nu~ I. III‘I lx-J‘.1..I‘.‘;.x r . 4| 1 "‘ .‘xllW‘ \‘l’ I" "I, P ji/"“}‘J’{ A]. :.\rl:‘1 i LWT‘11F‘11 N'y. "M ~ W’r‘ti i' -‘ JILL, MM?" «1va ml. H) r ‘.I i. ‘ ”ri‘uJ 2 “ '-l ._ . . . A}; ,5? ..t) “(LHIPLI‘I(1‘I ‘W‘kLVl M‘ ‘ ' ‘. x ‘ 31“ J .I, lg F ? ‘r 11‘:_ ,llrI‘ x‘ . ,[ Aky| I “‘n ‘Or I ""H‘JvL’JuV Jlbl‘lrfi'ullfw v {515HIUTvulwufl ::.H ‘ .‘l Ln“ 2er9 “I‘m HAL” ~ . . . . . . . . . ’w .itkLKwAAT-fi ..,.‘.__..* 5"“:- v . . . ¢ . 4 4 . >‘.’.-‘