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Problem s enco u n tered with this do cu m en t have b een identified h e re with a check mark V t. G lossy photographs or p a g e s ______ 2. Colored illustrations, p ap er or print______ 3. P hotographs with dark b ac k g ro u n d ______ 4. Illustrations are poor c o p y ______ 5. P ag es with black marks, not original 6. Print show s through a s th ere is text on both s id e s of p a g e _______ 7. Indistinct, broken or small print on several p a g e s 8. Print ex ce ed s margin req u irem en ts______ 9. Tightly bound copy with print lost in sp in e_______ 10. C om puter printout p ag es with indistinct print______ 11. P a g e (s)____________ lacking w hen material received, and n o t available from school or author. 12. P a g e (s)____________ seem to be missing in num bering only a s text follows. 13. Two pag es n u m b ered _____________ . Text follows. •4. Curling and wrinkled p a g e s ______ 15. O ther__________________________________________________________________________ . co p y __ 1— University Microfilms International IMPACTS OF A REGIONAL HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEM ON SMALL METROPOLITAN COMMUNITIES: A Case Study— The Lansing Metropolitan Area, Michigan By Shun'ichi Hagiwara A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY College of Social Science 1982 ABSTRACT IMPACTS OF A REGIONAL HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEM ON SMALL METROPOLITAN COMMUNITIES: A Case Study— The Lansing Metropolitan Area, Michigan By Shun'ichi Hagiwara To date, the intercity passenger in the United States has principally relied upon such transportation modes as the automobile and the airplane. However, progressively worsening energy resource conditions have made future dependency on such liquid fuel oriented modes of transportation uncertain. The necessity for the development of an alternative transportation mode for the intercity passenger travel market has become increasingly apparent. One alternative mode, the high-speed, intercity passenger train system (HSIPT), could be the most appropriate answer to such a need. The research for this dissertation was undertaken to examine the probable impacts which would likely occur if a HSIPT system were to be developed in the Great Lakes Midwest Region. The specific local area selected for this impact study was the Lansing Metropolitan Area, located in the middle of the lower peninsula of Michigan. Shun'ichi Hagiwara The methods utilized for this impact study were the models of "Population Potential" and "Population Energy." For the local level/ the "p-Mediam Problem" was adopted to assure objectivity in the selection of a site for the HSIPT system terminal. The "attraction-accessibility model" was used to analyze the probable impacts which would flow outwardly from the HSIPT system terminal site to the surrounding areas within the Lansing Metropolitan Area. The results of the application of the "Population Potential" and "Population Energy" models indicate that the communities of Grand Rapids (MI), Columbus (OH) , Cincinnati (OH), Kalamazoo (MI), and Indianapolis (IN) were likely to be most influenced by the creation of a HSIPT system. Other communities likely to experience impacts from the creation of a HSIPT system, though less dramatically than the first five, are: Detroit (MI), Cleveland (OH), Lansing (MI), and London, Ontario (Canada). The results of the application of the "p-Median Problem" and the "attractionaccessibility model" indicate that the creation of a HSIPT system in a local community will likely result in the metamorphosis of the existing urban area. However, prudent location decisions for the various HSIPT system facilities can minimize negative impacts on farm lands, forests, flood plains, and groundwater. ACKNOWLEDGEMENTS This dissertation research would not have been possible without the direct assistance of many people and my sincere apologies, as well as my grateful thanks, are due to those whose names are excluded from the necessarily brief list which follows. Professors on my dissertation committee to whom X owe a particular debt include: Dr. Raleigh Barlowe of Resource Development, Dr. Roger E. Hamlin of Urban Planning, Dr. John L. Hazard of Marketing and Transportation Administration, Dr. Robert I. Wittick of Geography, and Professor Myles G. Boylan of Urban Planning. They gave the firm criticism and supportive direction which were frequently needed to improve my dissertation research. My special thanks should go to Professor Boylan, the chairman of my dissertation committee, whose guidance, support, and enthusiasm during the past four years were invaluable. I should also like to thank Dr. Rene Hinojosa of Urban Planning who enthusiastically and patiently helped me to develop the necessary computer programs for this dissertation. ii I also wish to extend my special thanks to Dr. Craig Harris of Sociology whose constructive comments improved my dissertation greatly. There are a number of other individuals who have also contributed time and expertise to this dissertation project. I wish to express my sincere thanks to Dr. Etsuo Yamamura of the University of Hokkaido, Mr. Akira Iriyama of the Japanese National Railways, Mr. Bud Thar of the Center for International Transportation Exchange, Mr. William R. Enslin of the Center for Remote Sensing, and Mr. Jason Whittier of the Lansing Tri-County Regional Planning Commission. Also, very special thanks should be extended to my friend, William G. Marx, whose expertise in English, diligence, guidance, and criticism in editing and proofreading improved this dissertation significantly. Finally, to my wife Miwako and sons, Gaku and Tadashi, I wish to express my heartfelt thanks for the encouragement and love they have given me throughout the period of my studies at Michigan State University. TABLE OF CONTENTS Page Chapter I. INTRODUCTION ................................. Background of the Problem {The Issue of Transportation Gaps) ................... Research O b j e c t i v e s ................ . . . Research Assumptions ...................... Limits of the Research Scope and S u b s t a n c e .............................. Research Methodology ..................... II. NATURE AND CHARACTERISTICS OF HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEMS ........ State-of-the-Art of High-Speed Intercity Passenger Train Systems ............... The Roles of a HSIPT System on the Development Process {Case Study: The Shin Kansen and the Japanese Development Process) ................... The Phased Development of the Shin Kansen and the Japanese Development Process ................... Role of High-Speed/ Intercity Passenger Train Systems on Human Contacts and Transactions ............................ Positive and Negative Aspects Inherent in the Development of a HSIPT System . . III. PROBABLE IMPACTS OF THE CREATION OF A HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEM: THE GREAT LAKES MIDWEST REGION - A CASE S T U D Y ...................... Development of the Relationales for the Great Lakes HSIPT System Corridors . . . Concepts of "Population Potential" and "Population Energy" as Indices to Measure the Magnitude of the Probable Impacts of a High-Speed Intercity Passenger Train System ................. iv 1 3 9 10 15 16 25 25 37 44 63 80 86 86 94 Page Magnitudes of the Impacts of the Creation of a HSIPT System on the Forty Local Communities Within the Great Lakes Midwest Region .......................... Changes of the "Population Potential" of the 40 Local Communities Within the Region Before and After the Creation of a HSIPT S y s t e m ..................... IV. PROBABLE IMPACTS ON A LOCAL COMMUNITY DUE TO THE CREATION OF A HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEM WITHIN THE GREAT LAKES MIDWEST REGION (CASE STUDY: THE LANDING METROPOLITAN AREA IN MICHIGAN) . . . Probable Impacts on Rural-Urban Structures (Impacts on Land Uses and Land Covers and Population Settlement Patterns) . . Concept of Accessibility to Analyze the Relationship between Transportation and Land U s e ............................ Attraction-Accessibility Indices to Analyze the Population Settlement Patterns in the Lansing Metropolitan A r e a ............... 140 Accessibility to Shopping Opportunities ........................ Accessibility to Employment Opportunities ........................ Accessibility to Urban Functions . . . . Concept of Per Capita Accessibility: How Does It W o r k ? ............. 160 V. 104 110 123 12 3 133 14 6 150 153 IMPACT PROBABILITIES FLOWING OUTWARD FROM THE SITE DESIGNATED FOR A LANSING HIGH­ SPEED INTERCITY PASSENGER TRAIN SYSTEM T E R M I N A L .............................. 172 Development for the Rationale for the Site Selection for a Lansing HSIPT System Terminal ....................... Impact Probabilities Flowing Outward from the Designated Lansing HSIPT System Terminal Site to the Rest of the Lansing Metropolitan Area . . . . v 173 184 Page VI. SUMMARY AND C O N C L U S I O N ..................... Summary of the Research Findings ........ Regional Impacts ........................ Terminal Site Selection Impact ........ Local Community Impact ................. C o n c l u s i o n s .............................. ......... Suggestions for Further Studies A P P E N D I C E S .................................... BIBLIOGRAPHY ........................................... 201 2 01 2 02 2 04 208 210 214 A1 222 LIST OF TABLES Page 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Transition of Socio-Economic Characteristics ........................ in Japan (1960-1980) Population Changes in Five Regions (1960-1980).................................. Population Changes in Sixty Cities (1960-1980).................................. The Fares of the Shin Kansen and Air Modes . . 1959-1979 Domestic Share by Seven Different ........................ Transportation Modes Transition of Demographic Influence Due to the Shin K a n s e n .............................. Number of Passengers at each Terminal of the Tokaido Shin Kansen (1972) Population Potential at Each SMSA Based on the Time—Distance by Automobile at b = 1.0 ... Population Potential at Each SMSA Based on the Time-Distance by the HSIPT System at b = 1 . 0 ................................... 113 Rates of Change of the Population Potential after the Creation of the HSIPT System . . . Population Energy (Energy of Interchange) at each SMSA Based on the Time-Distance by Automobile at b = 0 . 5 .................... 117 Population Energy (Energy of Interchange) at each SMSA Based on the Time-Distance by the HSIPT System at b = 0 . 5 .............. 118 Rate of Increase of Population Energy (Energy of Interchange) after the Creation of the HSIPT S y s t e m ............................. 119 Nodal Accessibility to Shopping Opportunities at Township Base and Statistical Relation­ ship between Accessibility and Population . . Nodal Accessibility to Employment at Township Base and Statistical Relationship between Accessibility and Population ............... Nodal Accessibility to the Urban Functions at Township Base and Statistical Relationship between Accessibility and Population . . . . Nodal Accessibility to the Urban Functions, Per Capita Accessibility to the Urban Function, and Per Capita Income (Township Base) .............................. vii 47 52 54 66 71 98 100 112 114 14 9 154 158 162 Page 18. 19. Name of 4 8 Township Nodes, Their Cartesian Coordinates and Weights for the "p-Median Problem" .......................... The 192 Nodal Accessibilities to Ten Major Urban Centers (Urban Functions) in the Lansing Metropolitan Area ................... viii 176 189 LIST OF FIGURES Page 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. Transportation G a p s ............................ The Great Lakes Midwest Region Configuration M a p ........................................... Configuration Map of the Japanese HSIPT System (The Shin Kansen S y s t e m ) ................... Ranked Potential IPT Corridors (From Market Potential Analysis) ................. . . . . Ranked Potential TLV Corridors (From Market Potential Analysis) .......................... Grouping of 46 Prefectures of Japan based on the Phased Development of Shin Kansen . . . . Center of Gravity of Population in Japan (1960-1980) .................................. Four Old Industrial Zones in J a p a n ........... Transition of Wage, Number of Automobile, Price of Automobile, Consumer Price Index, Air Fare, and Rail Fare in J a p a n ........... Share of Four Transportation Modes for Five Different R a n g e s ............................ Four Possible Intra-State High-Speed Rail P l a n ..................................... Ohio Intra-State High-Speed Rail P l a n ......... Preliminary National High-Speed Ground Transportation Network (Part) ............... Geographical Distribution of SMSAs1 Population in the Great Lakes Midwest Region ........... Proposed Great Lakes Midwest Regional HSIPT System The Planned High-Speed Rail Network and 4 0 Local C o m m u n i t i e s ............................ Location of Nine Major Urban Centers in the Lansing Metropolitan Area Location of Major Agricultural Lands in the Lansing Metropolitan Area ................... Location of Major Woodlands in the Lansing Metropolitan A r e a Location of Major Flood Plains in the Lansing Metropolitan A r e a Location of Major Groundwater either Sensitive or Developable in the Lansing Metropolitan A r e a ......................................... Possible Locations of the Lansing HSIPT Terminal and HSIPT System Route ............. ix 4 8 30 35 36 45 51 61 69 72 88 89 90 91 92 105 12 6 127 12 8 12 9 130 132 Page 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. Population Growth During the 1970's in the Lansing Metropolitan Area ................... The Federal Land Survey System (The Rectangular System) .......................... Locations of Shopping Opportunities in the Lansing Metropolitan Area and the Levels of Attractiveness (the Amount of Retail Sales in Thousand D o l l a r s ) ................. Locations of Employment in the Lansing Metropolitan Area and the Levels of Attractiveness (the Number of E m p l o y m e n t ) ........................... Locations of Nine Destination Nodes (Nine Cities with Population More Than 2,500) . . . Distribution of 48 Townships' Nodal Accessibility ................................ Distribution of 48 Township Nodes' Per Capita Accessibility ........................ Isoaccessive Contour Lines Based on the 192 Nodes' Accessibility to Nine Urban Centers (Urban Functions) ............................ Urban Area in the Lansing Metropolitan Area . . Geocode System for 4 8 Townships in the Lansing Metropolitan Area ................... Geographic Configuration of Ten Urban C e n t e r s ....................................... Locations of New Lansing HSIPT Terminal Node and the Existing Nine Destination Nodes . . . Isoaccessive Contour Lines Based on the 192 Nodes' Accessibility to Ten Urban Centers (Urban Functions) ............................ Concept of the New Urban Corridor in the Lansing Metropolitan Area ................... Probable Land Uses in the Lansing Metropolitan Area due to the Development of the Lansing HSIPT T e r m i n a l .............................. Influences of the Development of the Lansing HSIPT Terminal on Land Uses in the Lansing Metropolitan A r e a ............................ Profile of the New Greater Lansing Area After the Creation of the HSIPT System Terminal in the Lansing Metropolitan A r e a ........... x 141 144 147 152 156 163 164 168 17 0 179 185 186 190 193 194 196 198 CHAPTER I INTRODUCTION This study is an examination of the probable impacts on rural-urban structural change in typical local metropolitan areas in the United States resulting from the hypothetical creation of a high-speed, intercity passenger train system. The Great Lakes Midwest Regional Corridor, which stretches from Milwaukee to Chicago to Pittsburgh and then to Toronto, Canada was selected for this study's locale. A lesser local metropolitan area where the direct impacts of the new system are examined is the Lansing Tri-County Regional Area, which is generally located in the middle of the lower peninsula of the State of Michigan. The selection of the Great Lakes Midwest Regional Coridor for evaluation of the development of a high-speed, intercity passenger train system was made for a number of reasons. A high-speed, intercity passenger train system is only feasible in densely populated areas, and the Great Lakes Midwest Region is one of those densely populated areas in the United States, along with the Northeast Coast and the West Coast Regions. The Great Lakes Midwest Region has been troubled by a progressively worsening 1 2 economy. The development of a high-speed, intercity passenger train system within this region could be the catalyst for the revitalization of the economic health of this particular region. There are the plentiful coal reserves in the region which can be converted to electricity which would be the primary energy source for a high-speed, intercity train system. The Great Lakes Midwest Region (hereinafter, the Region) has a balanced transport system which is composed of highly developed, interstate highway systems, rail and air systems, along with St. Lawrence Seaway System. The addition of a high-speed, intercity passenger train system (hereinafter, the HSIPT system) to the existing multi-modal transportation system could provide another substantial mode to the regional system filling a currently unmet need. Finally, Michigan State University, where this research has been undertaken, is located in the middle of this particular region, and the immediate accessibility to the data and information necessary for this research i s , one self-evident reason for the selection of the Region for the impact study. The HSIPT system discussed here is a new passenger rail transportation system which is capable of more than 100 miles per hour average speed. Such a HSIPT system has already been developed extensively in several European countries and in Japan. It is being assumed in this research engagement that a HSIPT system has been selected 3 by appropriate authorities to fill the so-called "trans­ portation gaps" in the United States Midwest as described below. Background of the Problem (The Issue of Transportation Gaps) In 1967, Bouladon published a paper entitled "Transportation Gaps" in which he stressed an apparent lack of transportation concepts and technology to satisfy certain potential markets.^- Those markets fall within two different areas: one ranges over 0.3 to 3 miles from the point where trips are generated; the other area ranges over 30 to 3 00 miles from the same point. These areas should be covered by transportation modes that can travel at 5 to 15 mph and 100 to 300 mph, respectively (Figure 1). The optimal transportation modes for the former area (Area II in Figure 1) are bicycle, bus, and subway trans­ portation systems, and for the latter (Area IV) are helicopter, a high-speed train, and short take-off and landing aircraft (STOL) systems, respectively. In the United States, both areas have been primarily covered by the automobile. G a b r i e l Bouladon, "Transportation Gaps," Battelle (Geneva), April, 1967 cited from A Review of Short Haul Passenger Transportation by Committee on Transportation, National Academy of Sciences, Wash., D.C., 1976. Also, Gabriel Bouladon, "The Transport Gaps (Science Journal) EKISTICS, Vol. 25, Number 146 (Jan. 1968), pp. 6-10. pedestrian DISTANCE (miles) 0.3 0.6 1 TIME (minutes) 6.1 7.5 8.8 SPEED (m.p.h.) 2.9 4.8 6.9 6 10 30 60 100 300 12.4 15 17.5 24.5 30 35 49 60 14.7 24 .. 34.2 73 120 172 370 600 3 600 1000 3000 6000 65 96.5 120 670 1865 3000 Figure 1,— Transportation Gaps (colored area above) from the paper, "Transportation Gaps," Gabriel Bouladon, Battelle (Geneva) April 1967. Cited from A Review of Short Haul Passenger Transportation, by Committee on Transportation, National Academy of Sciences, Washington, D.C., 1976. 5 Worsening energy resource conditions, however, cast a shadow over the liquid fuel-oriented mode of transportation. Not only energy resource problems, but also recent national legislation such as the National Environmental Policy Act and the Clean Air Act have made the liquid fuel-oriented mode of transportation more vulnerable than ever. Further, the downsizing of the automobile has made longer trips more uncomfortable and unsafe. The necessity for the development of alternative transportation modes for these markets has significantly increased. Following are some examples of recent commit­ ments by the federal and state governments to the develop­ ment of concepts and technology for the notable "Transportation Gaps" described above. The U.S. Department of Transportation, through agency subdivisions such as the Urban Mass Transportation Administration (UMTA) and the Federal Railway Administration (FRA) , has encouraged research into, and the development of, appropriate transportation modes with grants-in-aid. Research studies evaluating light-rail transit, personal rail transit, demand and commuter buses, and subway train systems are those (among others) being supported for the market ranging from 1.0 to 10 or 15 miles from the point where trips are generated. and landing aircraft High-speed rail, short take-off (STOL), and vertical take-off and 6 landing aircraft (VTOL) are being studied for the 3 0 to 2 300 miles zone. Recently (1980), the Center for International Transportation Exchange (CITE), a "National Governors' Association Center of Excellence," was established as the first in a series to serve the governors of the fifty states and U.S. possessions and their transportation advisors to exchange experiences, ideas, and innovative 3 technology with other nations. Among the first assignments identified for exploration and service to states in an action agenda are: the states' role in high-speed, intercity rail transportation; state potential use of electric vehicles; light rail systems for public transit; trans­ portation finances and management for facilities such as airports, highways, pipelines, public transit, railways, and waterways, including ports; multi-modal terminals for people and freight as used successfully in other nations. Furthermore, in 1979 and 1980, legislation was passed in Ohio, Michigan, Pennsylvania, and Illinois 2 See, U.S. DOT, High Speed Ground Transportation Alternative Study, Wash., D.C.: The U.S. Government Printing Office, 1973, and National Research Council, Committee on Transportation, A Review of Short Haul Passenger Transportation, Wash., D.C.: National Academy of Sciences, 1976. 3 Information is obtained from CITE, "Center for International Transportation Exchange (mimeo)," East Lansing: CITE, 1980. 7 establishing the Interstate High Speed Intercity Rail Passenger Network Compact to provide an organizational form for cooperation in the development of the regional project of the Midwest Corridor Improvement Project. In July, 1980, the Ohio Rail Transportation Authority (ORTA), which has already invested over three million dollars in feasibility studies for the development of the "Ohio High Speed Intercity Passenger Project," released a report, entitled Ohio High Speed Intercity Rail Passenger Program, which concludes that the Ohio High Speed Intercity Rail System is vital and economically feasible.^ Taking into account various investigations, past and present, by public as well as private institutions, this research endeavor focuses on the Great Lakes Midwest Region. This Region ranges over parts of Wisconsin, Illinois, Indiana, Michigan, Ohio, Kentucky, Pennsylvania, New York, and Ontario, Canada (Figure 2). The total area is approximately 35,00 0 square miles and involves ten of the 4 0 largest Standard Metropolitan Statistical Areas (SMSA) in the United States, namely Buffalo, Chicago, Cincinnati, Cleveland, Columbus, Detroit, Indianapolis, Louisville, Milwaukee, and Pittsburgh. Toronto, which is ^The State of Ohio and Dalton, Dalton, and Newport, ORTA - Ohio High Speed Intercity Rail Passenger Program. Phase II. Cleveland: The State of Ohio and Dalton, Dalton, and Newport, 198 0. # Buffalo HEW YQRKl land_________ [Pe n n s y l v a n i a ] Chicago [ILLINOIS U.S. state or Canadian Province One of the 40 largest SMSAs In the U.S. or CMA In Canada OHIO IlKDIAKA • Pittsburgh *Columbu^ f • Indi inapolls j k * Cincinnati • Louisville KENTUCKY| / J |WE ST VIRGINIA | \ Figure 2.— The Great Lakes Midwest Region Configuration Map. 00 9 the second largest Census Metropolitan Area (CMA) in Canada, is also included in this region. If such a new, high-speed, intercity passenger train system were to be installed, roughly 40 million people including 4 million in Canada could possibly benefit from it. Research Objectives The objective of this research undertaking is to identify and evaluate the probable impacts of a HSIPT system if it were to be created in a particular region of the United States (such as the Great Lakes Midwest Region). More specifically, the objective of this research under­ taking is to identify the probable impacts on local communities of the creation of a HSIPT system. This overall objective is divided into three parts: first, the probable impacts of a HSIPT system on the local communities in the Region are examined. Second, the probable impacts of a HSIPT system are examined as a competitor (consumer of land) to non-transportation land uses. The probable land use activities in and around the site for a HSIPT system terminal within the prototype metropolitan region and the amount of land necessary to support such land use activities are also investigated in this part. Finally, the probable impacts of new land use activities on the rest of the regional area are analyzed. 10 Research Assumptions The research undertaking is based on the following assumptions: 1. The installation of a HSIPT system is hypothesized for the Great Lakes Midwest Region; 2- A HSIPT system corridor is assumed to be located so as to join 17 U.S. Standard Statistical Metropolitan Areas (SMSAs) and 3 Canadian Census Metropolitan Areas (CMAs) in the Region; 3. The Lansing metropolitan area is assumed to be one terminal point 4. A HSIPT system onthe Midwestern corridor system; is assumed to run on an exclusive and grade-separated rights-of-way (two tracks) to secure its safety and speed; 5. A HSIPT system is assumed to be capable of more than 100 mph average speed (which requires a maximum speed of more than 160 mph); 6. A HSIPT system is assumed to serve only passenger, not freight, operations; and finally, 7. This research undertaking simply assumes that potential ridership will be forthcoming, that the project is economically feasible, and that the project is politically achievable. The bases for the above assumptions are explained briefly in the following paragraphs. 11 The first assumption, the installation of a HSIPT system mode, is based on recommendations by such public institutions as the U.S. Department of Transportation and the U.S. National Governors' Association. According to their studies, a HSIPT system is only feasible in such densely populated corridors as the Northeast Coast between Boston and Washington, D.C., the West Coast between Los Angeles and San Diego, the Florida Strip between Miami and Tampa, the Sun Belt between Dallas and Houston, and the Great Lakes between Chicago and Pittsburgh.^ For instance, the U.S. Department of Transportation's study designates 17 corridors for the Improved Passenger Train (IPT) system and 18 corridors for the Tracked Levitated Vehicles (TLV) system and ranks them. For the IPT system, such corridors as New York-Washington, New York-Boston, and Los Angeles-San Diego were ranked as the first, second, and third. On the other hand, such corridors in the Great Lakes Region as Chicago-Milwaukee, Pittsburgh-Detroit, Chicago-Detroit, and ClevelandCincinnati are ranked as the fifth, sixth, tenth, and twelfth, respectively. For the TLV system, such corridors as New York-Washington, New York-Boston, New York-Buffalo, 5 The U.S. Department of Transportation, High Speed Ground Transportation Alternative Study, Washington, D.C.: U.S. DOT, January 1973. The National Governors' Association, Committee on Transportation, Commerce and Technology, Rail Passenger Project, Final Report, Washington, D.C.: NGA, October 1981. 12 and Los Angeles-San Diego were ranked as the first through the fourth. Such Midwestern corridors as Chicago- Milwaukee-Madison, Pittsburgh-Detroit-Lansing, ChicagoDetroit, Cleveland-Cincinnati are ranked as the fifth, g sixth, seventh, and thirteenth, respectively. This research undertaking, however, simply assumes that a HSIPT system were to be created in the Great Lakes Midwest Region, which is one of the higher ranking areas designated by U.S. DOT's study. The second assumption, the role of linking U.S. SMSAs and Canadian CMAs, is essentially based on the studies done by the States of Michigan and Ohio and the U.S. Department of Transportation. 7 Although these two states and the U.S. DOT have independently studied possible HSIPT system networks, it is relatively easy to find out the ideas common to each of their studies. Namely, the potential HSIPT system corridors in the Great Lakes Midwest Region will join such big SMSAs as Milwaukee, Chicago, Detroit, Cleveland, Pittsburgh, Cincinnati, Columbus, and Indianapolis along with such middle-sized SMSAs as Gary, Kalamazoo, Grand Rapids, Lansing, Flint, Toledo, Akron, 6The U.S. DOT (1973), pp. (1-8)-(1-15). 7 Michigan Department of State Highways and Trans­ portation, Michigan Railroad Plan, Annual Update, August 197 8, Lansing: Michigan DOT. State of Ohio, Dalton, Dalton, and Newport (1980). The U.S. DOT (1973). 13 Youngstown, and Dayton. In addition to these seventeen SMSAs in the United States, this research undertaking assumes that a HSIPT system in the Region should be extended to three Canadian CMAs such as Toronto, Windsor, and London where the pivotal functions of the Canadian economy exist. The third assumption, the designation of Lansing as one terminal point, is based on a similar reason described above for the second assumption. Namely, this research undertaking simply assumes that a HSIPT system goes through the Lansing metropolitan area and tries to find out the impacts of such a new system on land use activities in the area concerned. The fourth assumption, the adoption of an exclusive, grade-separated right-of-way, is based on the writer's research concerning one HSIPT system which is described precisely in Chapter II. The most extensive experimenta­ tion in the field of HSIPT systems has been done in Japan since 1964. The Japanese HSIPT system adopted the dedicated right-of-way system and has carried more than 1.5 billion passengers without a single casualty. The fifth assumption, as assumed average speed of more than 100 mph, is based on several studies which strongly recommend that a HSIPT system run more than 100 mph. The U.S. National Governors' Association's study, for instance, recommends an average speed of 14 110 mph and the British Ralways' study also recommends a high speed so as to be competitive with the automobile Q mode of transportation. The Japanese HSIPT system and the newly emerged French HSIPT system run with average speeds of 102 mph and 106 mph, respectively. The sixth assumption, passenger career only, is based on two circumstances. The first is the concern for recent declining energy resources which have had a signif­ icantly negative impact on liquid fuel oriented modes of transportation such as the automobile, bus, and airplane used in intercity passenger travel. The development of alternative transportation modes which are relatively non-dependent on petroleum is essential. The high-speed, intercity passenger train systems being operated in such countries as Japan, England, France, and Germany run with electricity as a power source. In the United States such a source of power can be generated from substantial coal reserves in this country. Nuclear resources also offer a possible means for electricity generation. The second is the rationale for a high-speed, intercity freight train system is basically weak because (except for high valued goods or perishable goods) most goods carried between g The U.S. National Governors' Association, Committee on Transportation, Commerce and Technology (1981). Klaus Becker, "British Rail's Advanced Passenger Train Enters Service," Advanced Transit News, Vol. 4, Number 3 & 4, pp. 6, 7, 15. 15 cities do not require extremely high speed. If high speed becomes necessary for freight, an air mode could be utilized, regardless of freight or passenger operation. This second reason is, however, likely to draw considerable argument and the details of that argument will be discussed in Chapter II. The seventh assumption, forthcoming potential ridership, is axiomatic and needs no further explanation. Limits of the Research Scope and Substance The magnitude of an analysis on this subject could be enormous. It has, therefore, been necessary to establish limits to the scope and substance of the study, to establish, in effect, what the study does not include. As described in the statement of objectives of the research, this undertaking is limited to finding out the impact of a HSIPT system on land use activities based on the seven assumptions mentioned above. The following three components of a complete, comprehensive research analysis are out of the scope of this research undertaking: namely, 1) potential ridership analysis, 2) cost-benefit analysis, and 3) implementation strategies. Needless to say, these three aspects are the keys to the success of a HSIPT system project, but they are substantially beyond the time capabilities and logistics available for this study. 16 Research Methodology This research undertaking utilizes four models to analyze the probable impacts of a HSIPT system if it were created in the Great Lakes Midwest Region in the United States. four models are: 1) and 2) the population These potential and population energy models to analyze general impacts of the creation of a HSIPT system in the Region; 3) the attraction-accessibility model to analyze the specific impact of a HSIPT system on land uses; and 4) the location-allocation model, the "p-Median Problem" algorithm so as to make the selection of the site for a local HSIPT system terminal more objective. The first and second models, the population potential and population energy models which were originally developed by J. Q. Stewart in the 1940's, are utilized to examine the probable impacts of a HSIPT system on a total of forty local communities, mostly SMSAs in the United States and a few CMAs in Canada, within the Region. The first model, population potential, was orig­ inated from Lagrange's concept of the gravitational potential. In 1773, Lagrange found that where the attrac­ tion of several planets at once was under consideration , a new mathematical coefficient, not used by Newton, simplified the calculations. This coefficient amounted to a measure of the gravitational influence of a planet of mass m at a distance d, and it was as simple as 17 Q possible, merely m/d. Stewart substituted the population of each city (n) for a planet of mass (m) and called it the "population potential" of the city concerned. This measure could be plotted on a map in the form of "isopotential contours" which provide a visual presentation of the intensity of human activity, or urbanization, over the map of a region or nation. This measure of population potential has been found to be correlated with demographic and socio-economic patterns of human settlement such as population density, land rents, and newspaper sales from a city to its surrounding a r e a s . ^ This concept was later expanded to the concept of the attraction-accessibility interaction models and utilized in analyzing the relation­ ship between activity locations and the travel behavior of the users of these activities. The second model, population energy, is based on Newtonian physics and is an extension of Stewart's concept of "energy of interchange" in which Stewart stressed that "demographic energy" or "interchange" between a population and a second population N 2 at distance d is times g J. Q. Stewart, "Empirical Mathematical Rules Concerning the Distribution and Equilibrium of Population," The Geographic Review, Vol. 37, 1948, p. 471. ■^Donald A. Krueckeburg and Arthur L. Silvers, Urban Planning Analysis: Methods and Models, New York: John Wiley & Sons, Inc., 1974, p. 291. J. Q. Stewart, Coasts, Waves, and Weather, Boston: Ginn and Company, 1945, pp. 153-167. 18 Many empirical studies implemented later, however, suggested that the measurement of distance separating the various areas should be raised to some power, for instance, 2 d , as in the case of the Newtonian physics. Using this "inverse square of distance" concept, it was possible to predict human interactions between pairs of cities such as the number of people traveling by bus, train, or airplane, the number of telephone calls, the volume in tons of railway express shipments, etc. 12 In the early 1970's, two groups of Japanese scholars adopted the concepts of "population potential" and "population energy" described above and examined the impact of the Tokaido Shin Kansen on the "population potential" of the selected cities along the route and the possible impacts of the planned Tohoku Shin Kansen on the "population energy" of the selected cities along the planned route. 13 The results of the two groups' studies 1:LJ. Q. Stewart (1948) , p. 473. ^2Kruekeburg and Silvers (1974). ^■^The Tokaido Shin Kansen is the first Japanese HSIPT system which was installed between Tokyo and Osaka which is approximately 350 miles southwest of Tokyo in 1964. The faster train connects these two cities in 3 hours and 10 minutes and the slower train in 4 hours and 14 minutes. The Tohoku Shin Kansen is now being constructed between Tokyo and Sapporo which is approximately 650 miles north of Tokyo. The first stage of the Tohoku Shin Kansen between Tokyo and Morioka which is about 30 0 miles north of Tokyo is expected to be completed in the early part of the year 1982. 19 strongly demonstrated the statistical validity of the above two concepts. 14 Further, their results were compared with the data released by the Japanese National Railways (JNR) and this writer's own research concerning the impact of the Japanese HSIPT system on regional development. The consequence of the comparison was very interesting; namely, the result of this writer's research and the data released from the JNR fairly strongly support the results of the researches undertaken by the two groups of Japanese scholars mentioned above. This stimulated and convinced the writer to measure the magnitude of the probable impacts of a HSIPT system on each of the forty local communities within the Region. The third model, the attraction-accessibility interaction model, is used for two objectives. First, the model is utilized to analyze the relationship between the patterns of human settlement and the locations of various land use activities in a specific local community (the Lansing metropolitan area). Secondly, the same model is utilized to examine the probable impacts of the creation of a local HSIPT system terminal (a Lansing HSIPT system terminal) on land uses in the community concerned. Specifically, the model is utilized to analyze the impact 1A Hirozo Ogawa and Etsuo Yamamura, "Kotsu To Toshi Hatten (Transportation and Urban Development),” in Yoshinosuke Yasojima (ed.), Toshi Kotsu Koza (Urban Trans­ portation Review), Vol. I, 1975, pp. 27-31. 20 probabilities flowing outward from the site designated for a local HSIPT system terminal to the rest of its local metropolitan area (the Lansing metropolitan area). The fourth model, the "p-Median" algorithm, is utilized to investigate the optimal location of the site designated for a local HSIPT system terminal. The location of the HSIPT system terminal, as a matter of fact, is a crucial element for the success of the HSIPT system. The Japanese experience clearly shows that the selection of the site for the HSIPT system terminal has to be done with extreme cauti o n . ^ For instance, those sites for a HSIPT system located away from or isolated from the existing urban structures due to political or special interests are often left without the investment dynamics commonly seen in and around the sites for HSIPT system terminals which are developed so as to synchronize with the existing urban structures. Nevertheless, in the public sector, as Rushton mentions, inter-group conflicts often develop over location decisions so that the decision finally made represents a compromise between the wishes of various Unyu Keizai Kenkyu Senta (Transportation Economy Research Center), Kansen Kosoku Kotsu Taikei no Seibi Hoshiki ni kansuru Kenkyu Chosa Hokokusho (Research Report concerning the Methods for the Possible Improvements of Trunk Express Transportation System) , Tokyo: Unyu Keizai Kenkyu Senta, 1980, p. 23. 21 groups, favoring, perhaps, one or another group in 1g proportion to the political influence each wields. To alleviate such political and pluralistic location decision problems, objectivity has to be intro­ duced in the decision process. One of the ways to realize objectivity in the decision process can be the adoption of location-allocation techniques. The primary objective of such methods is to locate a necessary public facility for the maximum effectiveness to users. Among many location- allocation techniques, the "p-Median problem" is known to be one of the most important location models. Church and ReVelle concisely summarize the concept of the "p-Median problem" as follows: One of the important measures of the effectiveness of a given locational configuration is the average distance or time that is traveled by those who utilized the facilities. The smaller this quantity, the more accessible the system is to its users. This is appealing, since the smaller the average distance of the travel, the less one is inconvenienced in getting to his closest facility. Therefore, one approach to public facility location planning could be to locate a given number of facilities such that the resulting average travel distance is minimized. . . [The authors explain the equivalence of the concepts of minimizing average travel distance and of minimizing total weighted travel distance, then continue] . . . . . Within a network context, this location problem can be defined in the following way: Minimize the total weighted travel distance associated with a network of demand nodes by locating p-facilities on the network where each demand node is served by its closest facility. This problem is called the IS Gerald Rushton, Optimal Location of Facilities, Wentworth: COMPress, Inc., 1979, p. 18. 22 'p-Median problem.1 A set of points that yield the smallest possible weighted distance is called an 'optimal' p-facility solution set/ and the points in the set that minimize the sum of the weighted distances are said to be medians of the network.17 As Rushton mentioned, location decisions in the public sector are much more difficult to optimize because of the variety of considerations often deemed to be relevant in determining a "best location." 18 The intro­ duction of objectivity as one of key elements in the location decision process could result in a somewhat more unbiased location decision which would be supportable by various relevant interest groups. Taking into account the pluralistic location decision process in the public sector described above, the selection of the site for the specific local HSIPT terminal will be approached qualitatively as well as quantitatively. By considering various social, economic, and environmental elements in a specific local area, the location decision for a HSIPT terminal could be qualita­ tively made. By adopting the location-allocation technique, the decision could be quantitatively made. 17Richard L. Church and Charles S. ReVelle, "Theoretical and Computational Links between the p-Median, Location Set-covering, and the Maximal Covering Location Problem," Geographical Analysis, Vol. VIII, Oct. 1976, p. 407. 18 Gerale Rushton, p. 17. 23 The quantitative part of the analysis will be done by adopting one of the MSU's software programs, FLOW, developed by Dr. Robert I. Wittick of Michigan State University. FLOW is a large overlay system designed to analyze and map qualitative or quantitative flow data. The "p-Median problem" algorithm is one of the twelve modules accommodated in the FLOW program and is approachable by both batch and interactive systems. 19 The final product of the attraction-accessibility model is the "isopotential contour" map based on the locations of attractions and human settlements. By producing this "isopotential" map and referring it to the existing land use activities in a specific local metro­ politan area, it is possible to avoid unnecessary conflicts between the developmental potentiality and necessary land management to preserve productive agricultural land, forest land, water resources, etc. which are irreplaceable natural resources for a living environment of essential quality. In this regard, the results of this consideration of the conservation of life-support bases would be extremely crucial for both public and private policy decision makers. For public decision makers, the result will be referred to for future action in land management, land use control, 19 Robert I. Wittick, FLOW, Version 5, Technical Report 4 (MSU Software Reference Manual) , Sept. 1980, East Lansing: MSU. 24 public investment/ etc., and for private decision makers, it will help to develop future investment strategies within the area concerned. More importantly, however, the application of this research method will be important to any of the potential sites for a HSIPT system terminal and to the surrounding areas within the region where a HSIPT system is planned or expected. This introductory chapter presented the background of the problem concerning the HSIPT system in the United States; that is, this chapter presented an evaluation of the status of transportation concepts and technologies which are needed to satisfy certain potential markets in the U.S. transportation system. This chapter further stated research objectives, research assumptions, limits of the research scope and substance, and research meth­ odologies. In the following chapter, the nature and characteristics of high-speed, intercity passenger train systems are presented and examined. In doing so, the forthcoming chapter provides an essential background for understanding the various elements to be considered in designing future HSIPT systems in the United States or anywhere else. CHAPTER II NATURE AND CHARACTERISTICS OF HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEMS In this chapter, the nature and characteristics of high-speed, intercity passenger train systems are presented and examined. In order, this chapter examines current HSIPT already in operation in Europe and Japan, current state of the affairs regarding the development of HSIPT systems in the United States, the roles of a HSIPT system on the development process (the phased development of the Shin Kansen and the Japanese development process), the role of high-speed, intercity passenger train systems on human contacts and transactions, and the positive and negative aspects inherent in the development of a HSIPT system. In so doing, this chapter provides an essential background for understanding the various elements to be considered in designing future HSIPT systems in the United States or anywhere else. State-of-the-Art of High-Speed Intercity Passenger Train Systems In September 1981, the French National Railroad (S.N.C.F.) unveiled the world's fastest train, which is capable of 236 mph. The S.N.C.F. has spent $1.6 billion 25 26 since 197 0 to develop this new train, the T G V , which stands for train "a grande vitesse" (of great speed). By the end of October, 1981, 38 TGV trains from Paris to Lyon will be in daily operation. In 1983, TGV track will be extended to Marseille, and the present 4 hours and 50 minute ride will be trimmed to 2 hours and 50 minutes. 20 The TGV's 236 mph capacity outmoded the Japanese Shin Kansen's capacity of 165 mph. However, the average speed of the TGV between Paris and Lyon was a mere 106 mph, which is slightly faster than the present Japanese Shin Kansen's average speed of 102 mph. The reason for this low average speed is that the TGV has to run the first 78 miles on the S.N.C.F.'s regular track. The remaining special track built for the TGV has continuous welded rails and concrete "sleepers" for stability. The TGV needs 2 miles to stop at 162 mph; therefore, there are no grade crossing over this exclusively dedicated right-ofway. In Great Britain, the High Speed Train (HST), currently, the world's fastest diesel train, has been in operation since 1976. There are now 160 HST services every weekday, 100 of these serving routes from London Paddington to South Wales and Bristol and 60 on the London King's Cross to Edinburgh line. 20 The average speed of the Michael Demarest, "Entrez the Flying Peacock," TIME, October 5, 1981, p. 51. 27 HST system is approximately 93 mph. This high speed on conventional rail tracks was achieved by the introduction of a powered tilting body design plus a much lighter vehicle with a low center of gravity. British Rail 21 (BR)'s ultimate goal i s , however, to replace the HST system with the APT Train) system in the near future. (Advanced Passenger The APT system, originally developed by using gas turbines as the driving force, did reach 245 km/h on August 1975; however, the gas turbines were never satisfactory and quadrupling oil prices have made them uneconomical. BR eventually converted its energy source to electricity, as did the French and Japanese high-speed rail systems. The primary reasons for this conversion from the HST to APT are included in a major study concerning the future of intercity business carried out in 1971 by BR. The study confirmed that customers— potential and actual— put journey time at the top of their priorities when choosing their mode of travel. Amenities (quietness, a good ride, air-conditioning) came second, followed by reliability. It was the firm conclusion of this study that if rolling stock was renewed on a like-for-like basis, 21 I. M. Campbell, Intercity Rail Passenger Develop­ ment in Britain, published for the Annual Conference of the United States National Governors' Association, Denver, August, 19 80. British Railways Board (Central Publicity Unit) S1048. 28 with no improvement in speed in 1970, BR would see its market share decline steadily. Conversely, a substantial improvement in journey times would bring large amounts of extra business, even though fares were pushed up in real terms to reflect the better service offered. Because BR intends to utilize existing rail tracks, the available routes for the APT service are limited to routes from London to Bristol and South Wales, along with the route from London to Edinburgh where the present HST system is in operation. The remaining routes have serious curves which prevent high-speed operation. 22 In Japan, the first Shin Kansen was built in 1964 between Tokyo and Osaka, a city approximately 4 00 miles to the southwest of Tokyo. Eight years later, in 1972, the first phase of the Sanyo Shin Kansen was built between Osaka and Okayama, a city approximately 100 miles to the southwest of Osaka. Further, in 1975, the second phase of the Sanyo Shin Kansen between Okayama and Fukuoka (Hakata is the name of station in this 1 million population city} was completed. constructed. 22 Two more Shin Kansens are now being The first phase of the Tohoku Shin Kansen Klaus Becker (no date), pp. 6, 7, 15. As noted, the French system runs with an average speed of 106 mph and the Japanese system with 102 mph. To achieve 102 mph, the minimum radius of curves must be designed to be 4,000 meters. Many of the curves on the BR's existing tracks are less than 2,000 meters radius because the cost of curve realignment is prohibitive. 29 between Tokyo and Morioka, a city approximately 300 miles to the north of Tokyo, will start service sometime early in 1982, and its extension to Sapporo to be finished by the end of 198 4. (Phase 2) is expected The other line, the Joetsu Shin Kansen between Tokyo and Niigata, a city approximately 2 00 miles to the northwest of Tokyo, is also expected in 1982 (Figure 3). National Railways' MLV Further, the Japanese (Magnetic Levitation Vehicle) has repeatedly attained speeds in the range of 500 to 5 40 km/h (312 to 337 mph) over a 7 km (4.4 miles) test track. Making this MLV technology a base, the JNR and the Japanese government have been studying the possibility of a 2nd Tokaido Shin Kansen between Tokyo and Osaka. If this second Tokaido Shin Kansen were completed, those two cities could be reached within one hour and a half, or less. The field survey for this project started in the late 1970's. The date of the completion is unknown, but presumably it will be finished by the end of the 1990's. Although it is undeniable that Europe and Japan are clearly ahead in developing improved rail passenger transportation, several U.S. states have already taken some actions to realize a new, high-speed, intercity passenger train system. As early as in 1975, Ohio estab­ lished the Ohio Rail Transportation Authority (ORTA) and has already spent more than $3 million to study a HSIPT system, depending mainly on the Japanese experience for 30 Sapporo The 5hln kansen in operation The Shin kansana under construction kodate chinoe Sanyo Shin Kansen Phase II .fhase I March, 1975 March, 1972 hima iyama noniya kasak Yokohama ^tagoya SQB.Z mamatstu Kiftakyua o Tokaido Shin October, 1964 Figure 3.— Configuration Map of the Japanese HSIPT System (The Shin Kansen System). 31 guidance. In 1979, Michigan's Senate and House approved a bill to study a high-speed, interstate train system, and a ridership analysis for an intra-state, high-speed rail passenger system is now being undertaken by the Michigan Department of Transportation, utilizing the expertise of the British consulting firm, TRANSMARK. As mentioned before, in 1979 and 1980 legislation was passed in Ohio, Michigan, Pennsylvania, and Illinois to establish the Interstate High Speed Intercity Rail Passenger Network Compact to provide an organizational form for cooperation in the development of the Midwest Corridor Improvement Project. Not only such legislative actions but also actual actions to realize a high-speed, intercity passenger train system have been taken in several states and by AMTRAK. These actions are basically classified into two different approaches. The first approach could be called the British approach, which aims at the service improvement of existing systems. Existing tracks and signals are the objects of the improvement effort, and a joint freight-passenger operation is the characteristic method of this approach. Michigan, for instance, is following this approach. tentative goal aimed at by Michigan is to provide a The 32 maximum 79 mph service. 23 California and Illinois are examining the possibility of providing more frequent service necessary for true corridor operation through the 4 03(b) program which authorizes AMTRAK to operate selected services at the request of a state or local agency, with the state providing 50% of the operating expenses. 24 The second approach could be called the Japanese or French approach. This approach provides an exclusive right-of-way to a high-speed, intercity passenger train system. This exclusive right-of-way is secured by a protective fence, an elevated rail line, or an open ditch system; consequently, no grade crossings can be provided. California and Florida are now investigating the possibility of an exclusive right-of-way for high-speed operations, 25 and Ohio has already designed detailed plans for such a system. 26 AMTRAK, with the assistance of the JNR, is now undertaking design and engineering studies for a possible HSIPT system on four selected corridors. This study evaluates routes 23 Michigan Department of State Highway and Trans­ portation, Michigan Railroad Plan Annual Update August 1978, Lansing: Michigan DOT. 24 NGA Committee on Transportation, Commerce, and Technology, p. 3. 25Ibid., p. 3. 26 The State of Ohio and Dalton, Dalton, and Newport (1980). 33 from Los Angeles to San Diego, Dallas-Fort Worth to Houston, Miami through Orlando to Tampa, and one route 27 from Chicago. The U.S. Department of Transportation, on the other hand, implemented a study concerning high-speed ground transportation and released a report entitled, High Speed Ground Transportation Alternative Study, in January, 1973. This HSGT study concludes that two rail passenger systems could be implemented in the United States. One is the "Improved Passenger Train (IPT)" system and the other is the "Tracked Levitated Vehicle (TLV)" system. The IPT system concept is aimed at revitalization of past investments in conventional rdil routes by the introduction of 1) attractive, comfortable and reliable equipment, 2) reliable schedules to give convenient, frequent service, 3) speeds competitive with air modes in the 50 to 200 mile trip range, and 4) minimal adverse environmental impact. This IPT aims to provide greater comfort and convenience than conventional service at speeds 30 to 5 0% higher on curves and up to 150 mph on the straightaway. The TLV, on the other hand, aims at a speed competitive with air up to 4 00 miles. The intercity TLV system concept features speeds up to 300 mph. 27 The IPT system is similar to the The Lansing State Journal, 10 August 1981 and the NGA Committee on Transportation, Commerce and Technology (1981), p. 3. 34 HSIPT systems which have been implemented in Europe and Japan, and the TLV system is equivalent to the MLV system which is being developed in Japan and Germany. As mentioned earlier, the U.S. DOT'S study ranked seventeen corridors for the IPT system and eighteen corridors for the TLV system based on its market potential analyses (Figures 4 and 5), but concluded that system viability and benefits thoroughly depend on future petroleum fuel developments. 28 As can be seen, the time and place of eventual implementation for a HSIPT in the United States are uncertain. However, it is important to note that an appropriate system in one country may not be appropriate in others. In fact, each country's system needs to be dictated by its own geographic, demographic, socio-economic, political and even cultural structures. In fact, the introduction of a HSIPT system may lead to a drastic structural change of the U.S. economy. Future petroleum fuel shortages, on the other hand, if they occur, may jolt the U.S. societal system which has been dependent on the mobility offered by the automobile mode of transportation. Needless to say, the circumstances in the United States require more careful analysis than that by other nations where existing systems are better suited to such a pp. 28 The U.S. Department of Transportation (I— 1)-(1-5). (1973), 35 Corridors 1. 2. 3. 4. 5. 6. 7. 8. 9. New York-Washingcon New York-Boston Los Angeles-San Diego New York-Bu£falo Chicago-Mllwaukee Pittsburgh-Detrolt Washington-Norfolk/Nevport News Springfield/Hartford-New York San Franclsco-Sacraisento 10. 11. 12. 13. 14. 15. 16. 17. Chicago-Detroic Los Angeles-Lss Vegas Claveland-Cincinna ci Los Angela-San Francisco Piccsburgh-Philadelphia Chicago-St. Louis Tampa-Orlando Seattle-Portland Figure 4.— Ranked Potential IPT Corridors Market Potential Analysis). (From SOURCE: The U.S. DOT, High Speed Ground Transporta­ tion Alternative Study, January 1973, pp. (1-9). The map shown above is compiled by Shun'ichi Hagiwara. 36 Corridors 1. 2. 3. 4. 5. 6. 7. 8. 9. New York-Washlngtou 10. New York-Boaton New York-Buffalo 11. Loa Angeles-San Diego 12. Chicago-Milwaukee-Hadiaon 13. 14. Plttsburgh-Decrolt-Lanalng Chlcago-Datole 15. tfashington-Norfolk/Newport News 16. 17. Loa Angeles-San Francisco 18. Springfield/Hartford-New York -New York Los Angeles-Lao Vegas Chicago-SC. Louis Cleveland-Clnclunatl San Franclsco-SacrsaenCo Durham-Atlanta Jacksonville-Miami Fhlladelphla-Plccsburgh Seactle-Portland Figure 5.— Ranked Potential TLV Corridors Market Potential Analysis). (From SOURCE: The U.S. DOT, High Speed Ground Transporta­ tion Alternative Study, January 1973, pp. (1-14). The map shown above is compiled by Shun'ichi Hagiwara. 37 transportation system as a HSIPT system. Nevertheless, many valuable lessons can be learned from other countries which have already encountered the various problems inherent in the creation of a HSIPT system. Especially, the long and successful operation of the HSIPT system in Japan can provide reliable and substantial data to the United States. Therefore, a description and analysis of the Japanese Shin Kansen are provided as one working prototype which could be applicable if such a system were to be created in the United States. The Roles of a HSIPT System on the Development Process (Case Study: The Shin Kansen and the Japanese Development Process) It is reasonable to conceive that the creation of a HSIPT system in any region or in any country not only reduces the time-distance between the communities joined by the system, but it also stimulates new development in each of those regions or areas served by it. For instance, the aforementioned Ohio Rail Transportation Authority (ORTA) stresses the benefits of a HSIPT system as follows: namely, a HSIPT system would: 1. 29 create engineering and construction jobs during the design and building phases; 29The ORTA (1980), pp. 49-51. 38 2. create jobs in the operation, maintenance, and control of the rail network once it was operational; 3. utilize the Region's vast reserves of coal to provide electricity for the HSIPT system; 4. stimulate the coal industry; 5. stimulate investments in new enterprises around the terminals; 6. help attract and retain businesses seeking a location for expansion; 7. utilize high technologies and skills developed and used in the automobile and auto-parts industries in the Region for necessary materials, equipment, and machinery; 8. facilitate efficient and economical movement of the population, and; 9. stimulate and strengthen economic growth of the local area of any given terminal, as well as for the region where the system is planned. The U.S. Governors' Association's study also mentions the possible benefits of the creation of a HSIPT system in the United States as follows: 30 The Europeans and Japanese have built an entire industry based on providing rail passenger service and the equipment and technology necessary to operate it. This industry provides thousands of highly "^The NGA Committee on Transportation, Commerce and Technology (1981), p. 2. 39 productive jobs in the service, technological and industrial sectors of their economies. . . . Even if we were to decide tomorrow to launch a massive high-speed rail passenger improvement program, we would be forced to import foreign technology and equipment at least for the short term. Instead, we should be developing a domestic industry providing badly needed jobs, especially decreased demand for steel and autos. Such innovative industry will continue to grow and provide jobs. These extremely positive expectations for the role of transportation modes such as a HSIPT system in the economic development process, however, have been the subject of strong criticism. According to such criticism, development is not the single determining process, and the singling out of a single component such as investment in the highway program or rail improvement program as a decisive element is nothing but an oversimplification of a very complex development process. 31 Nevertheless, the positive view concerning the role of transportation in the development process is still remarkably resilient. In Japan, for instance, a number of studies have stressed a significant role of the Shin Kansen in the development process xn Japan. 31 32 Howard Gauthier, "Geography, Transportation, and Regional Development," Economic Geography, Vol. 46, 197 0, pp. 612-619. 32 Concerning the studies related to the role of the Shin Kansen, see Shun'ichi Hagiwara, Possible SocioEconomic Effects of the Development of the High-Speed Rail Transit Service in Underdeveloped Areas in Japan, Unpublished Master's Thesis, Michigan State University, East Lansing, Michigan, 1977. 40 In the United States, Goldberg cited Paul Wendt's study concerning the San Francisco Bay Area and Vancouver, British Columbia, Canada, and stressed that the areas which grew most rapidly in terms of population and value of land improvements were those areas which were opened up as a result of transportation improvements. According to him, the San Francisco Bay Area has experienced dramatic improvements in transportation and internal accessibility first by the automobile, then by the San Francisco-Oakland Bay Bridge and the Golden Gate Bridge, and more recently by the freeway system. 33 Recently, however, a pessimistic view concerning the role of transportation has emerged. This view holds that the creation of transportation may absorb some portion of scarce resources that should be employed elsewhere. The highway extension program has been halted in many states and cities in the United States. The plan to create the total of 7,200 km (4,500 miles) Shin Kansen network all over Japan is now regarded as a waste of scarce resources and funds. This pessimistic view will emerge more and more strongly in the decision process for the allocation of resources to transportation systems such as the HSIPT system. 33 In fact, errors in the allocation of Michael A. Goldberg, "Transportation, Urban Land Values, and Rents: A Synthesis," Land Economics, 46, 1970, pp. 153-162. 41 resources often happens in the sector of transportation. Gauthier summarizes the reasons for such a misallocation of resources to the transportation sector as follows:34 1) the lumpiness, longevity, and externalities associated with transportation capital create greater hazards in calculating and specifying future benefits and costs; and 2) there is a belief that transport is a safe investment politically. In fact, inappropriately located airports, highway interchanges, and rail terminals are commonly seen every­ where. Improper and unwise management of scarce resources can be avoidable only by proper planning and careful cost and benefit analysis. Proper decision making is often only obtained from valuable empirical lessons. In the following text, the role of the Shin Kansen in the Japanese development process will be examined in three different aspects. First is the impact of the system in the regional development process. As mentioned before, it took about ten years to complete the 1,070 km (670 miles) Shin Kansen between Tokyo and Fukuoka, and it is taking about ten years to finish up another 1,040 km (650 miles) between Tokyo and Sapporo. This part of the research, accordingly, tries to examine whether a strong relationship exists between the phased development of the Shin Kansen and regional development. Second is the role of the system in the enhancement of human contacts and 34Gauthier (1970), p. 614. 42 transactions. Traditionally, much attention has been given to the logistics of raw materials and finished products. Recently, however, the significance of the exchange of messages through the transport of people has been recognized as a key element of regional development. Thorngren, for instance, says that: 35 Technology, market conditions, and social values are changing at a more and more rapid pace. When changes are considered, contacts between various parties are often necessary. The actors are often spread over space. The exchange of information can take the form of face to face contacts, or can use technical devices. William Alonso also supports the significance of human 36 contacts as follows: Industries may now be attracted to areas of good weather, either because it is important to their locations (as in the case of the aircraft industry) or because it will be attractive to their workers (as in the case of some research industries). Or they may be attracted to special site advantages, or to cheap labor, or perhaps most important, to contacts. These contacts are infinitely varied in their forms. They may be managerial exchanges, where vital infor­ mation is exchanged casually over lunch, or close supplier-customer coordination, or the chance remark that discloses an unsuspected opportunity, or the shoptalk of technical people that stimulates new ideas. The importance of contacts will probably increase the attraction of large urban centers for many industries, and lead to further concentration. 35 B. Thorngren, "How do Contact Systems Affect Regional Development?" Environment and Planning, Vol. 12, 1970, p. 409. 36 William Alonso, "Location Theory," in John Friedmann and William Alonso, eds. , Regional Policy: Readings in Theory and Application, Cambridge: The MIT Press, 1975, pp. 35-63. 43 Thorngren, also, summarizes the propositions based on the assumptions concerning the necessity of the face-to-face contacts in the economic development process in the postindustrial society as follows: 37 1. the volume of contacts between different firms, research bodies, organizations and authorities is great. It is expected to increase considerably; 2. the contact work is mainly performed by people in higher positions. It is expected to involve an increasing proportion of employees, in the lower echelons also; 3. the means of communication now available do not permit a separation of contact-dependent functions and others within organizations. Even new devices, such as TV-phones or data terminals, cannot be expected to change this within the next few decades; 4. instead, new techniques for telecommunication may - by permitting a spatial division of the firm's administrative and production units - increase the tendencies towards growth within the bigger urban regions. To make people achieve face-to-face contacts, a network system which is faster, cheaper, more accessible, or more efficient than others is necessary. Gunner Toernqvist stresses the necessity of such a network as follows: 3 8 If people have to meet other people long distance away, then they have to use express trains or air services. The resulting contact system can be linked to a strongly focused network, consisting of a set of nodes linked by fixed transport routes, which people must use for getting from one place to another. ■^B. Thorngren (1970) , p. 410. 38 Gunner Toernqvist, "The Geography of Economic Activities: Some Critical Viewpoints on Theory and Application," Economic Geography, Vol. 53, No. 2, April 1977, p. 158. 44 This part of the research, accordingly, examines whether the Shin Kansen has been, and such a HSIPT system as the Shin Kansen, will be the key channel for human contacts and transactions in any region or in any country. Finally, various problems inherent in the creation of a HSIPT system will be investigated. others are positive. Some of those are negative and Some of these might have been predicted or foreseen, but others may have to be learned only from experience. In this regard, the various problems dealt with in creation of the Shin Kansen could be valuable for HSIPT system planners in any region or any country. Accordingly, the following thirty pages of this text are devoted to analyzing the Shin Kansen and to comparing similarities and potentials for the United States. The Phased Development of the Shin Kansen and the Japanese Development Process In this analysis, forty-six Japanese prefectures are divided into four groups (Figure 6). Group A is composed of nine prefectures located in the northern part of Japan where the service of the Tohoku and Joetsu Shin Kansens are expected between 1982 and 1984. Group B consists of the fourteen prefectures located along the Tokaido Shin Kansen route which have had the service of the Shin Kansen since 1964. Group C is composed of four prefectures along the Sanyo Shin Kansen; the service of 45 46 Prefectures excluding Okinawa 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 16. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. Hokkaido Aomori Ivate Miyagi Akita Yamagata Fukushima Ibaragl Tochigi Gumma Saltama Chiba Tokyo Kanagava Niigata Toyama lahikawa Fukui Yamanashi Nagano Gifu Shi 2uoka Aichi Mie Shiga Kyoto Oeaka Hyogo Nara Wakayama Tottori Shlmane Okayama Hiroshima Yamaguchi Hokkaido 36. 37. 38. 39. 40. 42. 43. 44. 45. 46. Tokushima Kagawa Ehime Kochi Fukuoka Saga Nagasaki Kumamoto Oita Miyazaki Kagoshima Honshu Shikoku Group A (9 Prefa.) * | Group B(14 Prefa.) Kyuahu Group C(4 Prefa.) J Group D(19 Prefs.) Figure 6.— Grouping of 46 Prefectures of Japan based on the Phased Development of Shin Kansen. 46 the Shin Kansen was given to these prefectures partly in 1972 and completely in 1975. The rest of the prefectures (nineteen prefectures) comprise Group D. No service of the Shin Kansen has been given to this group, and there will be no service in the near future. Five socio-economic variables were selected in order to analyze the effects of the Shin Kansen on regional development. 2) Those were: 1) prefectural population, urban population (in other words, DID population, densely inhabited district population), 3) the number of manufacturing establishments, 4) the number of serviceoriented establishments, and 5) the value of shipments. The data for these five variables were looked at for the years of 1960 , 1965 , 1970, and 1975 , respectively (Table 1). For the year of 198 0, only the prefectural population was available. The data shown in Table 1 can be interpreted as follows: 1. During the first five years of the 1960's (1960-65), Group B, which is composed of 14 prefectures along the Tokaido Shin Kansen route, expanded its dominant status in every category. The share of the prefectural population increased from 44.9 to 48.6 percent, while the population in densely inhabited districts increased from 60.9 to 65.3 percent. The shares in both man­ ufacturing and service-related establishments also TABLE 1.— Transition of Socio-economic Characteristics in Japan (1960-1980). 1960 1965/1970 1960/1965 Growth Share Rate Area Growth Share Rate National Group A Group B Group C Group D 1.000 1.000 1.000 1.000 1.000 100.0 20.6 44.9 10.1 24.3 1.052 1.001 1.137 0.997 .961 100.0 19.7 48.6 9.6 22.2 1.055 1.009 1.117 1.026 .975 National Group A Group B Group C Group D 1.000 1.000 1.000 1.000 1.000 100.0 12.7 60.9 8.7 17.8 1.158 1.229 1.243 1.183 0.802 100.0 13.5 65.3 8.8 12.3 National Manufacturing Group A Establishments Group B Group C Group D 1.000 1.000 1.000 1.000 1.000 100.0 14.0 58.0 8.7 19.4 1.209 1.221 1.281 1.0B5 1.039 National Services Group A -related Group B Establishments Group C Group D 1.000 1.000 1.000 1.000 1.000 100.0 18.8 46.2 10.2 24.8 National Group A Croup B Group C Froup D 1.000 1.000 1.000 1.000 1.000 100.0 9.5 70.0 10.4 10.1 Prefectural Population Population in Densely Inhabited District (DID) Value of Shipments Note Z 1970/1975 Growth Share Rate Growth Share Rate Z 100.0 18.8 51.4 9.3 20.5 1.069 1.042 1.100 1.065 1.020 100.0 18.3 52.8 9.3 19.6 1.046 1.048 1.050 1.043 1.032 1.165 1.151 1.203 1.112 1.001 100.0 13.3 67.5 8.4 10.8 1.149 1.124 1.131 1.121 1.181 100.0 13.1 67.7 8.2 11.0 N.A. 100.0 14.1 61.5 7.8 16.6 1.104 1.074 1.095 1.011 1.204 100.0 13.7 61.0 7.1 18.1 1.103 1.106 1.124 1.023 1.058 100.0 13.8 62.2 6.6 17.4 N.A. 1.157 1.157 1.205 1.120 1.103 100.0. 18.7 47.9 9.9 23.6 1.095 1.075 1.115 1.087 1.057 100.0 18.4 48.9 9.8 22.8 1.167 1.136 1.205 1.133 1.126 100.0 17.9 50.5 9.5 22.0 N.A. 1.893 2.020 1.889 1.809 1.889 100.0 10.2 69.8 9.9 10.1 2.340 2.353 2.313 2.262 2.395 100.0 11.1 69.0 9.6 10.4 1.847 2.157 1.725 2.035 2.156 100.0 12.9 64.4 10.6 12.1 N.A. X Growth Share Rate 1975/1980 X X 100.0 18.4 53.1 9.3 19.3 For Manufacturing and Service-related Establishments, the data are only available for the years of 1966 and 1969 Instead of 1965 and 1970. Servlces-related establishments Include wholesale and retail trade, finance and Insurance, real estate, transport and communication, electricity,.gas.and water, and services including medical and other heakth services and educational services. Sources: Japan Statistical Yearbook, 1963, 1967, 1972, and 1978/Minryoku, 19D1. 48 increased from 58.0 to 61.5 percent and 46.2 to 47.9 percent, respectively. The value of shipments category went down slightly from 70.0 to 69.8 percent, but still absolutely dominated others. The most noteworthy phenomenon in this term was a sharp drop of the DID population in Group D, from 24.3 to 22.2 percent. During this term, in 1964, the Tokaido Shin Kansen was built between Tokyo and Osaka. 2. During the second five years (1965-70), the dominance of Group B had not changed, but the growth of its share slowed down. The share of the DID population, in particular, slowed down from 4.4 percent growth during the previous term to 2.2 percent during this term. and Group B's shares in manufacturing establishments the value of shipments also dropped, but only slightly. Group D ’s shares in prefectural population and DID population had fallen again, fairly sharply. During this term, the construction of the Sanyo Shin Kansen was underway. 3. During the first five years of the 1970's (1970-75), Group B still dominated the others, but the growth of its share considerably slowed down. its share in the DID population category was only 0.2 percent. The increase of Even in the prefectural population category, the growth of Group B's share dropped from 2.8 percent during the previous term to 1.4 percent 49 in this term. The most significant change occurred in the category of the value of shipments of Group B which dropped from 69.0 percent share during the previous term to 64.4 percent in this term. During this term, the Sanyo Shin Kansen was completed between Osaka and Fukuoka, and the construction of the Tohoku and Joetsu Shin Kansens started. 4. For the second half of the 1970's (1975-80), only the data for prefectural population are available, and for the first time, Group A increased its share. Group B's share, on the other hand, increased very slightly, only 0.3 percent. Group C maintained its share of 9.3 percent and Group D's share continued to drop, but its rate of decline slowed down considerably. From the above observations, however, it is hard to specify a strong relationship between the phased development of the Shin Kansens and regional development, except for the following two phenomena which might be considered to be the results of the creation of the Shin Kansens in Japan. 1. Group B These are: (the prefectures along the Tokaido Shin Kansen) has continuously grown during the past two decades; 2. Group D (the nineteen predectures which have had nothing to do with the Shin Kansen) has continuously declined in terms of the size of its population. 50 Along with the above analysis, the movement of the center of gravity of population in Japan between 1960 and 1980 was investigated (Figure 7). As shown in the enlarged portion of Figure 7, the center of gravity made the largest move toward the east between 1965 and 1970, then changed direction slightly to the southeast, and during the last five years (between 1975 and 198 0), it moved upward to the northeast again. These moves clearly indicate the rapid increase of population in the Tokyo area (3.15 million) in the early 1960's and the continuous increase in the Tokaido area Sanyo area (0.8 9 million) and the sharp increase in the (0.25 million compared with 0.3 million decline in the previous term) in the late 1960's, and then, the sharp increase in the Sanyo area Tohoku area (0.68 million) and in the (0.88 million) in the early 1970's, and the continuous, and only absolute, increase in the Tohoku area (0.98 million) in the late 1970's (Table 2). The trends of population movement shown in Figure 7 and Table 2 are suggestive that there could be fairly strong relationship between the development of the Shin Kansens and the Japanese development process, but are not perfectly conclusive. The above analyses, based on data at the prefectural level, may seem rather too broad for examining the impacts of the Shin Kansens in the development process. So, the next study narrows down the scope of the research to a ** 1 3 J. 18 17 16 Sappc ro 15 14 1 9 8 0 (6 .8 7 ,7 ]5 4 K A one 12 ■Moficka 1960 Sencai 10 9 Tokj 8 ------ > u r--- waflgyi 7 ityoti o p -- f— iJhjytt oka Kobe f ^ l a a k i . ^ ^ manatsu 6 /f Tkij Hire *fmn% 5 Fukue 3 0 1 2 3 4 5 6 7 8 9 10 11 Figure 7.— Center of Gravity of Population in Japan (196 0-1980). TABLE 2.— Population Changes in Five Regions (1960-1980). Unit: 1,000s I960 Actual 1965 Actual Change 1970 Actual Change 1975 Actual Change Tohoku Region 19,289 19,320 31 19,432 112 20,307 875 21,289 982 Tokyo Metro, Reg. 17,864 21,017 3,153 24,113 3,096 27,067 2,954 28,694 1,627 Tokal Region 10,928 11,779 851 12,668 889 13,712 1,044 14,396 694 Osaka Metro. Reg. 13,189 14,923 1,734 16,510 1,587 17,845 1,335 18,442 597 9,462 9,435 -27 9,681 246 10,298 617 10,751 453 Sanyo Region 1980 Actual Change Note: Concerning Che configuration of the above region, see Figure 5. Tohoku Region: 9 prefectures (Group A) Tokyo Heto. Reg. (Tokyo Metropolitan Region): Tokyo, Saltama, Chiba, and Kanagawa prefectures. Tokai Region: Shizuoka, Alchl, Clfu, and Hie prefectures Osaka Metro. Reg, (Osaka Metropolitan Region): Osaka, Kyoto, and Hyogo prefectures, Sanyo Region: Okayama, Hiroshima, Yamaguchl, and Fukuoka prefectures. Source: Aaahl Shlmbun Sha (The Asahl Newspaper Publisher), Mlnryoku 76 and 81 (Prefectural Powers and Resources. Tokyo: The Asahl Newspaper Publisher. (In Japanese) 53 smaller scale (the city level). A total of sixty cities were selected and divided into six groups. Group A consists of four cities on the Tokaido Shin Kansen route where HIKARI (the fast train) stops. The second group, B, consists of nine cities on the Tokaido Shin Kansen route where KODAMA (the slower train) stops. Group C is composed of four cities on the Sanyo Shin Kansen where HIKARI stops. Group D is composed of ten cities on the Sanyo Shin Kansen route where KODAMA stops. Group E consists of fourteen cities along the forthcoming Tohoku and Joetsu Shin Kansen routes, and the final group, P, is made up of nineteen prefectural capitals where the service of the Shin Kansen system will not be expected in the near future. The population data for these sixty cities during the term between 1960 and 198 0 are listed in Table 3. Between 1960 and 1965, the largest growth rate was recorded by Group A's DIDs (1.375) and the smallest increase also recorded by Group A's cities. This clearly indicates that a rapid suburbanization occurred during this term, and this trend has continued until today. The second largest increase was recorded by Group E (1.328), but this sharp increase was due to an extraor­ dinary increase achieved by two cities, Koriyama and Oyama (2.591). (2.175) These two cities are located in the area just north of the Tokyo metropolitan area, and a 54 TABLE 3.— Population Changes in Sixty Cities (1960-1980). Growth Rate 1960/65 Growth Rate 1965/70 Growth Rate 1970/75 Growth Rate 1975/80 Tokyo 1^ 8,310,027 Nagoya 1,591,935 Kyoto 1 1,284,818 Osaka 1 3,011,563 Average Growth Rate 1.070 1.216 1.062 1.048 1.099 0.994 1.052 1.040 0.944 1.008 0.978 1.021 1.030 0.932 0.990 0.946 1.002 0.993 0.928 0.967 o 8,688,599 M Tokyo-DID U 2,154,613 Aichi-DID 1,298,965 Kyoto-DID 4,387,952 Osaka-DID Average Growth Rate 1.252 1.427 1.258 1.564 1.375 1.098 1.166 1.129 1.230 1.156 1.037 1.183 1.119 1.119 1.115 N.A. Yokohama 1,375,710 Atami 52,163 Odawara 124,813 Shizuoka 328,819 Hamamatsu 333,009 Mlahlma 62,966 215,515 Toyohashi Gifu 304,492 Otsu 113,547 Average Growth Rate 1.300 1.046 1.149 1.118 1.179 1.131 1.107 1.176 1.066 1.141 1.251 0,940 1.093 1.132 1.101 1.097 1.083 1.077 1.419 1.133 1.171 1.003 1.108 1.073 1.085 1.142 1.101 1.060 1.115 1.095 1.051 1.005 1.012 1.023 1.042 1.053 1.057 0.995 1.090 1.036 Okayama 260,773 Hiroshima 431,336 Kitakyushu 986,401 Fukuoka 1,047,122 Average Growth Rate 1.119 1.169 1.057 1.159 1.126 1.285 1.075 1.000 1.138 1.125 1.369 1.573 1.015 1.175 1.783 1.055 1.019 0.999 0.976 1.012 Kobe 1,113,977 Akashi 129,780 Himeji 328,689 36,521 Aioi Kurashiki 125,097 3 a Fukuyama 140,603 U Hihara 80,395 Iwakuni 100.346 77,246 Tokuyama Shinonoeeki 246,941 Average Growth Rate 1.092 1.227 1.119 1.066 1.155 1.210 1.022 1.056 1.096 1.030 1.107 1.059 1.296 1.110 1.113 2.352 1.499 1.005 1.002 1.163 1.016 1.262 1.056 1.137 1.068 1.150 1.156 1.293 1.013 1.047 1.086 1.032 1.104 0.989 1.070 1.015 0.986 1.028 1.047 1.024 :..014 1.033 0.985 1.019 Population 1960 < a a M a 3 O ha O U o 3 O h* 5J a a Mote: 1 Ku pare - Ku is similar jurisdiction to Ward. Ku pare may be understood as a city part compared with DU) part which may be regarded as a metropolitan part. - over - 55 Table 3.— Continued. Growth Rate 1960/65 Growth Rate 1965/70 Growth Rate 1970/75 Growth Rate 1975/80 Sapporo 523,839 Hakodate 243,012 Aomori 202,211 Hachinohe 174,348 Morioka 157,441 Sendai 425,272 Fukushima 138,961 102,636 Koriyama Utsunonlya 239,007 Oyama 34,973 Haebashi 181,937 Takasaki 142,152 Niigata 314,523 Nagaoka 148,254 Average G owth Rate 1.517 1.002 1.110 1.086 1.124 1.131 1.250 2.175 1.117 2.591 1.092 1.223 1.133 1.044 1.328 1.271 0.993 1.070 1.103 1.108 1.133 1.310 1.033 1.134 1.162 1.176 1.110 1.078 1.049 1.127 1.228 1.272 1.101 1.075 1.103 1.129 1.084 1.095 1.143 1.142 1.071 1.095 1.102 1.058 1.121 1.092 1.031 1.078 1.056 1.047 1.034 1.052 1.060 1.082 1.054 1.054 1.047 1.050 1.029 1.055 Akita 203,661 Yamagata 188,597 Nagano 160,522 Kofu 160,963 Toyama 207,266 Kanazawa 298,972 Fukui 149,823 Tottori 104,833 Matsue 106,476 Tokushima 182,7B2 228,172 Takamatsu 238,604 Matsuyama 196,288 Kochi Saga 129,888 Nagasaki 344,153 373,922 Kumamoto Oita 124,807 158,328 Hlyazaki 296,003 Kagoshima Average Growth Rate 1.064 1.027 1.077 1.071 1.157 1.123 1.132 1.038 1.038 1.057 1.067 1.185 1.110 1.036 1.178 1.089 1.814 1.155 1.110 1.133 1.089 1.054 1.651 1.059 1.123 1.076 1.182 1.039 1.068 1.156 1.127 1.142 1.104 1.066 1.039 1.081 1.151 1.109 1.228 1.134 1.108 1.077 1.075 1.061 1.077 1.094 1.154 1.081 1.080 1.071 1.090 1.138 1.168 1.061 1.069 1.109 1.229 1.155 1.133 1.107 1.077 1.052 1.044 1.025 1.040 1.021 1.0251.046 1.034 1.030 1.043 1.079 1.056 1.076 0.983 1.030 1.090 1.090 1.0B7 1.049 Group F Group E Population 1960 Source: The Japan Statistical Yearbooks. 1963. 1967. 1972. 1978. Asahi Shimbun, Mlnrvoku 81. 56 number of industrial plants which were forced to move out of the Tokyo area moved into these two cities. Without these two cities, Group E ’s growth rate drops to 1.152. During the second tern, between 1965 and 1970, Group D experienced the highest growth (1.262). Kurashiki City greatly contributed to this growth with a growth rate of 2.352. Fukuyama City also contributed greatly (1.499). The reason for the rapid expansion of Kurashiki may be explained partly by the creation of the Sanyo Shin Kansen and partly by the development of a huge steel plant in Fukuyama City along with petro-chemical plants around the area. Kurashiki is a beautiful, historic town, and it obviously attracts newcomers for the recently developed plants described above. Okayama City in Group C also experienced very high growth (1.285), presumably in anticipation of the creation of the Sanyo Shin Kansen within a few years. During the third period, 197 0 and 1975, the highest growth was experienced by Group C, especially the largest city in the group, Hiroshima (1.573). Okayama, Fukuyama, Kurashiki, and Fukuoka, all in the groups C and D, experienced very high growth. During this term, the first phase of the Sanyo Shin Kansen between Osaka and Okayama was completed in 197 2, and its extension to Fukuoka was completed in 1975. During the same term (1970-75) , the city part of Group A experienced a decline. The second highest growth in this term was 57 experienced by Group E which expects the creation of the Tohoku and Joetsu Shin Kansens within a few years. This trend became much clearer during the fourth term, between 1975 and 19 80. For the first time, Group E's growth dominated the others. Group A experienced more drastic decline during this term. The population growth in Groups B, C, and D stabilized. Notably, Group F climbed up to second for the first time. Several studies reveal the impacts of the Shin Kansen on regional development very clearly. For instance, according to the research done by the Japanese Development Bank, during the six years between 1964, when the Tokaido Shin Kansen was built, and 1972, when the Sanyo Shin Kansen was extended to Okayama, the number of branch offices or liason offices established by large enterprises increased to 378. Up until 1964, the total number of such branch and liason offices in Okayama was 202. 39 Also, during the two years of 1975 and 1976, according to the research done by Unyu Chosa Kyoku (the Transportation Research Bureau), the number of hotels in Fukuoka increased 100 percent, from 20 to 40, and in Hiroshima, 300 percent, from 4 39 The Japanese Development Bank, The Impacts of the Sanyo Shin Kansen on Regional Society, May 1975 cited by Zai Matsumura of the JNR's Hiroshima Branch, We Are Now Approaching the Completion of the Sanyo Shin Kansen (Address before the members of the Hiroshima Chamber of Commerce), February 24, 1975. (mimeo in Japanese). 58 to 13. Rental office buildings were also built in and around the Shin Kansen terminal in the above cities.40 As a matter of fact, the so-called redevelopment project in and around the Shin Kansen terminal site was commonly seen in most of the cities along the Tokaido and Sanyo Shin Kansens. Even in such cities as Sapporo, Sendai, Niigata, and Morioka, where the service of the Shin Kansen is expected within a few years, similar trends (redevelopment projects in and around the site for the prospective Shin Kansen terminal) are commonly seen. From these two analyses (prefectural level analysis and city level analysis), what kind of conclusion should be drawn? Are there really strong relationships between the phased development of the Shin Kansen and regional development in Japan? Some authorities stress that the industrial redistribution policies represented by the "New Industrial City" and the "Pacific Coast Belt Industrial Zone," both implemented in 1963, have been gradually showing their effects. assertion. However, no data support this Only 1 out of 15 designated new industrial cities, for instance, has grown more than the national 40Unyu Chosa Kyoku, The Extension of the Sanyo Shin Kansen and Its Effects on Regional Society, March 1976 cited by Unyu Keizai Kenkyu Senta (Transportation Economy Research Center), Research concerning the Improvement Methods for Trunk Express Transportation Systems, March 1980, p. 137. 59 average of urban growth during the past two d e c a d e s . ^ Nevertheless, it is still not certain to conclude that there is a strong relationship between the phased develop­ ment of the Shin Kansen and regional development in Japan until several other factors are considered. Those factors are: 1. strict environmental regulations assigned by local governments in the old industrial zone areas have spurred the outflux of industrial plants to economically underdeveloped regions such as the Tohoku and Kyushu regions; 2. growth management policies represented by the restric­ tion for new construction of office buildings, colleges and universities, and plants in such cities as Tokyo and Osaka have pushed some business activities and students to local areas; 3. sky-rocketing land costs in large cities have impeded the necessary expansion of plants and industries and have eventually pushed out business activities from those cities; 4. the conversion of the energy base from coal to oil and natural gas has required a huge storage capacity, and this has accelerated the new construction of port 41 The urban population in Japan had increased 5 6.3 percent more from 4 0.8 million in 1960 to 63.8 million in 1975. 60 and storage facilities in relatively less populated areas. In fact, since the early 1960's, the so-called "four old industrial zones" which had dominated Japanese industrial activities have lost their status. The sharp reductions of the value of shipments in the prefectural group, B, during the past two decades (which are illustrated in Table 1) are largely due to the decline of the old industrial zones 5. (Figure 8); even the aforementioned government's industrial distribution policy has been behind the movement of population during the last two d e c a d e s . ^ While it is true that these five factors have multiplied the effects of the Shin Kansen system on regional development, it has been broadly said that the development of the Shin Kansen system between Tokyo and Fukuoka has unified the southern half of the Honshu Island economically. It may be theoretically demonstrated that economic development is propagated circularly and cumula­ tively along the major transportation routes joining leading urban-industrial centers as just seen in the 42 The Japanese government designated 13 new industrial cities in 1963 and later added two more. Except for a few cities, most cities have been growing less than originally expected. The detailed study concerning new industrial cities was done by Norman J. Glickman. See Norman J. Glickman, The Growth and Management of the Japanese Urban System, N.Y.: Academic Press, 1979 and Shun1ichi Hagiwara (1977) , pp. 108-110. For details of the Pacific Coast Belt Industrial Zone, see Shun'ichi Hagiwara (1977), pp. 11, 42-46. 61 Group A Group C Old Industrial Zona Group A Group D Sendai ya hama Keihin Industrial Zone ] Group D[ Kitakyushu |Group C Industrial Hlros Zone Chukyo 1Group B| Industrial Zone Hanshin Industrial Zone Group C Group D Figure 8-— Four Old Industrial Zones in Japan. 62 economic development process along the Tokaido and Sanyo Shin Kansens explained above. Pottier, for instance, stressed the self-generating features of modern trans43 portatron system as follows: 1. the appearance of initially developed routes of modern transportation encourages interurban, or interregional, trade between the cities served; 2. the growth of traffic between these cities yields scale economies and lower per unit transfer costs; 3. the resultant, reduced shipping rates further stimulate interurban trade; 4. increased trade creates a demand for new transport facilities and provides the capital for such improvements; 5. repeated iterations of this sequence attract economic activities and population to the transport services and product markets paralleling the original major routes, and particularly to those large centers located at the most nodal route intersections. Although the Shin Kansen system was designed to serve passenger operation exclusively, it is safe to say that the system has generated not only extensive amounts ^ P . Pottier, "Axes de communication et theorie de developpement,” Revue Economique, Vol. 14 cited by Alan Pred and Gunner Toernqvist, Systems of Cities and Information Flows. Lund Studies in Geography, Series B, Human Geography, No. 38, 1973, p. 57. 63 of the human transactions but also extensive amounts of interurban and interregional trade along its route. It should not be unreasonable or invalid to conclude that some definitely positive effects of the Shin Kansen have contributed to the economic development process in Japan during the past two decades. Role of High-Speed, Intercity Passenger Train Systems on Human Contacts and Transactions A number of research investigations undertaken in Japan verify the significant role played by the Shin Kansen on human contacts and transactions. For instance, according to survey research done by the Hiroshima Chamber of Commerce, the following impacts are considered to have been brought on by the creation of the Sanyo Shin Kansen to the Hiroshima area. 1. 44 These are: business communication and contacts became extremely easy. (More than 6 0 percent of the respondents pointed out this merit.); 2. human flow between Hiroshima and such big cities as Tokyo, Osaka, and Fukuoka increased dramatically, especially the flow between Osaka and Hiroshima. (According to the JNR's data, passenger travel 44 Hiroshima Chamber of Commerce Union, The Investiga­ tion concerning the Impacts due to the Opening of the Sanyo Shin Kansen on the Region, (in Japanese), March 1976 (mimeo). 64 between Hiroshima and Osaka increased by 32 percent between 1974 and 1979.) (About 40 percent of the respondents pointed out this merit.); 3. collection of information became very easy (25 percent); 4. competition among businesses became more intensive (about 20 percent); 5. market ranges increased dramatically 6. purchase of goods became easier 7. land price and wages increased (15 percent); (5 percent); (5 percent). The top three impacts revealed in the response are related to human contacts. Similar research was done by the Kyushu Economic Survey Association (KESA) in 1976, and the result was almost the same as the one done by the Hiroshima Chamber of Commerce described above. to the KESA's report, 45 According the number of passengers between the Kyushu area and the Tokyo area increased approximately 2 8 percent and to Osaka by 59 percent in the year of 1975. These figures, however, need to be discounted considerably because the total patronage of the Shin Kansen has dropped rather sharply from 157 million in 1975 to 124 million 46 both in 1978 and 1979. The reasons for this sharp drop 45 Kyushu Economic Survey Association, The Extension of Shin Kansen and Kyushu Economy, (in Japanese), 1976 (mimeo). 46 The Ministry of Transportation, Japan, e d . , The 198 0 White Paper of Transportation, November 198 0, Tokyo: The Ministry of Finance Printing Office, p. 326. 65 in patronage of the Shin Kansen are many. Some attributed the decline to the long-standing sluggish economy in the area since the 197 3 Arab Oil Embargo, but the sharp increase of air passengers from 25 million to 41 million in 1979 (64 percent up) and the increase of automobile traveller from 17,681 million in 1975 to 23,405 million in 1979 (33 percent up) do not justify the above claim. One reason for this drop in ridership could be the sharp increases in fares of the Shin Kansen to make up the deficit from local operations; in fact, the total number of JNR passengers went down only 1.6 percent between 1975 and 1979. Another reason could be the introduction of the so-called "Wide-body Jet," such as the Boeing 747 and DC-10, into the long distance market by the Japan Air Line (JAL) and All Nippon Airways (ANA). Tables 4 and 5 and Figures 9 and 10 clearly illustrate the state of affairs described above. Table 4, for instance, shows the transition of the fares of the Shin Kansen and the above two airlines. that, up until 1975, Note the fare of the Shin Kansen was considerably lower than that of the air mode. In 1975, a regular ticket of the Shin Kansen was less than half of the air fare both for the Tokyo-Osaka and Tokyo-Fukuoka routes. raised rail fare in 197 6 changed The sharply situation rather drastically. the For the Tokyo-Osaka route, for instance, the air fare became only 9 dollars higher TABLE 4. — The Pares of the Shin Kansen and Air Modes. Unit: Yen Route 1970 1975 1976 1977 1978 Shin Kansen 4,130 n.a. 5,010 n.a. 8,300 14,300 8,300 12,300 9,300 13,300 9,500 13,500 (a green tlcket/lst class) Air Kode 6,800 10,600 10,400 10,400 10,400 14,400 5,360 n.a. 8,710 n.a. 14.600 23.600 14,600 20,000 15.300 21.300 15.500 21.500 (a green ticket/1st class) 13,800 20,100 20,100 20,100 20,100 25,900 1979 Tokyo - Osaka Tokyo - HaVata Shin Kansen Air Mode Source; Unyu Kelzai Kenkyu Senta (Transportation Economy Research Center), Research Report concerning the Improvement Hcthods for Trunk Express Transportation System (in Japanese), p. 53. 67 than the rail fare, which was about 38 dollars at that time. The rail fare was raised again in 1978, and the difference between the rail fare and the air fare narrowed more (only 4 dollars for the Tokyo-Osaka route). In 1979, however, the situation again changed considerably. The airlines were obliged to raise their fares rather drastically; the air fare for the Tokyo-Osaka route rose 38.5 percent and for the Tokyo-Fukuoka route 28.9 percent. As a result, for the first time since 1975, the price of a regular ticket of the Shin Kansen became considerably lower than the air fare, and even a first class ticket of the Shin Kansen became less expensive than the air fare by about 50 cents. The impact of this sharp rise of air fares has not been computed yet; however, it will be not so crucial for the air mode, because the JNR, as the national railway corporation, has been, and will be, assigned to serve local areas even though the necessary services are likely to be unprofitable. As a matter of fact, the Shin Kansen system has provided almost 4 0 percent of the total revenue of the JNR, but the distance covered by this system is only 5 percent of the total distance operated by the JNR. The result has been, and will likely be, an annual increase of the rail fare. Such increases steadily lessen the competitive ability of the JNR against the air mode. 68 Figure 9 illustrates the issue described above graphically. Six variables (the number of automobiles, wages, the JNR's rail fare, the consumer price index, the price of automobiles, and the air passenger fare) are selected and compared. As shown, the JNR's rail fare rose more sharply than the consumer price index since 1975 and more than the price of automobiles and air passenger fares since 1974. As a matter of fact, air passenger fares rose only 194 percent since 1967, even after the sharp rise of the fares in 1979, compared with the rail fare which rose 320 percent during the same term. The fare relationship between the rail mode and air mode, however, would be unpredictable; while the JNR's rail fare might be subject to a continuous raise, the air fare also would be quite vulnerable to a continuous hike in the price of crude oil. Local air services could become less and less profitable. Beside the issue of rail and air fares, the most noteworthy trend observed in Figure 9 is the sharp and constant increase in the number of automobiles since 1967. This extremely sharp increase in the number of automobiles (655 percent since 1967) is obviously owing to two facts: one is the sharp increase in wages during the same term (509 percent) and the much slower increase in the price of automobiles during the same term (194 percent). In fact, the share of the automobile mode of transportation in the 69 655 The Humber of Automobile (Index) 600 Wage 509 500 400 320 JNR's Rail Fare 300 261 Consumer Price Index (National) Price of Automobile 200 Air Passenger Fare 100 1968 1970 1972 1977 1975 1973 1971 1969 1967 1974 1976 1979 1977 Figure 9.— Transition of Wage, Number of Automobile, Price of Automobile, Consumer Price Index, Air Fare, and Rail Fare in Japan. SOURCE: The Ministry of Transportation, ed. , 198 0 Transportation White Paper, p. 134. 70 national total of transportation output in terms of passenger-km has constantly increased, from only 4.0 percent (8.8 billion passenger-km) (319.9 billion passenger-km) in 195 9 to 41.1 percent in 1979. During the same term (between 1959 and 1979) the national output increased 350 percent from 221 billion passenger-km in 1959 to 777 billion passenger-km in 1979, but the automobile mode's output easily surpassed the rate of the national increase with 1,60 0 percent. Incidentally, the share of the air mode was 3.9 percent (30.3 billion passenger-km) and the Shin Kansen Share was 5.3 percent passenger-km) in 1979. in 1979 (41 billion Although the share of the air mode is still low, the growth rate of the air mode since 195 9 is a striking 6,200 percent. The Shin Kansen, on the other hand, has been maintaining, more or less, 5 percent of its share in the national total since 1969 (Table 5). Although the sharp increases of the ridership in both the automobile and air mode during the past two decades cannot be ignored, after 15 years of Shin Kansen's operation, the shares of each transportation mode in the Japanese market quite likely has become fixed. Figure 10 illustrates the shares of four different modes of trans­ portation such as air, rail, automobile, and marine in five different markets in three different periods. As clearly shown, the automobile mode governs the market up to 300 km (approximately, 200 miles) and the rail mode TABLE 5.— 1959-1979 Domestic Share by Seven Different Transporta­ tion Modes. Unit: million passenger-km {percentage} National Railways Output 1959 1969 1970 1971 1972 1973 1974 1975 1976 1977 197B 1979 221,292 (100.0) 528,813 (100.0) 587,178 (100.0) 617,848 (100.0) 648,188 (100.0) 674,133 (100.0) 693,596 (100.0) 710,711 (100.0) 709,549 (100.0) 711,033 (100.0) 747,489 (100.0) 777,336 (100.0) Total 114,189 (51.6) 181,520 (34.3) 1B9.726 (32*3) 190,321 (30.8) 197,829 (30.5) 208,097 (30.9) 215,564 (31.1) 215,289 (30.3) 210,740 (29.7) 199,653 (28.1) 195,844 (26.2) 194,690 (25.0) Private Shin Nansen _ (0) 22,816 (4.3) 27,890 (4.7) 26,795 (4.3) 33,835 (5.2) 38,989 (5.8) 40,671 (5.9) 53,318 (7.5) 48,147 (6.8) 42,187 (5.9) 41,074 (5.5) 40,986 (5.3) Railways 56,113 (25.4) 93,804 (17.7) 99,090 (16.9) 99,719 (16.1) 102,469 (15.8) 104,831 (15-6) 108,460 (15.6) 108,511 (15.3) 106,826 (15.3) 112,644 (15.8) 115,285 (15.4) 117,770 (15.2) Bus 39,180 (17.7) 100.192 (18.9) 102,894 (17.5) 100,843 (16.3) 108,211 (16.7) 111,713 (16.6) 115,776 (16.7) 110,063 (15.5) 98,714 (13.9) 104,639 (14.7) 107,009 (14.3) 108,317 (13.9) Autouoblle 8,820 (4.0) 141,869 (26.8) 181,335 (30.9) 211,635 (34.3) 220,346 (34.0) 225,732 (33.5) 228,400 (32.9) 250,804 (35.3) 264,499 (37.3) 263,961 (37.1) 296,043 (39.6) 319,869 (41.1) Air 489 (0.2) 6,991 (1.3) 9,319 (1.6) 10,304 (1.7) 12,663 (2.0) 16,035 (2.4) 17,639 (2.5) 19.14B (2.7) 20,119 (2.8) 23,636 (3.3) 26,923 (3.6) 30,246 (3.9) Source; The Hlnlstry of Transportation, Japan, The 1980 White Paper of Transportation, p. 326. Waterborne 2,500 (l.l) 4,439 (0.8) 4,814 (0.8) 5,026 (0.8) 6,670 (1.0) 7,724 (1.1) 7,756 (1.1) 6,895 (1.0) 6,651 (0.9) 6,500 (0.9) 6,384 (0.9) 6,443 (0.8) 72 100-300 km 300-500 km 1965 f water borne Auco 44.2 xSRLtt ’■■ Air 2§gl2. Es-, 2.0 * a 6 56.6 1971 Waterborne 9 .0 ■ 2 1 .( 2.9 -•'7.9 1978 26.2 72.3 500-750 Van Water Auto borne 0.7 5.6 750-1,000 km 5.4 Auto Waterborne 1965 1971 1978 3 i;'4 : 1,000 km &Over Waterborne 0.3 1965 1971 Source: The Ministry of Transportation, Japan The 1980 White Paper of Transportation, p. 139. 1978 Figure 10.— Share of Four Transportation Modes for Five Different Ranges. 73 governs the market between 300 and 1,000 km (200 to 625 miles). Beyond 1,000 km, the air mode strongly governs the market with more than 65 percent of the share. Throughout the analyses of the data observed in Tables 4 and 5 and Figures 9 and 10, it has become clear that the Japanese HSIPT system, the Shin Kansen, will continuously capture the patronage in the market from 200 to 600 or 700 miles, and its share in the national market would be more or less 5 percent. A consistent . contribution to the increase of the ridership, however, can be expected from the completion of both Tohoku and Joetsu Shin Kansens in 1984. Through the previous analysis, it has become clear that the Shin Kansen has been accommodated in the Japanese transportation system as a key channel for human contacts and transactions, especially in the market range between 200 and 600 miles. In the following text, the nature and characteristics of the patrons of this system will be investigated. This investigation is necessary to examine Thorngren's proposition that the contact work will mainly be performed by people in higher positions and by professionals. Recently (1977), the JNR made a survey concerning the characteristics of the patrons of the Shin Kansen. 47 47The JNR, The 1977 Survey Concerning the Characteris­ tics of Passengers of the Shin Kansen. (in Japanese), (mimeo). 74 The following sections are summaries of data tabulated by the JNR and released by it: Purpose of trips - Among 42 3,000 passengers who took the Shin Kansen on October 13, 1977, 298,676 took HIKARI (70.6 percent) (the fast train which stops only at large cities such as Tokyo, Osaka, Nagoya, Kyoto, Hiroshima, and Hakata, which is the name of the station for the • * City of Fukuoka), and the rest, 124,623 (29.4 percent), took KODAMA (the slower train which stops at every station along the Shin Kansen routes). Incidentally, HIKARI means LIGHT in English and KODAMA means ECHO. Seventy-seven percent of HIKARI passengers and almost 80 percent of KODAMA passengers claimed their trips were business-related. Reasons for using the Shin Kansen - For HIKARI passengers, SAFETY came first and FASTNESS and RELIABILITY came in second and third. For KODAMA passengers, FASTNESS came first, and SAFETY and RELIABILITY came second and third. These are very interesting responses. For HIKARI passengers who travel between large cities, the air mode is still faster than the Shin Kansen mode, but they esteem the Shin Kansen's achievement in safety greatly. For KODAMA passengers who travel between a large city and smaller cities, or between smaller cities, the reduction of time-distance due to the creation of the Shin Kansen must have been tremendous compared to 75 the service offered by the old rail system or by the automobile. The differences found in the responses from HIKARI and KODAMA passengers should be understood in such a manner. Other reasons pointed out by both HIKARI and KODAMA passengers are: the appropriateness of the DISTANCE traveled by the Shin Kansen mode, LOWER FARES compared with other modes of transportation {keep in mind, the cost of gasoline, which has been approximately $2.50 per gallon, is much higher than that in the United States), COMFORTABLENESS, DESIGNATED MODE OF TRANSPORTATION by employer, GOOD FOR GROUP TRAVELLERS, and NO OTHER TRANSPORTATION MODES AVAILABLE. The number of days spent, or will spend, for the trip For HIKARI passengers, three days comes first percent), then, two days four and six days trip. (26.9 percent), and between (22.3 percent) follow the three day 11.7 percent of HIKARI passengers claimed a single day trip. first (2 8.7 For KODAMA passengers, two days comes (32 percent), then one day (29.4 percent), and three days (19 percent) follow the two day trip. From these data, it is clear that KODAMA passengers spend lesser days than HIKARI passengers for their trips. Further, 67.3 percent of HIKARI passengers and 80.4 percent of KODAMA passengers spent less than four days for their trips. 76 When the trip was planned or decided - For HIKARI passengers/ two to seven days before the trip comes first (27.8 percent), then eight to fourteen days comes second (15.3 percent)/ and a month before comes third percent). (15.1 Twelve percent of HIKARI passengers decided their trips a single day before and 7 percent decided their trips on that particular day. For KODAMA passengers, 55.5 percent decided their trips less than a week before. The data shown here clearly indicate the characteristics of the Shin Kansen. The Japanese Shin Kansen is the mode of transportation that is always available for the travellers; in other words, CONVENIENCE will always be one of the strong characteristics of the Shin Kansen. This characteristic is strongly supported by the fact that almost twenty percent of the HIKARI passengers and thirty percent of KODAMA passengers planned or decided their trips either a single day before the date of trip or on the day of the trip itself. This characteristic of the Shin Kansen will also be supported by the next piece of data. When the ticket was purchased - More than 5 0 percent (51.1 percent) of HIKARI passengers and 40 percent of KODAMA passengers purchased their tickets on the date of the trip or a single day before. Which age blocks use the Shin Kansen most - Among m e n , the thirties is the largest block, then the forties and 77 twenties follow the thirties. Among women, the twenties comes first, then the forties and fifties follow the twenties. For HIKARI passengers, the twenties, thirties, and forties age blocks occupy more than 70 percent (71.9 percent) and for KODAMA passengers, the twenties, thirties, and forties occupy approximately 7 0 percent (69.9 percent). Further, 77.7 percent of HIKARI passengers and 77.6 percent of KODAMA passengers are male. Occupations of the passengers - Employees of private companies and public institutions occupy the biggest category (53.5 percent). Executives of private companies or public institutions occupy the second (11.5 percent). housewives The third biggest category was (11.4 percent). Self-supporting merchants and manufacturers follow the housewives (5.2 percent). Students come seventh, a mere 5 percent. How many persons make a group for the trip - Companionless passengers make up the highest group (4 6.7 percent in HIKARI passengers and 4 4.4 percent in KODAMA passengers). Two person groups come second (26.1 percent in HIKARI and 24.5 percent in KODAMA passengers). 48 48 The writer's personal experience also supports the propositions explained by Thorngren. After the creation of the Shin Kansen between Tokyo and Osaka, business trips assigned to the writer increased dramatically. Between 1970 and 1973, when the Japanese economy flourished, the amount of business trips primarily to Osaka had reached 78 From these data, the profiles of the Shin Kansen passengers are: men in the twenties, thirties, and forties and women in the twenties, forties, and fifties. Occupa­ tions include company or public institution employees or executives in the men's block and company employees or housewives in the women's block. The days spent for the trip are usually less than four days. The passengers highly esteem the performance of the Shin Kansen in terms of safety, speed, and reliability. Finally, most of the purposes for their trips are business-related. These characteristics of the Shin Kansen passengers are very much similar to the ones found in the Northeast Corridor's more than a hundred a year. This had never happened when these two biggest cities were connected with the timedistance of more than eight hours or even with six hours just before the Tokaido Shin Kansen was created. The reduction of travel time from six hours to three hours (presently, the Shin Kansen ties Tokyo and Osaka in three hours and ten minutes) has made it possible to attend afternoon meetings at the same day in different places more than 4 00 miles apart. More importantly, this system made it possible to finish a business trip in a single day. This saves a lot of expenses previously incurred by business trips. The amount of per-diem expenses necessary for a three-day trip were reduced to those for one-day. The accommodation cost was eliminated for a single-day business trip. Another experience of the writer reveals a significant effect of the increase of speed and capacity of this transportation system on face-to-face contacts. In 1972 and 1973, the writer was engaged in a tourism development project in Seoul, Korea. The succeeding introduction of the "Jumbo Jet (B-747)" to the Seoul-Tokyo route by the Japan Air Line and the Korean Air Line had made the travel between those two cities safe, easy, and frequent. As a consequence, the writer was obliged to travel to Seoul more than twenty times during those two years to attend meetings necessary for the project. 79 rail passengers. According to the report released by the 49 U.S. D O T , rail passengers on the Northeast Corridor are profiled as: male/ age 25-44, married, $25,000 or more annual income, college or graduate degree holders, engaged on business trips, professional and technical employees, and also professors and students. Although no income and marital data are available in the JNR's study, there is no doubt that there is a significant correlation between the Shin Kansen passengers and the Northeast Corridor's rail passengers. In both cases, fairly highly educated people often use both rail systems and the purpose of their trips is mostly business. The data from this JNR Survey can be aggregated and analyzed in a myriad of contexts which would lead to different conclusions. Useful to the context of this dissertation, the following conclusions are judged to be highly significant. Throughout this part of the research, it has become clear that the Shin Kansen has greatly contributed to intensifying human contacts, especially among profes­ sional employees, businessmen, and executives. Those human contacts performed by people in higher positions definitely stimulates the information exchange necessary 49 The U.S. Department of Transportation, Two-Year Report on the Northeast Corridor, Wash., D.C.: U.S. Government Printing Office, 1978, pp. 27-43. 80 for the innovation of technologies and the expansion of markets. To be the key channel for the human contacts which are indispensable for further expansion of economic activities in any region or any country, a HSIPT system must be planned by taking into account the following points: 1. A HSIPT system should be planned to join medium and large cities; 2. A HSIPT system should be planned to secure safety, reliability, and speed to be competitive with other modes of transportation such as automobile, bus, and air; and 3. A HSIPT system should be planned to serve distances between 300 and 1,000 km (200 to 600 or the maximum of 700 miles). Positive and Negative Aspects Inherent in the Development of a HSIPT System The positive aspects of a HSIPT system may be arranged as follows: 1. Primary impacts such as the reduction of time-distance, the augmentation of transportation capacity, and the derived impacts from the accompanying investment with the construction; 2. Secondary impacts such as the conservation of energy and the enhancement of the tourist trade; 81 3. Tertiary impacts such as the enhancement of social and cultural motivation, human contacts, and the enlarge­ ment of market spheres. As can be seen, most of these positive aspects of a HSIPT system have been discussed in the previous text. Among these various positive impacts, a much more clearly visible benefit due to the creation of a HSIPT system will be its energy-saving saving) ability. (in more concrete term, petroleum- As mentioned earlier, British Railways decided to replace its diesel-powered HST system with an electricity-powered AGT system primarily because of the concern for the source of power, oil. In France, according to T I M E , the TGV uses little more energy than conventional trains, and since much of France's electrical grid is powered by hydroelectric or nuclear energy, the nation's growing investment in electric railroads will help lessen its dependence on imported oil. 50 In Japan, according to Takeshi Tamura, Director of the Japanese National Railways' New York Office, the Shin Kansen has saved more than 40 million barrels of crude oil annually. 51 For instance, according to him, in 1977 it took 4.4 million barrels of heavy oil to generate electricity for the Shin Kansen system. If the 124 million riders (the number of the 5°T I M E , October 5, 1981. C 1 The NGA, Committee on Transportation, Commerce and Technology (1981), Appendix III. 82 Shin Kansen patrons: the writer) had used automobiles, allowing 2.2 passengers per car and 14 miles per gallon, they would have consumed 20.6 million barrels of gasoline or 46.1 million barrels of crude oil. The difference is a savings of 41.7 million barrels of crude oil. As can be seen, the assumption behind this calculation is very simple and arbitrary; however, if electricity for a HSIPT system is produced from coal (such as is the possible case in the United States) or nuclear energy, the possible savings of crude oil can be substantial. In addition to t h i s , if a HSIPT system can successfully reduce ten percent of the automobile ridership in intercity travel in the United States, the impact of crude oil saving will be tremendous. Presently, 30 percent of the crude oil consumed in the United States is consumed by the automobile, and more than 85 percent of intercity travel is made by the automobile. 52 The negative aspects of a HSIPT system are roughly classified into two areas. One is the direct negative impacts inherent in the creation of a HSIPT system such as noise and vibration due to a high-speed operation. For instance, the JNR and Japanese government appropriated 38 billion yen 52 ($190 million) in 1979 and 24 billion yen National Transportation Policy Study Commission, National Transportation Policies Through the Year 20 00: Final Report, June 1979, Wash., D.C.: U.S. Government Printing Office. 83 ($120 million) in 1980 to the residents along the Tohoku and Joetsu Shin Kansen routes as compensation for noise and vibration. 53 The other is the so-called "counter-flow effect" which has been seen in Japan since the completion of the Tokaido Shin Kansen. According to the writer's study, the subsidence of administrative functions of such large cities as Osaka and Nagoya (the second largest city in Japan) (the third largest) since they were joined to Tokyo in 1964 has been conspicuous.5^ It has been broadly said that even the island of Kyushu's economy has been absorbed by the central economy represented by Tokyo's economic structure since the completion of the Sanyo Shin Kansen. In fact, the perception of a HSIPT system by people in large cities and in smaller cities are often remarkably in discord. In the Japanese experience, people in large cities such as Tokyo and Osaka regard the HSIPT system as a device for further concentration of various functions, such as financial, managerial, operational, administrative, and even technological. People in local areas, on the other hand, regard the HSIPT system as a device to accelerate the decentralization of the above functions. 53The Ministry of Transportation 54 (1980) , p. 90. Concerning the details of the "counter-flow effect" of the Shin Kansen, refer to Shun'ichi Hagiwara (1977), pp. 91-94. 84 This disparity emerges as an obvious difference in the evaluation of actual effects of the Shin Kansen. According to a survey done by the Hiroshima Chamber of Commerce, discouragement about the Shin Kansen is often seen among local people and businesses, especially retail businesses. On the contrary, those businesses such as construction, manufacturing, wholesale, finance and insurance, and services which manage their businesses regionally or nationally regard the effects of the HSIPT system (the Sanyo Shin Kansen in this case) fairly positively. Some of the discouragement with, or dissatisfaction about, the effects of the Shin Kansen expressed by retail business are: 1) a sharp increase of competition with those fellow businesses from large cities (big capital) and 2) diversified demand from the customers. Structural adjustments are necessary for such changes, but it is extremely difficult to achieve for locally based businesses with limited capital or restricted sources of information. 55 In fact, the so-called big businesses generally evaluate the Shin Kansen highly as a key means to expanding their business activities to local areas, which usually takes the form of opening new branches or liason offices. These sorts of reactions, perceptions, and evaluations concerning a HSIPT system by various different groups should be taken 55 The Hiroshima Chamber of Commerce Union (1976), pp. 1-20. 85 into account by HSIPT system planners. Once knowing these, a system planner can guide, instruct, and help to convince the public not to overestimate or underestimate what are often unknown or unmeasurable impacts of any proposed HSIPT system. In this chapter, the nature and characteristics of HSIPT systems were introduced. Foreign experiences with HSIPT systems were described and examined. Various problems inherent in the creation of a HSIPT system were investigated. In the following chapter, the probable and possible impacts on forty local communities within of such HSIPT system, if it were to be created in the Great Lakes Midwest Region, will be investigated. CHAPTER III PROBABLE IMPACTS OP THE CREATION OF A HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEM: THE GREAT LAKES MIDWEST REGION - A CASE STUDY This particular chapter is divided into two parts. Firsts the bases for the designation of the principal HSIPT system corridors which were assumed to be created in the Great Lakes Midwest Region are introduced. Various studies implemented by the states and the U.S. Department of Transportation (DOT) concerning the possible HSIPT system corridors in this particular region are examined. Secondly, the probable and possible impacts of the creation of a HSIPT system in the Region on the forty local communities which are assumed to be joined by the system are also examined. The concepts of the "population potential" and "population energy" to determine before and after indices of spatial isolation of the forty local communities are applied in this analysis. Development of the Rationales for the Great Lakes HSIPT System Corridors As mentioned in the introductory chapter, the installation of a HSIPT system has been hypothesized for the Great Lakes Midwest Region, as a basis for this research undertaking. Further, one of the HSIPT system 86 87 corridors was assumed to be located so as to join 17 U.S. SMSAs and 3 Canadian CMAs in the Region; and the Lansing metropolitan area was assumed to be one terminal point on the Midwestern corridor system. The bases for these two assumptions take into account the following three studies done by the States of Michigan and Ohio and the U.S. Department of Transportation. As mentioned before, Michigan and Ohio have been studying an intra-state HSIPT system independently. Michigan, for instance, is studying four possible intra­ state routes, from Detroit to Grand Rapids (Figure 11) and now is in the process of working out an agreement with Amtrak to provide daily round trip service from Grand Rapids to Chicago. 56 A second study is one developed already by Ohio with a detailed plan for an intra-state HSIPT system as shown in Figure 12. A third study is one by the U.S. DOT, which had studied a HSIPT system a decade ago and released a plan for a possible High-Speed Ground Transportation (HSGT) network in 1973 (Figure 13). Taking into account the above three studies and the location of urban centers within the Region (Figure 14), the principal HSIPT system corridors were designated as shown in Figure 15. This Great Lakes' HSIPT system network joins 17 U.S. SMSAs such as Milwaukee, Chicago, Gary, Indianapolis, e^ The NGA Committee on Transportation, Commerce and Technology (1981) , p. 6. 88 GRAND RAPIDS DURAND pont: JACKSON. DETROIT ANN ARBOl CHICAGO / Figure 11.— Four Possible Intra-State High-Speed Rail Plan. SOURCE: Michigan Department of Transportation cited from the Lansing State Journal, December 7, 198 0. ■I^^B J H OHIO Service Only OHIO Service with Out-of-State Connections Figure 12.— Ohio Intra-State High-Speed Rail Plan SOURCE: Ohio Rail Transportation Authority, Ohio High Speed Intercity Rail Passenger Program, p. 39. Compiled by Shun'ichi Hagiwara. Mikneapolis ston/Neu U) O Louis Philadelph 14 ’♦Washington St. Loul a via Louisville 1L 12 13 14 Southbend 15 16 Kalamazoo Grand Rapids 17 18 B Lansing 19 9 Detroit 20 10 Toledo 21 Madison Milwaukee Chicago Gary Cleveland Akron Youngstown Pittsburgh Columbu3 Dayton Lima Cincinnati Indianapolis Erie Buffalo Figure 13.— Preliminary National High-Speed Ground Transportation Network (Part) SOURCE: U.S. DOT, High Speed Ground Transportation Alternative Study, January 1973, pp. 4-11. non SMSA (U.S.) Census Metropolitan Area (CMA), Canada non CKA (Canada) Population Cl.000a) SMSA 1 Madison 290 2 Milwaukee 1,404 3 Chicago 6,975 A Rockford 272 5 Peoria 342 6 Davenport 363 7 Gary 633 8 Southbend 280 9 Fort Uayne 362 10 Indianapolis 1,111 11 Louisville 867 12 Lexington 267 13 Cincinnati 1,387 14 Dayton 853 15 Columbus 1,018 16 Lima 210 17 Toledo 763 18 Cleveland 2,064 19 Akron 679 20 Canton 394 © © 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 537 Youngstown 2,401 Pittsburgh 264 Erie Buffalo 1,349 Detroit 4 .435 Port Huron* 36 Saginaw 220 Flint 509 Ann Arbor 234 Jackson 259 Lansing 424 Battle Creek 142 Grand Rapids 539 Kalamazoo 258 Windsor** 259 Sarnia*** 79 286 London** Toronto** 2,628 499 Hamilton** Niagara Falls***303 Figure 14.— Geographical Distribution of SMSAs' Population in the Great Lakes Midwest Region. to H VD N) 1 2 3 4 5 6 7 8 9 10 Milwaukee Chicago Gary Kalamazoo Grand Rapids Lansing Flint Detroit Toledo Cleveland 11 12 13 14 15 16 17 18 19 20 Akron Youngstown Pittsburgh Colorabus Dayton Cincinnati Indianapolis Uindsor London Toronto Figure 15.— Proposed Great Lakes Midwest Regional HSIPT System 93 Cincinnati, Dayton, Columbus, Toledo, Cleveland, Akron, Youngstown, Pittsburgh, Detroit, Flint, Lansing, Grand Rapids, and Kalamazoo and 3 Canadian CMAs such as Windsor, London, and Toronto. Missing is a direct route between Chicago to Toledo, Ohio, via South Bend, which may require separate explanationRail networks have traditionally been located in response to political considerations regardless of the fact that historically highly negative consequences have resulted from such politically-based decisions. Even now, the committment or aggressiveness of so-called special interest groups would be the key for the final decision on a HSIPT system network. Among the so-called Great Lakes' states of Wisconsin, Illinois, Indiana, Michigan, Ohio, Pennsylvania, and New York (Minnesota was excluded, because it is not accommodated in the Great Lakes Midwest Region in this research), Indiana is the only state which has consistently avoided the HSIPT issue. In fact, except Indiana, such states as Illinois, Michigan, Wisconsin, Pennsylvania, and New York have been allocating considerable amounts of their budgets to the passenger transportation system study. Where this reluctance of Indiana about passenger transportation system comes from is unclear, but one of the reasons might be that Indiana has, so far, benefited very much from the interstate highway system. Also, the existence of a single dominant urban canter. 94 Indianapolis, located in the middle of the State and its remoteness from urban centers in other states might have been another reason for Indiana’s indifference to an interstate HSIPT system. The exclusion of Southbend and Port Wayne from the proposed HSIPT system network could possibly illustrate the problems which those two Indiana urban centers might encounter were they to be excluded from the assumed HSIPT system. Concepts of “Population Potential" and "Population Energy" as Indices to Measure the Magnitude of the Probable Impacts of a High-Speed Intercity Passenger Train System A number of the studies concerning the probable impacts of a HSIPT system have been done in Japan. 57 Most of these studies adopted simulation techniques based on an econometric model and could not be free from the 57 Kozo Amano, "The Impacts of the Tokaido Shin Kansen on Regional Economy," Unyu To Keizai (Transportation and Economy), Vol. 29, No. 2. Ittchu Tada, "The Development of the Tohoku District and the Tohoku Shin Kansen," Unyu To Keizai, Vol. 29, No. 2. Miyagi-Ken Tohoku Shin Kansen Kensetsu Suishi Hombu, The Effects of the Construction of the Tohoku Shin Kansen and the Direction of the Regional Improvement. March 1975 are the notable ones among many others. 95 limitations of such techniques as pointed out in the following. A forecast demand on an econometric model whose parameters are determined from historical relation­ ships cannot be expected to project truly dramatic traffic shifts, unless a large change in a variable is hypothesized (e.g., the real price of auto gasoline quadruples), or the parameters themselves are arbitrarily adjusted based on the forecaster’s own judgment. The former requires a priori documentation for such a break with historical trend, and the latter removes the rationale for employing models. For instance, the growth of the GNP assumed by the "flmano Model"— cumulatively, between 1975 and 1980, 10.7 percent— cannot now be expected and the necessary adjustment based on the actual GNP can be tremendously troublesome. 5 9 In 197 0, Hirozo Ogawa of Hokkaido University tried to clarify the effects of the Tokaido Shin Kansen on regional development by adopting the concept of the "Demographic Influence" originally developed by J. Q. Stewart of Princeton University. Ogawa adopted this principle, not only because it was simple and straightforward, but also because it could reflect the 58Frank P. Mulvey with National Transportation Policy Study Commission, AMTRAK: AN EXPERIMENT IN RAIL SERVICE, NTPSC Special Report No. 2, September 1978, Wash., D.C.: National Transportation Policy Study Commission, p. 154. 59 Concerning the details of the "Amano Model", see Shunichi Hagiwara (1977), pp. 89-91. 96 impact of the reduction of time-distance by the Shin Kansen most rigorously.^ Ogawa applied this "Demographic Influence" concept, which is also called by Stewart the "Population Potential," to the cities on the Tokaido Shin Kansen route where the terminals of the Shin Kansen were located. As mentioned earlier, the "Population Potential" in Stewart’s concept is depicted by the equation, N/d, in which population of the city city (N) is the (j) at a distance (d) from the (i) which can be influenced by the city (j). The equation which illustrates this relationship is: m X P. = E G — 1 j=l Dj. . where P. = population potential at i Xj = the number of population at j Dij= the distance between i and j G = constant i = 1 , 2 , ..... n j =1,2, ,m Because the objective of Ogawa's research was to investigate the impacts of the time reduction by the Shin Kansen, he naturally used the time-distance rather than geographical distance between cities. Hence, three different time-distances between the cities on the Tokaido Shin Kansen route were used. Those are: 1) the time- distance right before the Tokaido Shin Kansen was intro­ duced; 2) the time-distance at the time the Tokaido Shin CQ Hirozo Ogawa and Etsuo Yamamura (1975), pp. 27-31. 97 Kansen started its operation in 196 4; and 3) the timedistance after a one-year trial time in 1965. The transition of the time-distance and the results of Ogawa's study are shown in Table 6. According to Ogawa, the figures in Table 6 should be interpreted as follows: 1. Because of its own strong population potential, Tokyo does not receive a significant impact from the drastic time-distance reduction due to the creation of the Shin Kansen, but gives a strong impact on others; 2. Yokohama is the only city which experiences a decrease in its "population potential." This was primarily due to the poor selection of its terminal. As a matter of fact, the Shin Kansen terminal for Yokohama was built in the area far from the downtown Yokohama site which could have been the optimal site for the terminal. To make matters worse, the synchronized transportation systems are not provided for at this new Shin Kansen terminal. The passengers to and from Yokohama, as a consequence, rather get on and off the train at the next terminal, Tokyo, which is just thirty minutes away by commuter trains; 3. Gifu's potential also does not move up as desired by the local community. Yokohama can be cited. A reason similar to the case of The terminal for Gifu City is actually built at Hajima City, a small city with the TABLE 6.— Transition of Demographic Influence Due to the Shin Kansen. Tokyo Yokohama Shizuoka Nagoya Gifu Otsu Kyoto Osaka Total Actual FlRure(Person/minute) March, 1964 252,575 557,840 October, 1964 278,348 521,304 November, 1965 300,120 518,132 205,102 249,243 311,258 240,348 309,856 328,B38 384,879 401,738 432,195 478,328 528,785 633,406 415,470 552,091 672,037 183,990 253,753 317,280 2,718,532 3,095,119 3,567,265 Index (3) March, 1964 100.0 October, 1964 110.2 November, 1965 118.8 100.0 121.5 151.7 100.0 128.9 159.3 100.0 104.4 112.3 100.0 110.6 132.4 100.0 132.9 161.8 100.0 137.9 172.4 100.0 113.9 131.2 100.0 93.5 92.9 Source: Htrozo Ogawa, "Kotsu to Toshi Hatten," in Yoahinosuke Yasojima (ed.), Toahl Kotsu Koza I (Lecture Series in Urban Transportation I >. Tokyo: Kashlma Kenkyuaho Shuppankai, 1975. p.29. Note; The time-distance between Tokyo and Osaka changed as follows: March 1964 October 1964 November 1965 6 hours 00 minutes 4 hours 00 minutes 3 hours 10 minutes 99 population of 45,00 0, compared with Gifu's population of 360,000. An absence of a synchronized transportation system between these two cities again lessens the effect of the Hajima terminal; 4. The remaining cities, such as Shizuoka, Nagoya, Otsu, Kyoto, and Osaka, enjoyed a growth of their population potentials. Osaka, in particular, increased its population potential by 7 3 percent. As a conclusion, Ogawa sees the effects of the Tokaido Shin Kansen as "the system which joined Osaka and Kyoto to Tokyo rather than Tokyo to Osaka and Kyoto." The results of Ogawa's study are well supported by the JNR's data concerning the passengers' on and off at each city's terminal (Table 7). As shown, the number of the passengers who get on and off at the Shin Yokohama terminal, which is the terminal for the city of Yokohama, is the fourth from the lowest with 2,008,901. that the population of the City of Odawara If one knows (whose ridership amount is the fifth from the bottom), is only one-fifteenth of that of Yokohama, it will be quite easy to understand how the selection of the site for the Shin Kansen terminal is important. the least. Also, as expected, Gifu-Hajima's data is This is significant if one knows that the population of Gifu is 2.5 times bigger than that of Odawara, whose ridership is two times bigger than that of Gifu. Further, the passengers who get on and off at 100 TABLE 7.— Number of Passengers at each Terminal of the Tokaido Shin Kansen (1972). No. of Passengers from each Terminal to Shin Osaka 22,609,686 1,744,606 1,264,166 1,033,328 978,256 2,332,078 1,333,684 517,908 5,103,865 691,572 542,237 149,254 38,300,640 Name of Terminal (origin) Tokyo Shin Yokohama Odawara At ami Mlshima Shizuoka Hamamatsu Toyohashi Nagoya Gifu Hajlma Maibara Kyoto Shin Osaka No. of Passengers from each Terminal to Tokyo __ No. Of Passe gets who get on and off at each Terminal 26-',,295 820,279 1,779,857 1,854,224 2,211,329 1,572,547 1,229,691 7,654,871 354,792 1,370,435 7,042,579 11,012,301 22,609,686 2,008,901 2,084,445 2,813,186 2,832,480 4,543,407 2,906,231 1,747,599 12,758,736 1,046,364 1,912,672 7,191,833 11,012,301 37,167,200 75,467,840 Source: Unyu Keizai Kenkyu Senta, Kanaen Kosoku Kotsu Taikel no Seibi Hoahikl nl kanauru Kenkyu Chosa Hokokusho fin Japanese). Tokyo: Unyu Keizai Kenkyu Senta, March 1980. p.23. The original data H a t e d above were released by the Japanese National Railways(JNR). 101 the Kyoto and Osaka terminals (the combined figure: 18.2 million) is about 8 0 percent of the number for Tokyo. This figure is extremely high if one knows that the population of the Osaka metropolitan area (14.2 million including Kyoto and one other urban prefecture, Hyogo which is located west to Osaka) is only 57 percent of the population of the Tokyo metropolitan area, which is composed of four prefectures with a population of approximately 25.0 million. Although Ogawa stresses that the study concerning the effect of the Shin Kansen by adopting the "population potential" concept can be a simple and reliable way to reflect some of the important roles which the Shin Kansen can achieve in regional development process, he himself admits the shortcomings of his study. The shortcomings pointed out by Ogawa, himself, are: 1. The study was restricted to only the cities where Shin Kansen terminals were constructed. The impact of the Shin Kansen on the adjacent prefectures or cities and also on the rest of the nation was not figured into this study; 2. Except for the cases of Yokohama and Gifu (Hajima), where the terminals were located at extremely inconvenient places, the internal traffic friction due to congestion or lack of synchronized transportation systems in other cities was not taken into account; 102 3. The frequency of the services of the Shin Kansen was not taken into account. One of the most important shortcomings of this study is, however, that the formula for the "population potential" study cannot take into account the "population potential" of its own area. Namely, if the time-distance between a large city and a smaller city was significantly reduced, its impact on the "population potential" is always greater to a smaller city and lesser to a large city. This is often true, but it is also reasonable to consider that the reduction of the time-distance between a large city and a smaller city not only stimulates the smaller city's "population potential," but also the larger city's "population potential." Later, in 1973, Yamamura and Maki adopted the aforementioned "population energy" concept and examined the statistical relationship between the "population energy" indices of 46 prefectures in Japan 61 and 22 socio-economic variables of those 4 6 prefectures. The formula used by Yamamura and Maki is as follows. The "population energy" of each prefecture calculated from the following formula strongly correlated with 22 socio­ economic variables (Appendix I). ^ E t s u o Yamamura and Hiroyuki Maki, "Tohoku Shin Kansen to Dainapolis Keisei (The Tohoku Shin Kansen and the Formation of the Dinapolis)," Chrigaku Kenkyu, Vol. 3, 1973. 103 = m X^Xj Z G ---- where j= l = xi = Xj = D^j= b G population energy at i population at i population at j the shortest distance or time between i and j = an exponent describing the effect of the distance or travel time between i and j (distance disutility parameter) = constant Yamamura and Maki then utilized the above formula to predict the possible impacts of the Tohoku Shin Kansen on the Tohoku region. Although they made a precise prediction about the growth potentiality of each of six prefectures in the Tohoku region, the reliability of their study is not verified yet because of the delay in the construction of the Tohoku Shin Kansen. Two studies done by Ogawa and Yamamura and Yamamura and Maki, respectively, and the study done by Stewart convinced this author to utilize the two concepts of "population potential" and "population energy" to project the probable impacts due to the creation of a HSIPT system within the U.S. Region. In the following section, the magnitudes of the probable impacts due to the creation of a HSIPT system on each of the 40 local communities within the Region will be examined. 104 Magnitudes of the Impacts of the Creation of a HSIPT System on the Forty Local Communities Within the Great Lakes Midwest Region Before getting into the detailed analysis concerning the magnitudes of the impacts of the creation of a HSIPT system within the Region, four assumptions, mostly concerning traveller behavior, were adopted. 1. As shown in Figure 15 on page 92, the proposed HSIPT system network joins 17 SMSAs and 3 CMAs in Canada; however, the impact study will be extended to twenty other local communities in the United States and Canada. The configuration map of those 4 0 local communities where the impacts of the creation of the HSIPT system will be felt is shown in Figure 16; 2. A HSIPT system will definitely be used if the time a passenger has to be in the train is approximately 4.5 hours. This 4.5 hour ride assumption is based on the hypothesis about the business trip behavior. The writer assumes that businessmen travel willingly if they don't need to leave their homes before 7 o'clock a.m. and are able to come back home by 11 o'clock p.m. In reality, however, most businessmen will spend a few days for their business trips, as assertained by the JNR, but it is also true that a considerable number of businessmen will have to spend only one day for their The Planned High-Speed Intercity Passenger Train Network The Interstate Highway Network 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Youngstown Pittsburgh Erie Buffalo Detroit Port Huron Saginaw Flint Ann Arbor Jackson Lansing Battle Creek Grand Rapids Kalamazoo Windsor Sarnia London Toronto Hamilton Niagara Falls Figure 16.— The Planned High-Speed Rail Network and 40 Local Communities. 105 1 Madison 2 Milwaukee 3 Chicago 4 Rockford 5 Peoria 6 Devenport-Rock Isla -Moline 7 Gary 8 Southbend 9 Fort Wayne 10 Indianapol 11 Louisville 12 Lexington 13 Cincinnati 14 Dayton 15 Colombus 16 Lima 17 Toledo 18 Cleveland 19 Akron 20 Canton 106 business trips. (According to the JNR's data explained in the previous chapter, almost 12 percent of the Shin Kansen passengers spent a single day for their trips.) Although the writer assumes that businessmen in the United States will stay as much as four and a half hours in the train, if it is necessary, 90 percent of the Japanese Shin Kansen users have spent about 3.5 hours in the train. During this 3.5 hour ride in the Shin Kansen, the Japanese businessman can travel approximately 350 miles at an average speed of 100 mph. The American businessmen, on the other hand, can travel approximately 5 00 miles with an assumed average speed of 110 mph. A typical businessman's single day trip schedule is likely to be as follows: For a Chicago businessman who wants to travel to Cleveland, « ------ *» o o Leave home by car 0.5 hours Take the first train at Chicago terminal 7: 3 0 : 4.5 Get off the train at Cleveland terminal 12:00: 1.0 Business deal or meeting starts 1: 004.0 Business deal or meeting adjourns 5: 00: 1.1 6: 101 4.5 10:40n Take the train from Pittsburgh at Cleveland terminal Get off the train at Chicago terminal 0.5 11:10^ Back home 107 For a Lansinq businessman who wants to travel to Cleveland ■ o in 00 Leave home by car 0.5 hours 9.20: 2.5 " 11:50: Take the first train from Chicago at Lansing terminal Get off the train at Cleveland terminal 1.1 1:00: Business deal or meeting starts 4.0 5:00: Business deal or meeting adjourns 1.1 6:10: Take the train from Pittsburgh at Cleveland terminal Get off the train at Lansing terminal 2.5 8:40: 0.5 9:10- Back home Another possible case would be that of a business­ man who lives in a community where a HSIPT system terminal will not exist: For a Battle Creek businessman who wants to travel to Cleveland, 8: 00 - Leave home by car 1.3 hours 9:20: 2.5 II 1.1 II 4.0 II 1.1 rt 2.5 n 1.3 it 11:501:00: Take the first train from Chicago at Lansing terminal Get off the train at Cleveland terminal Business deal or meeting starts 5:00 = Business deal or meeting adjourns 6:10 : 8:40: 10:00- Take the train from Pittsburgh at Cleveland terminal Get off the train at Lansing terminal Back home According to the tourbook published by the American Automobile Association (AAA), the driving time between Battle Creek and Cleveland is assumed to be approximately 6 hours. It-implies that, in order to be at Cleveland 108 sometime around 12 o'clock, the businessman at Battle Creek has to leave his home by 6 o'clock in the morning. It is an unrealistic assumption that this "typical" businessman will be willing to leave home this early. The above assumption for the Battle Creek business­ man, however, is assumed to be unworkable for the business­ man at Cleveland who wants to travel to Battle Creek. The trip schedule for the Cleveland businessman to Battle Creek would be as follows: Leave home by car 7:40* 0.5 hours 8:10 = 2.5 11 0.3 11 1.5 II 0.5 11 4 .0 If 1.5 It 0.8 11 2.5 If 0.5 II 10:40: 11:00: Take the rent-a-car to Battle Creek Arrive at Battle Creek 12:30= Business deal or meeting starts 1:00* Business deal or meeting adjourns 5:00 = 6:30: Arrive at Lansing 7:20 = 10:10: 10:40- Take the first train from Pittsburgh at Cleveland terminal Get off the train at Lansing terminal Take the train from Chicago at Lansing terminal Get off the train at Cleveland terminal Back home The total travel time necessary for the Cleveland businessman's trip to Battle Creek is only one hour longer than that of the Battle Creek's businessman to Cleveland; however, the necessary time for driving a car for the Cleveland businessman, which is four hours, is 1.4 hours 109 (54 percent) longer than that of the Battle Creek businessman. The writer simply negates this sort of assumption. The predictable, and also unpredictable, time-loss in the above travel schedule for the Cleveland businessman should be assumed to reduce the travel opportunity to Battle Creek or the businessman concerned should be assumed to take his own car or airplane to get to Battle Creek. 3. A HSIPT system will not be utilized if the necessary travel distance to the destination is less than 100 miles. Even in Japan, only 30 percent of the Shin Kansen users are utilizing the system for such a short distance. It will be quite reasonable to make an assumption such as this in such a nation as the United States where the highway network systems are extensively developed; 4. A HSIPT system will not be utilized if the necessary travel distance to the destination is more than 60 0 miles or so. This sort of long distance should be, and most likely would be, covered by the air mode in terms of today's governing factors. On these bases, the necessary time-distance matrices between 40 origins and 20 destinations were produced (Appendices Ila and lib). 110 Changes of the "Population Potential11 of the 4 0 Local Communities Within the Region Before and After the Creation of a HSIPT System Two "Population Potentials" were calculated for each of the 4 0 local communities within the Region. One is based on the time-distance by automobile (before) and the other is based on the time-distance by a HSIPT system (after) . The formula used for this part of the research is similar to the one used by Ogawa, except the use of parameter b. That is: m Xj P. = I -----j=l -1 where = population potential at i Xj = population at j Dii= t^ie shortest distance or time between i and j b = an exponent describing the effect of the distance or travel time between i and j (distance decay parameter) l "■ 1/ 2 / >■«■•! n j = 1 , 2 , .... . m Although the shortcoming of this formula is undeniable, it is still worthwhile to examine the popula­ tion potential of the local communities by this formula. By calculating the population potential using the above formula, the level of influence given by other communities due to the reduction of the time-distance by the creation of a HSIPT system within the Region will be examined. The results of the calculation are shown in Appendices III and IV. As shown in Appendix III, the Ill correlation between the "population potential" and the population of each community is very low. The highest correlation coefficient obtained is only 0.413, at b = 1.0. The second highest correlation coefficient is 0.35 8, at b = 0.5. The third highest and the smallest are 0.333, at b = 1.5 and 0.134, at b = 2.0, respectively. From these values, it becomes clear that, although the correla­ tion is not so high, the "population potential" of each local community is less restricted by time-distance. The reason for this interpretation comes from the nature of the distance disutility parameter, or distance decay parameter, (b). The values of (b) have to be interpreted as "the smaller the value of (b), the distance or time is less restrictive." For instance, if the value of the exponent b for school trips is 2.0 and for shopping trips, 1.0, this should be interpreted as "people are willing to travel farther for shopping than they are for school." The adoption of the exponent b i s , as such, important to reflect a behavioral aspect in the formulations. The most highly correlated "population potentials" are grouped in Table 8, based on their strength. Table 9 shows the "population potentials" based on the timedistance by a HSIPT system at b = 1.0. The rate of changes of the "population potentials" for 40 communities are summarized in Table 10. TABLE 8.— Population Potential at Each SMSA Based on the TimeDistance by Automobile at b = 1-0. Unit: Person/Hour SMSA Population Potential Peoria Louisville Lexington Davenport 4,999.4 4,980.6 4,978,4 4,671.1 SMSA Population Potential Canton Battle Creek Southbend Sarnia Port Huron Toronto Kalamazoo Youngstown Columbus Cincinnati Dayton Indianapolis Lima Grand Rapids Fort Wayne Saginaw Rockford Hamilton London Erie Madison Niagara Falls Buffalo 9,193.2 9,126.2 9,060.2 9,008.2 8,953.1 8,932.1 8,836.0 8,829.9 8,705.0 8,605.3 8,506.6 8,300.6 8,232.4 8,023.0 7,914.2 7,622.9 7,362.8 7,181.3 6,772.2 5,897.6 5,720.2 5,577.5 5,243.4 5,054.2 Note: (1 Bd.) SMSA Population Potential Gary Ann Arbor Toledo Cleveland Flint Akron Pittaburgh Jackson Milwaukee Lansing 12,579.0 12,456.7 11,490.1 11,062.9 10,173.7 10,083.0 9,616.3 9,538.0 9,448.7 9,362.2 SMSA Population Potential Uindsar Chicago Detroit 28,462.5 18,641.2 16,165.1 Kean * 9,257.8 Standard Deviation (sd.) - 9,257.8 (1 ed.) 13.461.4 The "population potentials" listed above ere calculated aa follows: where Pt « X) ** DjLj ** i M j » population potential at 1 population at j the shortest time-distance between 1 and j (see Appendix Ila) 1, 2, ...... 40 . . . i 1, ...... , 2 0 (the number of communities where the terminal Is planned; TABLE 9.— Population Potential at Each SMSA Based on the TimeDistance by the HSIPT System at b = 1.0. Unit: Person/Hour SMSA Population Potential Lexington Erie Madison Niagara Falla Louisville Buffalo Peoria Davenport 6,656.9 6,647.2 6,368.0 5,771.5 5,672.2 5,265.2 5,049.2 4,647.7 SMSA Population Potential Milwaukee Port Huron Sarnia Toronto Youngstown Saginaw Canton London Southbend Lima Fort Wayne Rockford Hamilton 11,484.2 11,293.2 11,287.3 10,810.1 10,571.4 10,410.4 10,386.8 10,172.5 9,653.0 9.043.5 8.194.5 7.794.5 7,534.7 6,536.2 (1 sd.) SMSA Population Potential Toledo Cary Ann Arbor Cleveland Flint Grand Rapids Kalamazoo Akron Columbua Lansing Cincinnati Indianapolis Dayton Jackson Pittsburgh Battle Creek 15,477.3 15,212.2 15,146.0 15,112.9 14.355.3 13,861.9 13,729.2 13.226.9 13.163.7 13,149.4 12.831.1 12.505.9 12.045.1 12.035.2 11.90B.9 11,606.6 11,569.2 (1 sd.) SMSA Population Potential Windsor Chicago Detroit 31,577.5 20,938.8 20,570.8 16,602.2 Mean “ 11,569. 2 Standard Deviation (sd.) - 5,033.0 Mote: See note In Table 8. Appendix lib should be referred for the values of D ^ . TABLE 10.— Rates of Change of the Population Potential after the Creation of the HSIPT System. SMSA Rate SMSA Rate SMSA Rate SMSA Southbend Rockford Hamilton Fort Wayne Niagara Falls Peoria Buffalo Davenport 1.065 1.059 1.049 1.035 1.035 1.010 1.004 0.995 Pittsburgh Ann Arbor Milwaukee Toronto Oary Youngstown Louisville Canton Chicago Madison Windsor Lima Erie 1.238 1.216 1.215 1.210 1.209 1.197 1.139 1.130 1.123 1.113 1.109 1.099 1.093 Dayton Flint Saginaw Cleveland Toledo Akron Lexington Detroit Battle Creek Jackson Port Huron Sarnia 1.416 1.411 1.367 1.366 1.347 1.312 1.297 1.273 1.272 1.262 1.261 1.253 Grand Rapids Kalamazoo Columbus Indianapolis London Cincinnati Lansing 1.070 (1 sd.) 1.248 (1 sd.) ‘Rate 1.426 Mean - 1.248 Standard Deviation (sd.) “ 0.178 Mote: The rates of change listed above are calculated as follows: Rate of Change ** by automobile In Table 8/ Pj by the HSIPT system In Table <7. 1.728 1.554 1.512 1.507 1.502 1.491 1.441 115 The data shown in Tables 8, 9, and 10 should be interpreted as follows: 1. Among three communities/ Windsor, Chicago, and Detroit, which are in the highest bracket in terms of "population potential" for both before and after the creation of a HSIPT system, Detroit is likely to receive the strongest effect wfrom the reduction of the timedistance by the system. In fact, the impact on Windsor and Chicago is quite small; 2. Among the other 37 local communities, Grand Rapids, Kalamazoo, Columbus, Indianapolis, London, Cincinnati, and Lansing will be influenced by the new system most strongly. Eleven other communities, such as Dayton, Flint, Saginaw, Cleveland, Toledo, Akron, Lexington, Battle Creek, Jackson, Port Huron, and Sarnia, will be influenced by the system more than average. Among the communities where direct service by a HSIPT system terminal is not planned, Saginaw will be most influenced by the system. Davenport's population potential, on the other hand, grew less after the creation of the new system. The nature of the influence of a HSIPT system is unpredictable. If the application of the analogy from the Japanese experience is allowed, those communities such as Grand Rapids, Kalamazoo, Columbus, Indianapolis, London, Cincinnati, and Lansing might enjoy a large number of 116 "on" and "off" passengers at their terminals. This, however, does not imply the same positive impacts to those communities concerned as seen in some of the Japanese communities along the Shin Kansen routes. Suffice it to say that careful planning and study can alleviate negative influences from such unpredictableness. The necessary actions for this will be discussed in the following chapters. As a next step, to alleviate the shortcomings of the "population potential" concept, the "population energy" concept, which at least can take into account its own "population potential," was calculated. The results of the calculation are listed in Appendices V and VI. As shown in Appendix V, the correlation between "population energy" and the population of each community is fairly high, except in the case of b = 2.0 (0.503). correlation coefficient was 0.989, at b = 0.5. The highest Tables 11, 12, and 13 are the summarization of "population energy" for both before and after the creation of a HSIPT system in the Region. The data shown in those tables should be interpreted as follows: 1. As shown, large cities such as Chicago and Detroit have an extremely high "population energy," a reasonable finding. Cleveland, Pittsburgh, and Toronto, all of these three SMSAs having a population of more than 2 million, also compose the highest TABLE 11.— Population Energy (Energy of Interchange) at each SMSA Based on the Time-Distance by Automobile at b = 0.5. Unit: Square-Person/Hour SMSA Energy of Interchange Energy of Interchange SMSA - 2,472,817.1 (1 ad.) Energy of Interchange Milwaukee Cincinnati Buffalo Indianapolis Columbus Toledo Dayton 17,755,178.4 17,073,309.3 16,059,157.2 14,211,255.3 13,533,359.0 12,290,285.1 11,310,543.2 11,060,903.9 SMSA Energy of Interchange Chicago Detroit Cleveland Pittsburgh Toronto 67,637,409.9 54,695,874.6 27,086,132.1 26,319,022.7 25,569,468.8 Note: Population Energies listed above are calculated as follows: *■ si El “ 1 X jX j ' J-l where Ei }q Xj Dji b 1 j (1 sd.) 'b Dij population energy at 1 population at 1 population at J the shortest tlma--distance between 1 and j (see Appendix Ha) - 0.5 - 1, 2 ....... ,40 “ 1, 2, 20 24,594,784.9 Mean - 12,060,983.9 Standard Deviation (sd.) -13,363,557.7 117 Gary 10,398,080.5 Louisville 10,168,026.8 9,922,067.2 Akron Flint 7,770,950.2 Youngstown 7,465,661.7 7,408,404.8 Grand Rapids Hamilton 6,583,315.8 Lansing 6,378,655.4 Canton 5,928,170.5 Windsor 5,566,960.3 Fort Wayne 5,426,755.1 Southbend 4,369,727.3 4,100,881.0 Ann Arbor Davenport 4,098,968.0 4,082,186.1 Jackson Peoria 3,993,794.9 Kalamazoo 3,8B7,776.4 Rockford 3,712,824.6 3,697,853.7 London Niagara Falls 3,669,816.9 3,537,954.9 Madison Erie 3,334,222.3 Lima 3,184,058.9 Saginaw 3,125,985.2 Lexington 3,105,752.3 Battle Creek 2,239,899.9 Sarnia 1,201,016.3 Port Huron 544,583.5 SMSA TABLE 12.- -Population Energy (Energy of Interchange) at each SMSA Based on the Time-Distance by the HSIPT System at b = 0.5. Unit: Square-Person/Hour SHSA Energy of Interchange SMSA Energy of Interchange Gary Akron Louisville Grand Rapids Flint Youngstown Lansing Hamilton Canton Windsor Fort Wayne Kalamazoo Jackson Ann Arbor Southbend London Davenport Feoria Rockford Saginaw Niagara Falls Madison Lexington Erie Lima Battle Creek Sarnia Port Huron 11,878,748.0 11,640,044.9 10,835,329.6 10,123,928.3 '9,733,580.5 8,333,870.1 7,877,121.3 6,757,707.6 6,355,912.2 6,336,323.4 5,529,07B.0 4,879,902.0 4,706,099.8 4,700,002.3 4,524,736.8 4,518,069.0 4,090,235.8 4,011,809.0 3,842,294.2 3,761,444.0 3,733,657.5 3,708,646.9 3,546,304.3 3,486,381.7 3,335,655.7 2,524,004.6 1,385,521.0 630,522.0 - 3,864,743.8 U sd.) SMSA Energy of Interchange Toronto Cincinnati Milwaukee Indianapolis Columbus Buffalo Toledo Dayton 30,313,974.7 22,534,584.6 20,657,337.3 18,127,095.9 17,687,545.2 16,092,5D8.1 14.79B.779.5 14,249,929.6 13,304,144.6 (1 sd.) SMSA Energy of Interchange Chicago Detroit Cleveland Pittsburgh 82,B82,288.5 72,499,582.7 34.318.007.0 31.212.224.0 30,473,033.0 Mean Standard Deviation (sd.) Note: See note in Table 11. Appendix lib Bhould be referred for the values of D^j. 13,304,144.6 17,168,888.4 TABLE 13.— Rate of Increase of Population Energy (Energy of Interchange) after the Creation of the HSIPT System. SMSA Rate SMSA Rate SMSA Rate Madison Lima Erie Southbend Rockford Hamilton Fort Wayne Niagara Falla Peoria Buffalo Davenport 1.048 1.048 1.046 1.035 1.035 1.026 1.019 1.017 1.005 1.002 0.998 Ann Arbor Gary Lexington Windsor Battle Creek Youngstown Canton Louisville 1.146 1.142 1.142 1.138 1.130 1.116 1.072 1.066 Flint Lansing Chicago London Toledo Saginaw Pittsburgh Toronto Akron Milwaukee Port Huron Sarnia Jackson 1.253 1.235 1.225 1.222 1.204 1.203 1.186 1.185 1.173 1.163 1.158 1.154 1.153 1.051 (1 ad.) 1.153 (1 ad.) SHSA Rate Grand Rapids Detroit Cincinnati Columbus Indianapolis Cleveland Dayton 1 Kalamazoo 1.364 1.326 1.320 1.307 1.276 1.267 1.260 1.255 1.255 Mean 1.153 Standard Deviation (sd,)- 0.102 Note: The rates of change listed above are calculated as follows: Hate of change - El by automobile in Table LI/ El by the HSIPT system In Table 12. 12 0 bracket. Among these large SMSAs, however, Detroit is likely to have the strongest impact from a HSIPT system and Cleveland follows Detroit in impact reception; 2. Among the middle sized SMSAs, such as Cincinnati, Milwaukee, Indianapolis, Columbus, Buffalo, Toledo and Dayton (all of these having the population size of 800,000 to 1.5 million), Cincinnati is likely to have the strongest impact from the system. Columbus, Indianapolis, and Dayton, then, follow Cincinnati. Buffalo, on the other hand, will be excluded from the effects of the system completely; 3. Among the SMSAs in the third bracket, Grand Rapids is likely to receive the strongest impacts from the system. Kalamazoo, Flint, Lansing, London, and Akron will follow Grand Rapids. Among the SMSAs where a HSIPT system terminal is not planned, Saginaw is likely to have the strongest impacts from the system. Port Huron, Sarnia, and Jackson will follow Saginaw. From the two studies described above, it can be concluded that the new system will influence most signif­ icantly Grand Rapids, Michigan; Columbus, Ohio; Cincinnati, Ohio; Kalamazoo, Michigan; and Indianapolis, Indiana. Then, Detroit, Michigan; Cleveland, Ohio; Lansing, Michigan; and London, Ontario, Canada will follow the above five SMSAs. The other nine communities, such as Flint, 121 Michigan; Toledo, Ohio; Saginaw, Michigan; Battle Creek, Michigan; Jackson, Michigan; Port Huron, Michigan; Sarnia, Ontario, Canada; and Lexington, Kentucky, are also likely to have strong impacts from the new system. As indicated, the communities in Michigan are likely to experience the most significant impacts from the creation of a HSIPT system within the Region. The result, however, would have been different if a different network were planned. Canton, Ohio, for instance, which has a strong locational advantage to such large SMSAs as Cleveland and Pittsburgh, is left out from the influence of the new system. South Bend and Fort Wayne, both in Indiana, are also left out from the influence of the new system completely. It will be reasonable to assume that the influence of a HSIPT system will be considerably different if a new network is planned to join them. It is natural to estimate that the introduction of a sharp reduction of the time-distance between SMSAs due to the creation of a HSIPT system will result in significant impacts on those SMSAs. The problem will be how to deal with the strong impacts introduced by the new system. Careful analyses of the impacts and development of a comprehensive plan to alleviate the possible negative impacts will be essential. In the next chapter, the probable impacts on local communities due to the creation of the HSIPT system in the Region will be specifically 122 investigated. In fact, as experienced in Japan, the impacts from such a new transportation system are enormous. The impacts on land uses and covers, economic and social structures, other modes of transportation such as the highway and air, and environmental conditions have to be projected. Most importantly, the involvement of political considerations concerning the selection of the site for a HSIPT system terminal have to be carefully watched. CHAPTER IV PROBABLE IMPACTS ON A LOCAL COMMUNITY DUE TO THE CREATION OF A HIGH-SPEED INTERCITY PASSENGER TRAIN SYSTEM WITHIN THE GREAT LAKES MIDWEST REGION (CASE STUDY: THE LANSING METROPOLITAN AREA IN MICHIGAN) Probable Impacts on Rural-Urban Structures (Impacts on Land Uses and Land Covers and Population Settlement Patterns) Transportation and land use have a symbiotic relationship with each other. This strong relationship should be seen from two different aspects: 1) transporta­ tion as a consumer of scarce urban land and 2) trans­ portation as a provider of access to non-transportation land-consuming activities. 62 In fact, the necessary space for highway systems and airports often requires enormous amounts of land in the middle of or in the vicinity of urban areas, and they have become serious threats to preservation efforts for productive agricultural lands, forest lands, and flood plains in local communities. A HSIPT system, on the other hand, requires much less space compared to the above two transportation modes. 62 D. B. Lee, Jr. and C. P. Averous developed this distinction in their paper titled "Land Use and Transporta tion: Basic Theory," Environment and Planning, Vol. 5, 1973, pp. 491-502. 123 124 In fact, the necessary width of a two-track HSIPT system would be as wide as 10 to 11 m compared to that for fourg2 lane highway system which can be more than 25 m. Even the necessary space for a HSIPT system terminal is small. For instance, the ordinary HSIPT system terminal in Japan has two or three platforms of 500 m or so; accordingly, it is reasonable to assume that all of the necessary facilities related to a HSIPT system terminal could be accommodated in the area of one square mile. This, however, does not mean to negate the necessity of cautious planning for the location of a HSIPT s y s t e m ^ right-of-way and terminal. As a matter of fact, negative ramifications from careless planning could be tremendous. Such negative effects from a HSIPT system as noise and vibration will degrade the quality of land along the route and will result in a sharp decline of the value of land. A carelessly planned HSIPT system terminal could result in the waste of valuable land, as occasionally seen in Japan. In fact, the lack of follow-up development in and around carelessly planned sites has often been seen in Japan. To minimize the negative effects on land uses and land covers in the local areas, the following considerations are prerequisites: 63 The figures are based on the Japanese Standards. 125 1. A HSXPT system right-of-way should not be placed on productive agricultural lands, on forest lands, or within flood plains; 2. A HSIPT system right-of-way should be located so as to be away from densely populated areas; 3. A HSIPT system terminal should be located so as to be functionally linked with the existing commercial center of the area concerned, such as the central business district or commercial core. This linkage is necessary to avoid drastic land use changes in the local areas and to avoid inefficient and non-effective dual investments in small local areas; 4. A HSIPT system terminal should be located so as to synchronize effectively with existing transportation systems such as highways, buses, mass transits, and air terminals. This is necessary to avoid unnecessary investments of valuable urban land to provide the necessary transportation system with a planned or developed HSIPT system terminal. By taking into account the above four prerequisites, the HSIPT system planners can alleviate negative impacts due to the creation of a HSIPT system on land uses and land covers. For instance, if one observes the maps of five different land uses and covers in the Lansing Metro­ politan Area which are shown in Figures 17, 18, 19, 20, and 21, it will be relatively easy to reach the optimal 12 6 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Lebanon Essex Creenbush Duplaln Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld Roxand Oneida Delta Vermontville Chester Benton Windsor 25 26 27 28 29 30 31 32 33 34 35 36 37 38 . 39 40 41 42 43 44 45 46 78 47 48 Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Wllliamston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Stockbrldge 3 jl £ fwrrcrasn 1-96 g US-127 US-27 Lansing Metropolitan Area Clinton County ( 1-16) — Eaton County (17-32) Ingham County (33-48) Figure 17.— Location of Nine Major Urban Centers in the Lansing Metropolitan Area. 127 B 9 10 11 12 13 14 15 17 IS 19 20 21 22 23 Lebanon Essex Greenbush Duplaln Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld Roxand Oneida Delta Vermontville Chester Benton Windsor Lansing Metropolitan Area 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheatfie Id Leroy Aurelius Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Stockbrldge Clinton County ( 1-16) — Eaton County (17-32) Ingham County (33-48) Figure 18.— Location of Major Agricultural Lands in the Lansing Metropolitan Area. SOURCE: Tri-County Regional Planning Commission. Michigan Tri-County Region Environmental Framework Study. Date Unknown, p. 33. 128 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 23 24 Lebanon Essex Greenbush Duplaln Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld Roxand Oneida Delta Vermontville Chester Benton Windsor Lansing Metropolitan Area 25 26 27 28 29 30 31 32 33 34 35 37 38 39 40 42 43 45 46 47 48 Clinton County — Eaton County Ingham County Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheacfield Leroy Aurelius Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Stockbrldge ( 1-16) (17-32) (33-48) Figure 19.— Location of Major Woodlands in the Lansing Metropolitan Area. SOURCE: Tri-County Regional Planning Commission. Michigan Tri-County Region Open Spaces of the Region: Principles of Open Space Planning, Dec. 1969, p. 24. 129 8 9 10 12 13 14 16 17 18 19 20 21 22 23 24 Lebanon Essex Greenbush Duplaln Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld Roxand Oneida Delta Vermontville Chester Benton Windsor 25 26 27 28 29 30 31 33 34 35 38 39 40 42 43 44 45 46 47 48 Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Stockbridge k Lansing Metropolitan Area Clinton County ( 1-16) — Eaton County (17-32) Ingham County (33-48) Figure 20.— Location of Major Flood Plains in the Lansing Metropolitan Area. SOURCE: Tri-County Regional Planning Commission. Michigan Tri-Countv Region Environmental Framework Study. Date Unknown, p. 27. 130 1 Lebanon 2 Essex 3 Greenbush A Duplaln 5 Dallas 6 Bengal 7 Bingham 6 Ovid 9 Westphalia 10 Rile/ 11 Olive 12 Victor 13 Eagle 11 Watertown 15 Dewitt 16 Bath 17 Sunfleld 18 Roxand 19 Oneida 20 Delta 21 Vermontville 22 Chester 23 Benton 24 Windsor 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 I Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williams tan Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Stockbrldge i f i I Lansing Metropolitan Area E Clinton County ( 1-16) — Eaton County (17-32) Ingham County (33-48) Figure 21.— Location of Major Groundwater either Sensitive or Developable in the Lansing Metropolitan Area. SOURCE: Tri-County Regional Planning Commission. Michigan Tri-Countv Region Environmental Framework Study. Date Unknown, p. 23. 131 (or quasi-optimal) terminals. locations of a HSIPT system route and The area suitable for such a terminal should be designated in one of seven township areas: Watertown, Dewitt, Bath, Delta, Windsor, Delhi, and Alaiedon. Lansing and Meridian Townships have to be excluded from the site proposed for a HSIPT system terminal because these two townships are substantially developed and populated. By the same token, a HSIPT system route should be planned to run through two possible corridors; one is within such townships as Eagle, Watertown, Dewitt, and Bath, and the other is within Oneida, Windsor, Delhi, Alaiedon, Wheatfield, and Locke (Figure 22). As far as a HSIPT system is concerned, however, the most important role is that of a provider of access to non-transportation, land-consuming activities. In fact, a HSIPT system not only opens the specific local areas to the rest of the region or the nation, but also gives a significantly improved accessibility to certain portions of the local areas concerned. Improved accessibility will eventually give rise to rural-urban economic, social, and physical structural changes in the areas concerned. If some portion of a local area receives a significant locational advantage from the creation of a HSIPT system terminal, the developmental potential of that portion concerned will increase considerably, especially the developmental potential of residential types of use 132 1 2 2 4 5 6 7 8 9 10 11 12 13 14 15 18 17 Lebanon Essex' Greenbush Duplaln Pallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 US-27 o ires 18 Roxand 19 O n e id a 20 Delta 21 Vermontville 22 Chester 23 Benton 24 Windsor Grand f Rapids Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Willianston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham Uhlteoak Onondaga Leslie Bunkerhlll Stockbrldge infa■ 11 Flint O LC US-127 P US-27 Possible HSIPT System Terminal Lansing Metropolitan Area ••••••••••; Possible HSIPT System Route Clinton County ( 1-16) — Eaton County (17— 32) Ingham County (33-48) Figure 22.— Possible Locations of the Lansing HSIPT Terminal and HSIPT System Route. 133 activity. As a matter of fact, accessibility and residen­ tial land use have had a strong interrelationship. For instance, Hansen says that "an empirical examination of the residential development pattern illustrates that acces­ sibility and the availability of vacant developable land can be used as the basis of a residential land use model." In the text that follows, the concept of accessibility, which is necessary for an understanding of the role of transportation as a provider of access to non-transportation, land-consuming activities, will be examined and applied to analyze the probable impacts of a HSIPT system on land uses and covers in the Lansing Metropolitan Area. Concept of Accessibility to Analyze the Relationship between Transportation and Land Use The concept of accessibility has been used frequently in both transportation and planning studies. This concept, however, is not easy to define in clear and quantifiable terms. On the one hand, accessibility could be conceptualized as a measure of spatial opportunities which are inherent at any location. On the other hand, accessibility has been primarily synonymous with the minimization of the costs of friction as perceived in the 64 Walter G. Hansen, "How Accessibility Shapes Land Use," Journal of American Institute of Planners, Vol. 25, 1959, pp. 72-76. literature of economics. This concept of accessibility has been developed in the discipline of location theory for both industrial locations (Weber, 1929; Losch, 1954; and Isard, 1956) and residential locations Alonso, 1964). (Wingo, 1961; Isard has noted, in conventional economic theory, that "transport costs and other costs involved in movement within a 'market' are assumed to be zero. In this sense the factor of space is repudiated, everything within the economy is in effect compressed to a point, and 65 all spatial resistance disappears." In these two fields, the fields of residential location theory and industrial location theory, analysis has concentrated on the trade-off between transport costs and rents. Further, in these analyses, accessibility has been considered in unidimen­ sional terms as minimizing distance from a city center; in other words, the Central Business District (CBD). Recently, however, people have been more interested in such matters as low tax rates, the high quality of schools, availability of recreational spaces and facilities, crimeless or free environments, and high environmental quality. This sort of human behavior cannot be analyzed in the traditional model of residential location theory in which the distance from the CBD was assumed to be the single key element to figure out accessibility. According to this 65 Walter Isard, Location and Space Economy, Cambridge: The MIT Press, 195 6, p. 26. 135 assumption, the CBD and its vicinity where job opportunity is assumed have always had highest accessibility, and the distance from the CBD is always assumed to be a disutility. In reality, however, many affluent people choose to live in areas of low accessibility and other people, whose ability to receive the opportunities inherent in their spatial location may be very low, live in areas of rel­ atively high accessibility. Alonso, as previously noted, introduced the size of the site element into the location decision by people and stressed that the trade-off relationship between accessibility and space is the main concern for people who want to make a choice among alternative locations. This concept of the availability of developable, vacant land is certainly the key element to understanding the location decisions of people and entrepreneurs. Without taking into account this element, such a series of phenomena as suburbanization, exurbaniza­ tion, and gentrification movements, which have been noticeable in many of the urban areas in the United States, cannot be understood. The above-mentioned traditional trade-off theory has been in the main stream of residential location theory; however, its underlying assumptions, such as a single employment center in the CBD, no locational externalities, transport cost savings as the sole determinant of location rent, the negligibleness of density function, environmental 136 quality, etc. , make the trade-off model a very special case which is of little help to understanding the residen­ tial location behavior of people in a modern city. Although the traditional trade-off models have been remarkably resilient, a number of the alternatives have been proposed to alleviate its unidimensional concept. 6G Many of those alternatives have emphasized the importance of environmental externalities in the residential location choice (Ellis, 1967; Yamada, 1972; Richardson, 1977); others have emphasized that accessibility could no longer be figured out by minimizing distance from the CBD (Stegman, 197 4; Senior and Wilson, 197 4; Beckman, 1973; Richardson, 1977). The complexity of those alternatives, however, have not succeeded in replacing the traditional trade-off models, which in some sense has a remarkable simplicity. R. Vickerman tried to clarify various concepts of accessibility. He examined a geographical concept of accessibility which, according to him, involves a combination of two elements: location on a surface relative to suitable destinations and the characteristics of the transport network or networks linking points on W. Richardson concisely summarizes the state of affairs of the alternatives to the traditional standard trade-off models. See, H. W. Richardson, "A Generalization of Residential Location Theory," Regional Science and Urban Economics, 7, 1977, pp. 251-266. 137 that surface. 67 The former element was originated by Christaller's central place theory (Christaller, 1966) and the latter have been developed by Shimbel Kansky (1963), Haggett and Chorey (1953), (1969), and Hay (1973). He also examined the economic concept of accessibility originated by Weber Wingo (1929) , Losch (1961) , and Alonso (1959), Isard (1959) , (1964) and further, the concept of accessibility based on attraction and potential which was primarily discussed and introduced by Harris Hansen (1959), and later by Wilson (1971). (1954), Among these, according to Vickerman, the attraction-accessibility concept associated with the spatial interaction model is the most satisfactory, although there exists a high degree of intercorrelation among the variables usually selected to identify the effects of attraction and accessibility. This measure is also superior to a similar measure, the Shimbel Index, which does not accommodate "a behavioral aspect into the formulations which is plausible on a priori grounds— that the perception of accessibility declines 68 increasingly rapidly as distance increases." Turning to the issue of intercorrelation which was pointed out by Vickerman, factor analysis has been shown 67 R. W. Vickerman, "Accessibility, Attraction, and Potential: A Review of some Concepts and their Use in Determining Mobility," Environment and Planning A , Vol. 6, 1974, pp. 675-691. 68Ibid., p. 677. 138 to be a useful tool to alleviate the problem of collinearity; however, its application as an analytical tool is limited because of the sensitivity of the solution to variations both in the number of observations and in the 69 number of original variables. Also, the selection of those variables and the interpretation of the results of factor analysis are absolutely dependent on the modeller's judgment. Concerning this point, Isard, for instance, says that "the analyst must bear in mind the extent to which factor analysis cannot eliminate his responsibility for sound reasoning and judgment, and in many cases cannot eliminate the need to resort to arbitrary procedures. Briefly put, factor analysis is not nearly as objective as appears to the unsophisticated analyst." 70 Although Vickerman regards the attractionaccessibility index as most satisfactory in many cases. 69 Factor analysis has a long history in psychology, and to a lesser extent in sociology and political science. Recently, this method has frequently been used among social scientists. The single most distinctive characteristic of this method is its data-reduction capacity; namely, it offers a fruitful approach to condensing voluminous sets of data into relatively few useful indices or dimensions. It is often used as an effective tool to delineate regions within a system which have firm theoretical foundations. As many statistical tools, it can serve as a partial test of an hypothesis or reflect the adequacy of the charac­ teristics initially selected as relevant, etc. (Isard, 1960). 70 Walter Isard, Method of Regional Analysis: An Introduction to Regional Science, Cambridge: The MIT Press, 1960, p. 305. 139 independent attraction-accessibility indices may be calculated by the Hansen method. Hansen calculated the attraction-accessibility indices for three different attractions, i.e., employment, shopping opportunities, and residential activity (Hansen, 1959). In most cir­ cumstances, however, it would be more satisfactory if the combined attraction-accessibility indices are produced in connection with spatial interaction models. Taking into account these points, this research dealt with two different attraction-accessibility indices. The first to be examined were the accessibilities of each node (the Lansing Metropolitan Area is divided into 192 nodes and the detail is discussed in the following section of this chapter) to decentralized shopping opportunities (to five major retail centers in the Lansing Metropolitan Area) and employment opportunities (six major employment centers). The second to be examined were the accessibilities of the above 192 nodes to more generalized urban functions which are assumed to be represented by the population in cities of known size. The underlying reason for the selection of the population in cities of known size is that the population of such cities can be assumed to reflect the urban functions which each of those cities possesses. The urban functions here are job and shopping opportunities, amenities such as cultural and academic events, cultural and amusement opportunities such as theaters, movies, 140 museums, restaurants, sports, and recreational opportunities and facilities. It is true that people are concerned with the environmental quality around them; however, they also need to have such urban functions as described above and various maintenance services such as gas, electricity, sewage treatment, garbage collection, fire and police protection, and good school systems, which require some amount of supportable population. Attraction-Accessibility Indices to Analyze the Population Settlement Patterns in the Lansing Metropolitan Area In the middle of the year 1981, the (Lansing) Tri-County Regional Planning Commission released a summary of its investigation concerning the population trend within the Lansing Metropolitan Area, based on the 19 80 United States Census of Population. 71 According to the summary, the suburban areas within the Lansing Metropolitan Area have grown much faster than such cities as Lansing, East Lansing, St. Johns, Charlotte, Eaton Rapids, Potterville, and Mason and also such villages as Dimondale and Dansville. In the summary, forty-eight townships in the Lansing Metropolitan Area were divided into three groups according to the level of population growth during the past ten years (Figure 23). 71 As shown in Figure 23, only two Jane Garrick, "Lansing a Loser in 198 0 Census," The Lansing State Journal, April 19, 1981. 141 1 Lebanon 2 Essex 3 Greenbush 4 Duplain 5 Dallas 6 Bengal 7 Bingham 8 Ovid 9 Westphalia 10 Riley 11 Olive 12 Victor 13 Eagle 14 Watertown 15 Dewitt 16 Bach 17 Sunfleld 18 Roxand 19 Oneida 20 Delta 21 Vermontville 22 Chester 23 Benton 24 Windsor Kalatno Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Willlamston Locke Delhi Alaiedon IK Wheat£ield Leroy Aurelius mmmm Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Scockbrldge LU« uzu a saai High growth □ Moderate growth Loss Lansing Metropolitan Area — Clinton County ( 1-16) Eaton County (17-32) Ingham County (33-48) Figure 2 3.— Population Growth During the 1970's in the Lansing Metropolitan Area. SOURCE: 198 0 U.S. Population Census. 142 townships experienced a population loss during the 1970*s. Those were Lebanon Township, which is located in the northwestern corner of Clinton County, and Lansing Township, wherein the City of Lansing occupies most of the land area. At the city level, Dewitt is the only exception; it experienced a population increase during the 1970's. Thirteen out of the 48 townships scored high growth and nine out of those thirteen townships accommodate one of those cities or villages mentioned above. On the county level, Eaton County had the biggest population gain of 28 percent, from 68,8 92 to 88,337. Clinton County also scored a strong gain, growing 15 percent, from 48,49 2 to 55,893 residents. Ingham County, on the other hand, registered only a 4 percent population increase, going from 2 61,039 to 272,437 residents. This strong growth of non-urban townships implies that the population has been dispersing evenly within the Lansing Metropolitan Area more than ever. Taking this trend of non-urban township growth into account, the township was designated as the demand node where people who want to utilize certain facilities or the opportunities such as employment or shopping live. Further, if this non-urban township growth continues, even the existing highway system (in terms of the availability of interchanges to these new residents) might have to be reconsidered. Fortunately, however, the street and road system within the Lansing Metropolitan Area is based on the rectangular survey system which is ordinarily seen in the Midwest region of the United States; that is, most of the area within the Lansing Metropolitan Area is subdivided into sections or subareas of one square mile (1 mile x 1 mile) by the basic section line roads which run in the directions of north to south and east to west (Figure 24). 72 This systematic street system will be utilized more and more by those residents who dispersed from the central urban areas to suburban areas. This part of the research, accordingly, will be based on these two facts: the population increase in non-urban townships and the existence of the rectangular street system within the Lansing Metropolitan Area. To figure out the attraction-accessibility indices, the Lansing Metropolitan Area was divided into 1 9 2 , 3 x 3 mile, subareas, rather than 4 8, 6 x 6 mile, subareas (the area of the township) or 1,728, l x l (the area of the section). mile, subareas The reason for the adoption of 192 subareas was to obviate the need for extensive and expensive calculation processes which were likely to result from the adoption of 1,728 subareas and to secure a 72 This rectangular survey system is applied . in the thirty public domain states and also in part of some other states. In the system, a county which has the area of 24 x 2 4 mile square is composed of 16 townships. A township ( 6 x 6 mile square) consists of 36 sections. A section ( l x l square mile) is equivalent to 64 0 acres and the section is usually divided into 4 quarter sections. 144 COUNTIES (14 I|1 MI CHI GAN WORLD TAN MS W ^ tltllii/ T 3N MS W T4N RIW [ 1 T4N RLE Ttvtkl* . TJN } R I W <| I 1*1 TJN MIC rjn MSE TIN MIC MSC TIN MIC r n R2C l'< Ull, tlttlll N h M I Jifijj 4 3 4 3 2 1 7 8 a 10 11 12 ia IT 14 13 14 13 it SO SI 22 2 3 24 2 4 j24 38 I3 4 30 s» 21 27 31 31 33 3* MERIDIA N TAN MS C J V TOWNSHIP ( 3 4 * 0 * * S « Mil* ii -i TIN M S w T i N Ml W -1 Z| t s n wi iJ «1 iJ T in MS w TIN MIW lAtC __________ w\ S M\ 1 LINI ONE SECTI ON (4 Oy*iT** I NGHAM COUNTY (14 T b w m Jh A C O U K T T A AN ( X 4 ■ 2 4 mill ■ 3CCTI0K ACftE m ) \* {I M - " 1 1 * 1 * « 4 Q ■ 4 9t3 6 0 lieiltM) 18 TOW NSHIP S ACftC* 4 TOWNSHI P K A 1/4 ■ • mill!) ■ 3 1 SECTI ONS S E C T I O N • 1/ 4 >4 . mi l * " 1 0 0 ACHES *4. T * « l Figure 24.— The Federal Land Survey System (The Rectangular System). SOURCE: Myles G. Boylan, Urban Design Papers. (Mimeo). East Lansing: MSU, p. UPD 5. 145 reliability and accuracy of analysis which could not have been assured by the adoption of 48 large subnodes. In fact, the aggregation or disaggregation of the area is very crucial for spatial analysis. Zone or area config­ uration is often the key to the success of urban and regional analyses; that is, an excessive aggregation results in a loss of detail and an excessive disaggregation results in prohibitive data collection and calculation costs. The adoption of 192 subnodes in this research, however, is not likely to degrade the reliability and accuracy of the analysis because the land uses and land covers in the Lansing Metropolitan Area are mostly homogenous; that is, most of the land uses and land covers are rural, residential, or agricultural land uses. The formula used to calculate the attractionaccessibility indices is shown below: m Ej A. = I ---1 j=l D. ^ 1U where A^ = accessibility at node i Ej = size of activity (attraction) at node j; i.e.., number of people, jobs, capacity of school, etc. D^j= distance disutility between node i and j k = an exponent describing the effect of the travel time or distance between node i and j (distance disutility parameter) m = number of destinations; i.e., number of facility locations, job locations, etc. 146 Accessibility to Shopping Opportunities In the Lansing Metropolitan Area there are five major retail centers. These are 1) Lansing CBD, 2) East Lansing CBD, 3) Frandor Shopping Center, 4) Lansing Shopping Mall, and 5) Meridian Shopping Mall. The total amount of retail sales in these five retail centers has reached approximately $300 million, which is approximately 15.5 percent of the total retail sales volume for the Lansing Metropolitan Area. The following figures are the amount of sales at each of five major retail centers as of 1977, investigated and released by the (Lansing) Tri-County Regional Planning Commission in 1981 (in 73 thousands). Lansing CBD - $ 44,957 East Lansing CBD - $ 25,119 Frandor - $148,892* Lansing Mall - $ 46,683 Meridian Mall - $ 29,038 * Including the amount of sales from STORY-OLDS which is the largest Oldsmobile Dealer in the United States. The locations of these five major retail centers are shown in Figure 25. 73 The accessibility of each of the The (Lansing) Tri-County Regional Planning Commission, Regional Fact Book for the Tri-County Region, Lansing: Tri-County Regional Planning Commission, June 1981, p. Economic Base 15. 147 imiles 1 2 5 6 9 10 13 14 3 4 7 a 11 12 15 16 17 18 21 22 25 26 29 30 19 20 23 24 27 28 31 33 34 37 38 35 36 39 40 49 50 53 54 51 52 55 66 42 ^Lansing Mall (45,000) ^Lansing CBD (25,200) // // ^Frandor (149,000) 36 30 x / , /•/ ! r\j 7 I/I/ i Ay 41 42 43 Meridian Mall (29,100) / 24 Ease Lansing CBD (46,700) 60 AlL 64 / f 137 138 141 142 139 140 143 144 150 153 154 157 158 151 152 155 156 159 160 162 165 166 169 170 173 174 163 164 167 168 171 172 175 176 126 177 178 181 182 185 186 189 190 128 179 180 183 184 187 188 191 192 65 66 69 70 73 74 77 67 68 71 72 75 76 79 80 131 132 135 81 82 85 86 89 90 93 94 145 146 149 83 84 87 88 91 92 95 96 147 148 97 98 101 102 105 106 109 110 161 99 100 103 104 107 108 111 112 113 114 117 118 121 122 125 115 116 119 120 123 124 127 13 18 12 12 13 Lansing Metropolitan Area 24 30 36 42 48 miles Clinton County { 1-64) — Eaton County ( 65-12 8) Ingham County (12 9-192) Figure 25.— Locations of Shopping Opportunities in the Lansing Metropolitan Area and the Levels of Attractive­ ness (the Amount of Retail Sales in Thousand Dollars). SOURCE: Tri-County Regional Planning Commission, Regional Fact Book for Lansing and Tri-County Region, 1981, p. Ec-15. 148 192 demand nodes to those five major retail centers was calculated and the results are shown in Appendix VII. The value of exponent, k, adopted for this calculation ranges from 0.5 to 3.0. The accessibility at each of the 192 demand nodes, then, was reaggregated into 48 township nodes to examine the statistical relationship between those accessibilities and the number of residents in each of 48 township nodes. The results are shown in Table 14. As shown in Table 14, the correlations between the two variables (township nodal accessibilities and the number of their residents) are mostly high. The correlation coefficients range from 0.809, at k - 0.5, to 0.962, at k = 2.0. These high correlation coefficients indicate that there are strong linear relationships between the above two variables. Statistically, a correlation coefficient equal to 0.962 means that about 92.5% (0.9622 = 0.9254) of the variability of the populations at 4 8 township nodes can be explained by a linear relation. In this part of the study, the highest correlation coefficient was obtained at the value of 2.0 for exponent k. In most of the cases, the exponent values decrease as trips become more important; namely, for school trips, 2.0; for shopping trips, 2.0; for social trips, 1.1; for work trips, 0.9; etc. ^Hansen 74 The accessibility is the inverse (1959) , p. 74. 149 TABLE 14.— Nodal Accessibility to Shopping Opportunities at Township Base and Statistical Relation­ ship between Accessibility and Population. Township Lebanon Essex Greenbush Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Deyitt Bach Suofield Roxand Oneida Delta Vermontville Chester Benton Windsor Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaledon Wheatfield Leroy Aurelius Vevay Ingham White Oak Onondaga Leslie Bunker Hill Scockbrldge k - 0.5 k - 1.0 k - 1.5 k - 2.0 k - 2.5 k - 3.0 Population Access­ ibility Access­ ibility Access­ ibility Access­ ibility Access­ ibility Access­ ibility 697 1,688 1,929 2,330 2,288 1,067 9,747 3,241 2,350 1,547 2,111 2,287 2,060 3,602 13,203 5,746 1,998 1,975 10,298 28,262 1,942 1,622 3,907 6,078 1,683 8,769 4,965 3,725 2,725 3,205 1,380 5,803 116,493 77,603 5,472 1,456 36,722 2,845 3,004 3,413 2,460 9,132 1,974 1,096 2,289 4,300 1,794 2,914 197,208.0 216,470.2 233,623.0 225,409.0 216,470.2 242,998.4 267,822.5 255,596.6 242,998.4 283,332.7 324,440.8 303,161.7 283,332.7 360,235.5 456,029.9 399,699.0 229,423.1 261,892.3 315,551.3 446,769.6 207,601.9 230,420.6 263,269.3 317,633.8 190,513.2 207,601.9 230,420.6 263,269.3 177,080.2 190,513.2 207,601.9 230,420.6 644,272.3 538,410.8 356,747.7 285,853.5 378,602.1 356,866.7 298,341.3 251,238.8 295,695.7 282,682.3 251,238.8 222,006.5 251,482.4 242,809.4 222,006.5 201,286.9 Slone Y- interception Corr. Coeff, (r) 5,575.8 160.1 33,096.4 943.0 39,947.6 1,383.8 259.1 7,413.7 46,459.0 9,275.6 373,9 1,859.1 1,608.4 43,234.6 311.9 8,323.5 1,383.8 39,947.6 7,413.7 259.6 50,510.2 10,596.1 479.8 2,243.8 61,228.3 14,091.5 3,264.1 760.8 55,725.7 12,224.5 599.2 2,698.3 50,510.2 10,596.1 479.8 2,243.8 1,133.4 4,375.6 69,247.5 17,238.7 90,531.2 25,681.4 2,135.5 7,348.5 5,546.2 78,881.9 20,783.8 1,499.1 1,133.4 4,375.6 69,247.5 17,238.7 6,312.0 116,501.2 40,456.0 15,276.8 186,635.7 80,966.6 37,164.8 17,958.3 8,547.4 141,307.9 52,451.2 20,560.0 1,751.7 349.5 44,891.2 8,839.1 712.8 3,064.2 58,770.5 13,339.2 2,158.1 7,137.9 86,590.5 24,460.7 196,421.2 106,200.9 71,591.1 57,367.5 1,155.4 206.2 6,496.8 36,660,5 1,774.8 8,935.4 354.7 45,248.8 724.0 3,108.4 13,504.6 59,320.9 2,187.9 7,240.5 66,311.2 24,792.7 132.7 814.2 5,005.1 30.B41.7 206.2 1,155.4 6,496.8 36,660.5 354.7 1,774.8 8,935.4 45,248.8 724.0 3,108.4 59,320.9 13,504.6 91.6 26,629.4 605.4 4,011.6 132.7 814.2 5,005.1 30,841.7 1.155.4 206.2 6,496.8 36,660.5 8,935.4 354.7 1,774.8 35,138.8 404,247.3 291,315.5 235,769,3 207,379.0 282,177.7 173,360.1 124,282.5 100,887.4 4,590,1 111,794.1 36,562.3 12,581.5 1,131.1 4,410.6 70,174.7 17,465.4 4,876.4 161,936.4 41,295.9 14,049.9 5,300.8 112,976.8 37,864.6 13,608.5 1,866.6 6,110.2 77,994.6 21,267.7 600.7 2,846.6 54,225.0 11,879.7 1,249.4 74,621.B 13,959.9 4,850.3 1,984.0 4,250.7 68,697.3 16,953.1 600.7 2,846.6 54,225.0 11.B79.7 302.0 1,551.2 8,046.0 42,095.0 537.9 2,488.3 53,770.5 11,549.9 470.1 2,214.9 50,347.6 10,518.9 302.0 1,551.2 42,095.0 8,046.0 179.6 1,030.6 5,948.1 34,513.6 0.5748979 0.5005031 0.3925248 0.2651835 0.1764784 -41157.3B -12106.17--2169.367 1835.4870 3313.6128 0.8089657 0.9183882 n OHfiOA? O.9620010 0.9596237 27.4 49.0 75.4 60.6 49.0 103.6 178.3 L33.9 103.6 299.9 ' 628.4 410.5 299.9 2,842.1 9,067.3 3,773.1 70.3 168.1 677.1 51,098.0 37.0 71.5 170.7 685.5 21.6 37.0 71.5 170.7 13.8 21.6 37.0 71.5 192,404.3 89,191.1 1,784.1 294.9 1,725.6 2,246.6 609.5 139.2 324.0 281.5 139.2 59.3 116.7 100.6 59.3 23.9 0.6201749 4027.0466 _ ap 1r 0.9539215 150 function of the distance between the nodes i and j . Accordingly/ the less the value of exponent/ k, the more the influence of the distance. That is, people are willing to travel farther to work than they are willing to travel for any other of the purposes described above. According to Hansen's study, those exponents figured out from the data in the Washington, D.C. metropolitan area were for work trips, 2.20; for social trips, 2.35; for shipping trips, 3.00. These values are peculiar to individual communities, but ordinarily range between 0.5 and almost 3.0 (Hansen, 1959). The value of the exponent for shopping opportunities within the Lansing Metropolitan Area, 2.0, which is obtained in this study, accordingly, should be regarded as an appropriate figure. Accessibility to Employment Opportunities It is commonly said that the Lansing Metropolitan Area's economy is based on the "big three:" automobile production, state government, and education. In fact, General Motors' Oldsmobile Division, the state government, Michigan State University, and a fourth influential employment sector, local governments, together account for almost half of all employment in the Lansing Metro­ politan Area. The State Government employed approximately 39.000 workers in 1980, including about 10,000 Michigan State University employees. Approximately 24,000 workers 151 are employed by Oldsmobile Division of General Motors, and local governments employed about 24,000 workers in 1980. The remaining half are employed by such sectors as retail trade, services, wholesale, transportation, machinery, etc. No detailed data for these sectors are available for the year 19 80. However, another publication done by the (Lansing) Tri-County Regional Planning Commission in 1979 illustrates six key employment locations. 75 These are Lansing CBD, the area between Lansing CBD and East Lansing CBD, East Lansing CBD, the Oldsmobile Plant in Downtown Lansing, and the Lansing and Meridian Shopping Mall areas. Although there are no concrete data concerning the numbers of employees in these six locations, this estimate was made by the writer based on the employment data in 1974. (The above publication released in 1979 by the Commission also uses the data for the year 1974.) The assumed number of employees in each of the above six employment locations is shown in Figure 26. The accessibility at each of the 192 nodes to these six employment locations was calculated; the results are shown in Appendix VIII. As in the previous section, the 192 nodes were reaggregated into 4 8 township nodes and the statistical relationships between the 4 8 township nodal 75 The (Lansing) Tri-County Regional Planning Commission, Long Range Street and Highway Plan for the Tri-County Region, Lansing: Tri-County Regional Planning Commission, April 1979. 152 1 2 5 6 9 10 13 14 3 4 7 8 11 12 15 16 17 18 21 22 25 26 29 3 0 / 'Township/Part of Lansing (18,000) 19 20 23 24 27 28 31 42 Lansing Mali Area/Delta / 36 33 34 37 41 38 A Downtown Lansing Area (35,500) Oldsmobile Plant Area (24.000) 42 Lansing/Eas Lansing Corridor / / 36 39 49 50 53 51 52 55 35 30 24 65 66 69 70 73 74 67 68 71 72 75 76 * 81 82 85 86 89 90 93 83 84 87 88 91 92 97 93 101 102 105 99 100 103 104 113 114 117 115 116 119 ” IB / V LJ ■■ ■i■■ 43 40 (15.000) ,Downtown East Lansing Including M.S.U. / / /> (24.000) Mall Area / T // / /.Meridian (6 ,000) '64 j y j y 60/ 54 137 138 .41 142 139 140 143 144 1 80 132 .» 94 145 146 149 150 153 154 157 158 95 96 147 148 151 152 155 156 159 160 106 109 110 161 162 165 166 169 170 173 174 107 108 111 112 163 164 167 168 171 172 175 176 118 121 122 125 126 177 178 181 182 185 186 189 190 120 123 124 127 128 179 180 183 184 187 188 191 192 12 12 18 Lansing Metropolitan Area 24 30 36 42 48 miles Clinton County ( 1-64) — Eaton County ( 65-128) Ingham County (129-192) Figure 26.— Locations of Employment in the Lansing Metropolitan Area and the Levels of Attractiveness (the Number of Employment). SOURCE: Tri-County Planning Commission, Projected Development Patterns Year 2000, p. 33. Adjusted by Shun'ichi Hagiwara. 153 accessibilities and their population were also examined. The results are shown in Table 15. As shown in Table 15, the correlation coefficients obtained are again mostly high, ranging from 0.8 09, at k = 0.5, to 0.954, at k = 2.0. The highest correlation coefficient was obtained again at k — 2.0, and this value should also be regarded as an appropriate one. These two studies indicate that the population in the townships in the Lansing Metropolitan Area decrease in proportion to the inverse-square of the distance from the five major retail centers and the six major employment centers. Using this relationship, it is possible to estimate the residential growth in any township in the Lansing Metropolitan Area if new or additional employment or shopping opportunities were added anywhere within the Lansing Metropolitan Area. Accessibility to Urban Functions Population movement during the past decade (1970198 0) in the Lansing Metropolitan Area can be labelled the "non-urban township growth" in which people are moving into the "non-urban townships" around smaller cities. Several reasons for this have already been mentioned, but it is occurring primarily because of lower taxes and security, etc. in the non-urban areas and still can allow people to enjoy the necessary services for comfortable 154 TABLE 15.— Nodal Accessibility to Employment at Township Base and Statistical Rela­ tionship between Accessibility and Population. Township Lebanon Essex Greenbush Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfield Roxand Oneida Delta Vermonvllle Chester Benton Windsor Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham White Oak Onondaga Leslie Bunker Hill StockbridRe 697 1,929 2,330 2,288 1,067 9,747 3,241 2,350 1,547 2,111 2,287 2,060 3,602 13,203 5,746 1,998 1,975 10,298 28,262 1,942 1,622 3,907 6,078 1,683 8,769 4,965 3,725 2,725 3,205 1,380 5.B03 116,493 77,603 5,472 1,456 36,722 2,845 3,004 3,413 2,460 9,132 1,974 1,096 2,289 4,300 1,794 2.914 Slope Y-interception Corr. Coeff. (r) k - 1.0 Access­ ibility k - 1.5 Access­ ibility k - 2.0 Access­ ibility k - 2.5 Access­ ibility k - 3.0 Access­ ibility 82,931.9 14,084.9 2,400.4 91,252.4 17,080.5 3,213.4 96,465.1 19,052.6 3,775.2 91,122.7 17,031.6 3,200.1 91,252:4 17,080.5 3,213.4 102,808.6 21,749.2 4,639.4 110,327.9 24,979.4 5,686.5 102,627.9 21,675.9 4,618.5 4,639.4 102,808.6 21,749.2 120,612.2 30,167.9 7,671. 7 132,977.3 36,515.9 10,147.8 120,360.1 30,068.3 7,649.6 120,612.2 30,167.9 7,671.7 155,319.2 51,885.4 18,443.6 183,464.2 72,077.7 29,858.1 155,295.6 52,244.4 18,903.4 19,642.2 97,815.9 3,967.5 112,556.8 26,124.2 6,126.6 137,710.0 39,642.2 11,700.7 203,652.0 96,261.0 53,283.1 88 ,868.8 16.189.2 2,962.1 99,398.7 20,303.2 4,175.9 115,071.7 27,361.5 6,587.5 142,812.4 42,906.4 13,300.6 81,140.9 13,477.8 2,245.6 88 ,868.8 2,962.1 16,189.2 4,746.8 99,39B.7 20,303.2 6,587.5 115,071.7 27,361,5 1,779.7 75,148.5 11,551.3 2,245.6 81,140.9 13,477.8 2,962.1 16,189.2 88,868.3 99,398.7 20,303.2 4,175.9 271,662.8 172,083.4 124,595.1 204,969.7 100,963.8 60,801.5 139,540.7 41,107.8 12,621.7 114,144.3 26,940.6 6.450.2 166,420.0 59,047,2 22,078.9 142,683.9 43,154.4 13,683.0 7,726.8 119,632.2 29,930.8 101,978.8 21,446.7 4,563.6 8,653.6 126,107.8 32,833.0 114,804.7 27,246.6 6,556.1 101,978.8 21,446.7 4,563.6 3,157.7 90,622.3 16,861.5 5,088.8 106,306.9 23,192.3 99,216.9 20,227.3 4,213.0 90,622.3 3,157.7 16,861.5 13.925.7 82.440.9 2.362.1 410.5 607.7 750.4 604.5 607.7 997.9 1,302.0 993.0 997.9 1,984.5 2,854.2 1,984.0 1,984.5 7,038.2 13,074.9 7,427.6 806.0 1,451.7 3,544.1 34,892.2 544.4 864.7 1,605.7 4.254.B 375.3 544.4 864.7 1,605.7 274.9 375.3 544.4 864.7 101,000.1 44,272.5 4,072.8 1,568.5 8,769.2 4,600.0 2,076.9 984.1 2,310.2 1,601.0 984.1 595.4 1,123.0 859.0 595.4 402.4 70.4 115.4 149.7 114.8 115.4 216.5 299.7 215.6 216.5 522.5 812.6 525.1 522.5 2,897.6 6,046.9 3,176.1 196.8 347.7 1,102.2 26,501.0 100.4 180.3 396.3 1,403.6 63.0 100.4 180.3 396.3 42.5 63.0 100.4 180.3 SB,852.3 37,004.0 1,392.6 387.8 3,717.3 1,659.3 587.3 215.3 1,525.0 396.9 215.3 113.1 249.4 179.0 113.1 12.2 22.0 Population 1,688 k - 0.5 Accesslbllitv 68.8 29.9 21.9 22.0 47.3 69.3 47.3 47.3 139.9 234.1 141.8 139.9 1,285.5 2,940.1 1,467.8 33.8 84.0 352.0 22,448.0 18.6 37.8 98,8 476.7 10.6 18.6 37.8 98.8 6.5 10.6 18.6 37.8 82,413.2 33,600.2 507.9 97.6 1,681.2 648.2 176.5 47.8 171.5 100.1 47.8 21.6 55.8 37.6 21.6 11.8 0.4298723 0.6429734 0.9372413 1.1863299 1.3569475 1.4638146 -42000.18 -12367.97 -2161.168 1947.6165 3530.2735 4114.2040 0.8087223 0.9009588 0.9372413 0.9543566 0.9511577 0.9478019 155 lives even in smaller cities. 76 The necessary services, however, may better be translated as the "urban functions" described earlier. Taking into account this recent trend of population movement, the smaller cities with more than a 2,5 00 population were selected, in addition to such larger cities as Lansing and East Lansing, as the destination nodes. Those cities selected as the destination nodes and their populations are as follows: Lansing East Lansing St. Johns 116,500 (most of theCity ofLansing excluding the parts located in Dewitt, Delhi, and Delta Township areas) 77,600 (East Lansing and part of the City of Lansing) 7,4 00 Dewitt 3,17 0 Grand Ledge 6,920 Charlotte 8,250 Eaton Rapids 4,510 Mason 6,02 0 Williamston 2,980 The figures above are round numbers; the locations of those nine cities are shown in Figure 27. The results of the study are shown in Appendix IX. As in the previous sections, the accessibility of the 192 nodes were reaggregated into 4 8 township nodes to examine 76Jane Garrick (1981). 156 4g miles St. Johns (7,400) Grand Ledge (6,920) Dewitt (3,170) Eaton Rapids (4,510)i Lansing (116,300) Charlotte (8,250) East Lansing (77,600) Mason (6,020) •\W11 llama ton (2,980) miles E — Clinton County ( 1-64) Eaton County ( 65-128) Ingham County (129-192) Figure 27.— Locations of Nine Destination Nodes (Nine Cities with Population More Than 2,500). SOURCE: Tri-County Regional Planning Commission, 1980 Census Results. Adjusted by Shun'ichi Hagiwara. 157 the statistical relationship between the accessibility to urban functions at each township and its population. results are shown in Table 16. The The correlation co­ efficients obtained in this part of the study range from 0.806, at k = 0.5, to 0.969, at k = 2.0. Again, fairly and very high linear relationships were found in this case, and the correlation coefficient, 0.969, obtained here was the highest among those obtained in the accessibility studies for shopping and employment opportunities and urban functions. Hence, a study has been made for three different attractions: shopping opportunities, employment oppor­ tunities, and urban functions. In the writer's view, the third attraction (urban functions) is the best measure to investigate the recent population movement in the Lansing Metropolitan Area and in most of urban areas in the United States. According to Jason Whitler of the (Lansing) Tri- County Regional Planning Commission, the strong growth of non-urban townships was also evident in neighboring sections of Shiawassee and Ionia Counties. It is safe to say that most of urban areas in the United States have experienced a similar phenomenon during the past decade. By taking into account the urban functions in smaller cities, it becomes possible to approach the recent problem of population movement to rural areas which has been labelled as an "exurbanization" movement. In this regard, the urban 158 TABLE 16.— Nodal Accessibility to the Urban Functions at Township Base and Statistical Relation­ ship between Accessibility and Population. Township Lebanon Essex Greenbush Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld Roxand Oneida Delta Vermontville Chester Benton Windsor Kalatno Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheatfield Leroy Aurellua Vevay Ingham White Oak Onondaga Leslie Bunker Hill Stockbrldge Population 697 1,688 1,929 2,330 2,288 1,067 9,747 3,241 2,350 1,547 2,111 2,2d7 2,060 3,602 13,203 5,746 1,998 1,975 10,298 28,262 1,942 1,622 3,907 6,078 1,683 8,769 4,965 3,725 2,725 3,205 1,380 5,803 .116,493 77,603 5,472 1,456 36,722 2,845 3,004 3,413 2,460 9,132 1,974 1,096 2,289 4,300 1,794 2,914 Slope Y-intersectlon Corr. Coeff. (r) k - 0.5 Access­ ibility k - 1.0 Access­ ibility k - 1.5 Access­ ibility k - 2.0 Access­ ibility k “ 2.5 Access­ ibility k - 3.0 Access­ ibility 15,977.8 17,531.8 18,900.3 17,750,1 17,592.7 19,820.2 22,055.4 20,094.0 19,553.6 22,478.5 25,399.3 23,329.5 22,780.4 27,B59.5 34,724.4 30,443.0 13,288.8 21,017.4 25,512.4 33,305.9 16,848.0 19,085.1 21,392.1 24,879.8 15,610.8 18,168.7 19,349.1 21,472.4 14,547.1 15,910.8 17,206.1 19,184.3 47,124.0 39,374.4 26,385.8 21,551.9 28,808.8 26,486.8 22,221.3 19,092.7 23,521.4 22,480.6 19,465.0 17,260.5 20,165.0 19,109.3 17,335.0 15.746.5 2,774.9 3,392.2 4,043.5 3,442.0 3,377.4 4,422.6 5,918.9 4,443.1 4,157.1 5,529.4 7,130.0 5,993.9 5,766.5 8,688.6 14,040.4 10.B36.3 3,627.8 4,846.7 7,636.4 12,940.6 3,103.0 4,138.9 5,039.1 6,764.7 2,799.0 4,400.5 4,264.4 5,103.1 2,321.0 2,846.2 2,983.5 4,408.0 28,381.5 20,602.7 7,987.3 5,140.0 9,159.9 7,883.8 5,457.1 3,977.0 6,105.0 6,002.9 4,159.8 3,235.3 4,498.6 4,012.1 3,267.2 2.682.3 491.0 687.2 958.5 682.8 663.8 1,077.2 2,121.0 1,013.4 898.2 1,386.8 2,065.8 1,579.2 1,539.3 2,827.8 6,181.2 4,222.1 728.9 1,149.3 2,751.5 5,461.9 587.8 1,001.2 1,228.6 1,874.6 534.9 1,723.3 1,046.9 1,274.9 383.2 551.7 659.7 1,373.2 20,026.6 13,436.8 2,685.8 1,276.6 2,994.8 2,469.9 1,393.4 846.3 1,654.1 2,039.1 918.0 616.0 1,062.4 871.3 630.5 461.8 89.0 149.3 270.0 139.3 134.5 303.3 1,167.6 240.1 197.5 356.1 620.5 421.0 445.1 959.4 2,984.2 1,797.0 148.6 281.7 1,353.7 2,484.5 115.8 289.3 312.8 529.0 115.2 1,127.7 304.3 344.6 16.6 35.7 95.0 29.5 57.8 103.9 900.2 59.8 44.4 93.4 194.9 117.5 144.4 339.0 1,598.3 827,9 30.8 71.9 928.1 1,203.4 24.1 104.0 84.0 151.8 28.9 958.2 108.8 104.9 3.4 9.6 40.9 6.5 6.3 43.1 811.7 15.7 66.2 12.1 120.5 142.5 709.0 16,024.8 10,454.4 1,084.1 336.0 1,005.2 817.9 375.4 185.2 478.4 1,033.4 211.5 119.4 277.5 198.0 122.5 80.4 30.5 33.8 543.6 14,003.8 9,113.0 575.0 96.7 345.7 287.5 109.5 41.9 152.3 907.2 51.6 23.7 84.9 47. 7 24.6 14,3 10.2 25.0 64.9 33.1 53.9 124.7 961.6 407.0 6.4 19.2 786.9 612.5 5.4 45.3 24.0 44.3 8.4 893.2 46.8 37.4 2.5 8.9 9.0 492.7 12,943.2 8,468.9 403.8 31.6 121.6 107.7 35.7 10.0 54.9 666.4 13.4 4.8 31.4 12.4 5.1 2.5 2.5405034 3.8855811 5.7302372 7.2291078 8.2021434 8.7836290 -47645.04 -15133.82 -3361.197 932.26640 2718.7074 3463.2180 0.8055598 0.9062104 0.9588910 0.9690317 0.9645855 0.9590642 159 functions are considered to be the prime attraction for people and the key factor in locational decisions made by people and also entrepreneurs in the following study. Before getting into the next stage of the research concerning the site selection of a Lansing HSIPT system terminal and the probable impacts flowing outward from the site to the rest of the Lansing Metropolitan Area, we may consider one of the interesting arguments concerning the concept of accessibility offered by John Symons. 77 He rejects the concept of nodal accessibility which has been discussed in the previous text. According to him, the nodal accessibility which is often higher in the CBD and lower in the suburbs is a superficial one. He asserts that one should look at the distribution of accessibility per person (per capita accessibility) at each node. By applying this per capita accessibility concept, according to him, one will find that highly accessible CBD nodes with high population densities often have as low or lower per capita accessibility than low accessibility, suburban low density nodes. Although Symons developed the per capita accessibility concept to examine equity and efficiency in public facility location, and though his 77 John G. Symons, Jr., "Some Comments on Equity and Efficiency in Public Facility Location Models," ANTIPOLE, 3, 1, November 1971, p. 64. Also, see David Harvey, Social Justice and the City, Baltimore: The John Hopkins University Press, 1973, pp. 96-118. 160 concept is not directly related to residential or industrial land use models, it still might be possible to find out certain standards for the developability of land by using his method. In the following section, the writer applies this per capita accessibility concept to the Lansing Metropolitan Area to determine if two such radically different concepts as real and superficial accessibilities actually exist. Concept of Per Capita Accessibility: How Does It Work? Symons1 comments concerning the nodal accessibility concept can be summarized in the following two comments: 1) per capita accessibility at the CBD will be as low or lower than the one at the suburban areas with a low density of population; and 2) there will be a strong statistical relationship between per capita accessibility and per capita income. In this section, these two comments offered by John Symons are investigated and, if not found useful, alternative ways to utilize the concept of per capita accessibility will be sought. Symons* concept of per capita accessibility is expressed as follows: Ai Apci = ---Popi where . . . Apci = per capita accessibility at node i A^ = nodal accessibility at node i Popi = population at node i 161 Table 17 shows the nodal accessibility to urban functions in the Lansing Metropolitan Area at the 48 township nodes, population in the 48 township nodes, per capita accessibility at each of the 4 8 township nodes based on the above formula, and per capita income at each of the 48 township nodes. The means and standard deviations are calculated for the nodal accessibility, per capita accessibility, and per capita income. The distribution of nodal accessibility is shown in Figure 28 and the distri­ bution of per capita accessibility is shown in Figure 29. As shown in Figure 28, the disparity between the nodes with the highest nodal accessibility and the nodes with the lowest accessibility is very high; only nine townships (18.8%) have a nodal accessibility higher than the mean. Per capita accessibility shown in Figure 29, however, illustrates less disparity. Thirty-four of the 48 town­ ships' per capita accessibility fall into a plus and minus one (1) standard deviation from the mean (70.8%). Twenty out of the 4 8 townships have per capita accessibility higher than the mean, and most of those townships in the higher mean block are concentrated in the central part of the Lansing Metropolitan Area. Six townships out of the so-called "nine township area," which is composed of such townships as Watertown, Dewitt, Bath, Delta, Lansing, Meridian, Windsor, Delhi, and Alaiedon, have per capita accessibility higher than the mean. The very low per 162 TABLE 17.— Nodal Accessibility to the Urban Functions, Per Capita Accessibility to the Urban Function, and Per Capita Income (Township Base). Township Lebanon Essex Greenbush Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfleld Roxand Oneida Delta Vermontville Chester Benton Windso Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamscon Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham White Oak Onondaga Leslie Bunker Hill Stockbridge Mean (/*> Std.'-Dev. (s) Population 697 1,688 1,929 2,330 2,288 1.067 9,747 3,241 2,350 1,547 2,111 2,287 2,060 3,602 13,203 5,746 1,998 1,975 10,298 28,262 1,942 1,622 3,907 6,078 1,683 8,769 4,965 3,725 2,725 3,205 1,380 5,803 116,493 77,603 5,472 1,456 36,722 2,845 3,004 3,413 2,460 9,132 1,974 1,096 2,289 4,300 1,794 2,914 Nodal ^ 'Accessibility 89.0 149.3 270.0 139.3 134.5 303.3 1,167.6 240.1 197.5 356.1 620.5 421.0 445.1 959.4 2,984.2 1,797.0 148.6 281.7 1,353.7 2,484.5 115.8 289.3 312.8 529.0 115.2 1,127.7 304.3 344.6 66.2 120.5 142.5 709.0 16,024.8 10,454.4 1,084.1 336.0 1,005.2 817.9 375.4 185.2 478.4 1,033.4 211.5 119.4 277.5 198.0 122.5 80.4 1,073.4 2,668.0 Per Capita Accessibility 0.128 0.088 0.140 0.060 0.059 0.284 Per Capita Income 0.045 0.068 0.028 3,635 3,990 3,381 4,142 3,396 3,253 4,513 4,236 3,311 4,574 4,267 4,250 4,142 5,225 4,710 4,233 3,627 3,731 5,091 5,711 3,660 3,958 4,194 4,862 3,730 4,429 4,805 4,176 4,341 4,515 3,936 4,437 4,998 5,278 5,033 4,223 4,847 4,936 4,937 4,816 3,B22 5,133 3; 903 4,824 3,372 4,477 3,283 4,186 0.128 0.076 4,303 599 0.120 0.074 0.084 0.230 0.294 0.184 0.216 0.266 0.226 0.313 0.074 0.143 0.131 0.088 0,060 0.178 0.080 0.087 0.068 0.129 0.061 0.093 0.024 0.038 0.103 0.122 0.138 0.135 0.198 0.231 0.027 0.287 0.125 0.054 0.194 0.113 0.107 0.109 0.121 611.147 Slope Y-interception 4223.42? Correlation! Coefficient (r) 0.078 * Value of the distant disutility parameter, K, used for this calculation is z.u 163 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Lebanon 89.0 Essex 149.3 Greenbush 270.0 139.3 *“ Duplaln n r n P Dallas 134.5 h EZ Bengal 303.3 i I i U Bingham 3 r 4_ 1 .167.6 L r Ovid 240.1 t P il i 197.5 Westphalia _ ! 356.1 Riley tz —1 III j i 620.5 Olive t ^HBSSSSEZil p 1 L L £ 421.0|_ Victor p j □ P e e w * 445.1 Eagle P □ 1 HeEaraeiE — 959,4 Watertown p p 1 i_ 984.2 2, Dewitt 1 r I 1 U P 1 ” p 1 Bath 1.797.0 p p 148.6 r I 7ii Sunfleld 11 . . _L L 5 — i | 1 i 281.7 Roxand i Oneida 1.353.7 ' z “ — 1 1 ~ 484.5 Delta 2. Vermontville 115.8 ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ .-vaJdtoAttSMCMMfl ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ M il& R a tv iS 'a iiiU B a 289.3 Chester ■ R i n a B H n n m .^s?tjs ~ 'zbs 312.8 Benton ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ .as:«.tf:': .asjnBE5i 529.0 ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ .S^ei^SSKEya Windsor 25 Kalamo 26 Carmel 27 Eaton 28 Eaton Rapids 29 BellavuB 30 Walton 31 Brookfield 32 Hamlin 33 34 35 36 Lansing Meridian Williams ton Locke 37 Delhi 38 39 40 41 42 43 44 45 46 Alaiedon Wheatfleld Leroy Aurelius Vevay Ingham Whlteoak Onondaga Leslie 47 Bunkerhill 48 Stockbrldge ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ .*-5&£Su2!S:aHlSiaiH 115.2 ,127.7 304.3 344.6 66.2 120.5 142.5 709.0 ,024.8 ,454.4 ,084.1 336.0 ,005.2 817.9 375.4 185.2 478.4 ,033.4 211.5 119.4 277.5 198.0 122.5 80.4 n .I'jijs asas SiSSSESHSH :t '«&'$,*o«y» m ■■ as«?3»^^^8iss^5i3^sjsigS*SgBBSHg •.-~r «a sh:*:$ aaHjgsiass^msjjs® &&&&&&H5S25BBBBS f-j *f,^« a«r.:-w p ' ^ ^ « f t m s g ? j « j s s s f t « s s s s a s i i w s s a a a w a J _ ni j 1 i m~ Ea Ra y3 1 z£ AJ Jp “i )LU j1 27_ *"i 4J m 3L i | Jr M 1 ! ~j JEZ ,__ Zl_ _ 11 ~~\3n EZ .— 9. I H i \ jp 1 _Ip — p_ J p — ,— i « m1i i1 i1i i _j p tj.i, L u ~| ~1 p Zj ‘; 1 _LJ "["S’n p “ j]I] < 441 I d ~p 3p □ Ml ~p r p I '1M i □c a_ Z 1__ LiL r ztz C t Z j 8j 1 L j p p _P J ZP zi P 1- ___ mm _L-! zlz _iL_ 1 3 t 1 [ 1 r J _j '1 1 r [£3,741.4 1,073.4 £1 Mean ( ) ■ 1,073.4 |<3,741.4 -1,549. 6 <| [<1,073.4 Mean (/*) ■ 1,073.4 Standard Deviation ( S ) ■ 2,668.0 Lansing Metropolitan Area Clinton County — Eaton County Ingham County ( 1-16) (17-32) (33-48) Figure 28.— Distribution of 4 8 Townships' Nodal Accessibility. 164 1 Lebanon 2 Essex 0.128 0.088 0.140 0.060 0.059 0.284 3 Greenbush 4 Duplain 5 Dallas 6 Bengal hi; 7 Bingham 0.120 8 Ovid 0.074 • i.,s (/.«• X»I 9 Wescphalla 0.084 10 Riley 0.230 11 Olive 0.294 12 Victor 0.184 ■ ■ ■ a n 13 Eagle 0.216 -0.266 14 Watertown 0.226 15 Dewitt 16 Path 0.313 17 Sunfleld 0.074 18 Roxand 0.143 ■ ■ ■ ■ ■ ■ 19 Oneida 0.131 ■ ■ ■ ■ ■ ■ 20 Delta 0.088 ■ M B H H 21 Vermontville 0.060 0.178 22 Chester 23 Benton 0.08ft 24 Windsor 0.0871 1y iStfsasSSSiJjisi.iitfS2| w mmy#.*3.y.a122aa aft3&&33m&8& sssBSSBSssissssoBSKSis ss&($${&!&s&smsms *A «£* • * r aiifi$3fe$ m V¥ ^ £*iZZl£2 laaisssa sasna aassa mss^sssfsg&sss ^§«KBSSSS8S88S J* x -4 ■■^?53na m ^SSS^SiiS38£5:SS§ ’ EiSS1 : 27 4J i 5:.204 S*A Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Herldlan Williamston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay tngham Whiteoak Onondaga Leslie Bunkarhlll Stockbrldge .W'fc»v'.•>,«rf*., ’._■r-*n a ra**0C.shj■ ;sf-.• * •*;:■»v-5£3 s ^ ^ ; ■ .> -5.£! JlTJt v? a.j*4 ft* < ■■KtVH ■■■■■■ "S* ■■■■■■ ■■■■■■ ’ luSaffiass ■■■■■■ ■■■■■■ ■ MNmEaHu Mu . m ■■■■■■ ■ ■ ■ ■ ■ ■ ..^KSiiaaf ■ ■ ■ ■ ■ ■ Jiisisisa A • >.*>.. 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 0 . 1 2 8 ^ W B < 0.204 S M i M SMSSS smm'sssss ^■SS!S$!S$S^$S 0.052/(X^ - X^)^ + (Y^ - Y 2 ^ ' the Pythagorean theorem. which is calculated from In this study, the distance between the 4 8 townships within the Lansing Metropolitan Area will be figured by the city block metric system based on the aforementioned "non-urban township growth" trend and the existence of the rectangular street system. Figure 32 shows the locations of 4 8 demand nodes and the paths between those 4 8 demand nodes. The result of the p-Median algorithm was the selection of Delhi 179 Lebanon Esaex Greenbush 4 Duplaln p. uanas 6 Bengal 7 Bingham 8 Ovid 9 Westphalia 10 Rilev 11 Olive 12 Victor 13 Eagle lb, watertown 15 Dewitt 16 Bath 17 Sunfleld 18 Roxand E- 20 Delta ! nj r j 1 1 1 i i : - c 7 1 1 | I i ij 7 VCUBOnLVlllt 22 Chester 23 Benton 24 Windsor £1 l 1 .2 | , I Kalamo Carmel Eaton Eaton Rapids SallQVue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham Uhlteoak 45 Onondaga is 46 Leslie 47 Bunkerhill 48 Stockbrldge 1 j,7 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 n i *rn j i i i r ,I n 23 ft 7 \ 3i 27 TR i1 4 ?i 11 ,7 1 h r \1 Path between Nodes • Centroid of township: the point at which population is assumed to concentrate. Lansing Metropolitan Area Clinton County { 1-16) — Eaton County (17-32) Ingham County (33-48) Figure 32.— Geocode System for 48 Townships in the Lansing Metropolitan Area. 180 Township as the optimal location for a Lansing HSIPT system terminal. 80 Although Delhi Township was already found to be the node that represents the feasible solution based on the aforementioned four prerequisites/ the following points should be considered to strengthen the rationale which can support this selection. 1. Those are: Delhi Township is the third largest township in terms of the number of its residents; however, more than 80 percent of its residents live in the northern half of the area which is incorporated in the City of Lansing. Accordingly, it is reasonable to assume that there will be no significant negative impacts on the existing communities if a HSIPT system terminal were built in the southern half of the area; 2. Delhi Township is obviously one of the most accessible areas from both of the most populated areas, the Cities of Lansing and East Lansing. qa To link the site for a A mathematical formulation of the "p-Median Problem" in the city block metric as: n m n m . minimize z = Z Z a..w, w. - y . + Z I a..w. x. - y. i=l j=l 13 11 1 31 i=l j=l 13 11 1 3 where z = the aggregate distance from all demand points to their closest supply center xi * yi = coordinates of the ith demand point X j , yj = the coordinates of the jth supply center w = the weight assigned to the ith demand point a^^ = 1 when the demand point i is served from supply center j, otherwise a^j = 0 . Lansing HSIPT system terminal in this township with the existing commercial centers in both cities could be accomplished fairly easily; Delhi Township accommodates two major interchanges of the interstate highway network. One is the interchange of 1-96 which connects Lansing to Grand Rapids and Detroit and US-27 (partially used as U.S. 1-69) which connects Lansing to Flint and Battle Creek and the other is the interchange of 1-96 and US-127 which connects Lansing to Jackson. The existence of these two major interchanges could strengthen the potential of Delhi Township as the optimal location for a Lansing HSIPT system terminal; Delhi Township per se does not belong to the group of townships which scored a high growth during the 1970's; it is located almost in the center of those highly developed townships (see Figure 2 3 on page 141). The introduction of a Lansing HSIPT system terminal in this township will strongly enhance locational benefits for this entity as well as for those highly developed townships noted; Delhi Township has an area which could be sensitive to development and which requires a large amount of groundwater in its eastern half; however, the south­ western corner of the area, where a HSIPT terminal 182 could be constructed would not be restricted by such a constraint (see Figure 21 on page 130). From these observations, the research justifies the conclusion that Delhi Township is a logical selection for a Lansing HSIPT system terminal. The final location decision concerning a HSIPT system terminal in a real situation, however, has to take into account a few more crucial economic elements which are briefly mentioned in the beginning of this chapter, in addition to the number of demands and transportation costs which are taken into account in PMEDIAN. In fact, several types of costs are ordinarily involved in the development of land resources. 1) Those are: the actual outlays of cash and human effort required to bring new land resources into use and to qualify partly developed resources for higher uses; 2 ) the social costs associated with individual and group sacrifices; 3) the time costs which arise because of the time it takes to bring resource developments into use; and 4) the superses­ sion costs associated with the frequent practice of scrapping existing developments to make way for new resource uses. 81 81 Raleigh Barlowe, Land Resource Economics: The Economics of Real Property, 2nd Edition, Englewood Cliffs: Prentice-Hall, Inc., 1972, pp. 197-218. 183 The so-called "project costs" include all of the above costs: namely, the full value of the land, labor, and materials used in establishing, maintaining, and operating the project plus an allowance for any adverse effectsresulting from the project. 82 "project costs,"along with the number In reality, these of demands and transportation costs from the locations of the demands, have to be taken into account so as to make this particular project have anyreal meaning. As has been discussed, Delhi Township is selected as the optimal area for the location of a HSIPT system terminal. The exact site or land parcel for a HSIPT system terminal, however, has to be narrowed down to a much smaller space than a general location in a 36 square mile township. As discussed in the previous chapter, each township is divided into 4 subareas of 9 square miles. This 9 square mile subarea would be large enough to accommodate all possible facilities related to the operation of a HSIPT system and other necessary facilities such as hotels, department stores, parking ramps, retail shops, etc. which likely follow the development of such a new rail terminal. In conclusion, by taking into account various constraints, the southwestern corner of Delhi Township (subarea number 147) has been selected as the 82Ibid. , p. 210. 184 exact site for the Lansing HSIPT system terminal. For the geographical location of the designated site and the relationship with nine of the most populated areas in the Lansing Metropolitan Area, refer to Figure 33. In the following section, the probable impacts from the creation of a Lansing HSIPT system terminal on the rest of the Lansing Metropolitan Area will be inves­ tigated and the necessary policies and plans to alleviate possible negative ramifications will be discussed. Impact Probabilities Flowing Outward from the Designated Lansing HSIPT System Terminal Site to the Rest of the Lansing Metropolitan Area The location of a Lansing HSIPT system terminal (new destination node) along with the location of nine destination nodes are shown in Figure 34. Figure 34, the weight As shown in (attractiveness) assigned to the new destination node is 37,000, which is equivalent to the population in Delhi Township (see Table 18). It will, however, be necessary to explain why the existing population in Delhi Township was selected as attractive. It is relatively easy to estimate the impacts of the development of such a high-speed rail terminal upon the neighboring areas qualitatively if the application of a similar case is allowed, such as that of the Japanese Shin Kansen. In fact, as mentioned earlier, a massive amount of construction of buildings and facilities always 185 1 2 3 d 5 6 7 8 9 10 11 12 13 Id 15 16 17 18 19 20 21 22 23 2d Lebanon Essex ' Greenbuah Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfield Roxand Oneida Delta Vermontville Chester Benton Windsor Kalaao Carmel US-27 Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian it. Johns Williams ton Locke Delhi Alaiedon WheacfieLd Leroy Aurelius Vevay Ingham Whiteoak Onondaga Leslie Bunkerhill Scockbridge Lansing i i rn flrand Ledge E a»tu_ Lansing- !i 1 ■ Ullliamston 1-96 Mason Charlotte Lansing' HSIPT Terminal:! Gaton Rapids US-127 US-27 Lansing Metropolitan Area — Clinton County ( 1-16) Eaton County (17-32) Ingham County (33-48) Figure 33.— Geographical Configuration of Ten Urban Centers. 43 miles 11 10 13 14 12 15 16 26 29 30 32 42 17 18 21 22 19 20 23 24 27 28 31 33 34 37 38 41 42 45 36 -St. Johns (7,400) ^ D e w i t t (3,170) ^ Lansing (116,500) Grand Ledge (6,920) East Lansing (77,600) Eaton Rapids (4,510)^ Charlotte (8,250)1 Lansing HSIPT Terminal / (37-.000) ,Mason (6,020) \Williamston (2,980) .o miles Lansing Metropolitan Area Clinton County ( 1-6 4) — Eaton County ( 65-128) Ingham County (12 9-192) Figure 34.— Locations of New Lansing HSIPT Terminal Node and the Existing Nine Destination Nodes. SOURCE: Tri-County Regional Planning Commission, 19 80 Census Results. Adjusted by Shun'ichi Hagiwara. 187 accompanies the development of such a high-speed rail terminal in Japan. Those buildings and facilities built in and around the rail terminal are, in most cases, hotel and office buildings, department and retail stores, and other facilities related to transportation such as parking ramps, bus and taxi terminals, in addition to the facilities necessary for the operation of a high-speed rail system. Further, in many large cities, the expansion or new construction of highways and subway rail networks to the new rail terminal have commonly been seen. These impacts are, however, hardly quantifiable. As discussed in the previous chapter, Delhi Town­ ship, the designated site of the nominated Lansing HSIPT system terminal, does not have a key "urban center" such as the Cities of Lansing and East Lansing within its territory, despite the fact that a large population resides in that township. Consequently, the township nodal accessibility and per capita accessibility, in particular, are very low, in spite of its locational superiority to the most densely populated areas of the Lansing Metropolitan Area such as the Cities of Lansing and East Lansing. The research was focused on this large population; in other words, on the potential of 37,000 residents and designated it as the weight node (attractiveness) of the new destination (the Lansing HSIPT system terminal). The underlying assumption for the selection of the existing population 188 as the weight (attractiveness) is that the new destination node can be expected to offer some levels of urban functions which should be enjoyable to those 37,000 residents. To examine the probable impacts of the creation of a HSIPT system terminal at the 147th subnode in Delhi Township, as done in the previous chapter, the attractionaccessibility indices were calculated. The formula used for this part of the research is: A. = 1 m Ej I --j=l ^ where A = accessibility at node i E = size of attraction at node j D = distance disutility between node i and j k = an exponent describing the effect of the travel time between node i and j (k = 2 which is obtained from the previous calculation) m = number of destination (place of attraction) j = 1 , ..... 10 i = 1, ....... . 192 The result of the calculation is shown in Table 19. The isopotential contour map based on the nodal acces­ sibility of 192 nodes is shown in Figure 35. The isopotential map shown in Figure 35 should be interpreted as follows: 1. The area surrounded by a 1,000 contour line now appears in two locations. Those are the existing Lansing urban area and the area around a new Lansing HSIPT system terminal at the 147th subnode in Delhi Township. The 189 TABLE 19.— The 192 Nodal Accessibilities to Ten Major Urban Centers (Urban Functions) in the Lansing Metropolitan Area. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 36 39 40 41 42 43 44 45 46 47 48 1 SI 1 '•O 1 ■H C A _ ^m 19.8 23.8 24.0 29.8 29.0 37.6 38.2 55.9 55.4 40.9 126.8 60.5 36.1 28.6 48.1 36.2 30.0 39,3 33.7 43.0 56.7 127.4 55.4 80.5 799.0 134.0 164.7 90.4 71.3 46.3 78.2 56,1 40,5 52.5 51.4 69.7 66.8 92.9 90.0 132.6 146.1 109.0 238.5 161.2 105.5 72.6 165.3 103.1 EJ _ k where 1 ■ l,,..,192; j ■ 1,... ,10; k - 2.0. ij 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 69.5 103.3 101.3 197.1 135.6 235.9 217.9 417.2 722.0 294.9 1462.9 573.9 321.3 164.4 1030.4 315.1 38.8 50.4 33.5 42.5 68.9 103.4 56.2 79.2 197.2 888.7 109.1 206.1 478.1 1445.5 231.4 441.5 30.8 39.3 30.8 41.0 52.7 78.9 62.0 143.0 88.0 124.4 94.2 118.8 168.6 296.6 189.5 531.7 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 ' 31.4 48.5 23.9 31.8 123.3 865.2 49.2 124.3 144.8 97.3 64.8 66.9 119.2 201.0 86.8 155.7 19.6 24.5 16.2 19.6 32.8 50.9 24.5 32.8 46.4 57.1 33.7 39.8 103.4 521.2 52.9 101.0 11935.6 219B.5 1509.5 599.5 8114.5 1030.4 1048.9 330.0 282.1 192.0 227.5 415.8 107.1 71.9 112.2 65.4 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 17a 179 180 181 182 183 184 185 186 187 188 189 190 191 192 801.9 357.9 3866.7 567.7 366.1 188.5 323.2 158.2 136,8 118.8 108.8 80.5 69.8 50.1 56.7 42.8 542.7 264.1 196.9 132.0 744.0 159.1 160.2 82.7 90.0 63.4 63.7 47.6 46.4 35.9 36.6 29.2 153.3 93.0 81.2 62.6 85.8 58.3 58.0 43.2 47.5 37.2 36.7 29.7 29.6 24.2 24.0 20.4 190 46 miles St. Johns Dewitt Lansing East Lansing Lansing HSI?T Terminal lUllliamston Grand Ledge 50 300 260 189 4 kCharlotte 30 '■’M Eaton Rapids 36 190 miles 'Maoon 300 - 500 500 - 1,000 1,000 and over Lansing Metropolitan Area Clinton County { 1-64) — Eaton County ( 65-128) Ingham County (129-192) Figure 35.— Isoaccessive Contour Lines Based on the 192 Nodes' Accessibility to Ten Urban Centers (Urban Functions). 191 size of the Lansing urban area surrounded by a 1,000 contour line has not changed significantly, compared with the same area shown in Figure 30 on page 168. These two areas, surrounded by the 1,000 contour line, may eventually be joined to each other as a unitary urban area; 2. The City of Mason, which has maintained its status as a local core city in Figure 30, is completely absorbed into the suburban area of the Lansing urban area. This implies that the City of Mason will soon to be a dormitory town of the Lansing urban area, if a Lansing HSIPT system terminal is built at the 14 7th node in Delhi Township; 3. The Cities of St. Johns and Charlotte, on the other hand, can maintain their statuses as resional core cities, respectively, even after the creation of a Lansing HSIPT system terminal; 4. The City of Eaton Rapids will emerge as one of the key regional core cities in the Lansing Metropolitan Area after the creation of a Lansing HSIPT system terminal because of its location proximity to the new terminal; 5. The City of Grand Ledge's position as a dormitory town of the Lansing urban area will not change significantly. Similarly, the City of Williamston would not be influenced greatly by the creation of the new terminal; 192 6. The direction of the movement of the development pattern of the Lansing urban area, which has been observed during the past decades, will shift from the direction along the east-west axis to the northsouth. A new urban corridor will emerge between the City of St. Johns and the City of Eaton Rapids (Figure 36) . The conceptual image of the new urban corridor illustrated in Figure 36 is more realistically shown in Figure 37. A highly urbanized core shapes like the inverse figure of "L." This inverse "L" area accommodates parts of Dewitt and Delta Townships, the Cities of Lansing and East Lansing, the western half of Meridian Township, and the western half of Delhi Township. The new urbanized area around the new urban core accommodates most of Dewitt Township, the City of Dewitt, the City of Grand Ledge, three-quarters of Delta Township, the eastern half of Windsor Township, the eastern half of Delhi Township, the northern half of Aurelius Township, the City of Mason, and the eastern half of Meridian Township. The new suburban area will accommodate the southern half of Olive Township, the southeastern half of Watertown Township, most of Oneida Township, the western half of Windsor Township, most of Eaton Rapids Township, and most of Williamston Township. For convenience sake, the whole area which includes the most densely urbanized core area, the 193 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Lebanon Essex Greenbush Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Wa tertown Dewitt Bath Sunfield Roxand Oneida Delta Vermontville Chester Benton Windsor IhhiiS 25 26 27 28 29 30 31 32 33 34 35 36 37 3B 39 40 41 42 43 44 45 46 47 48 Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaicdon Wheatfield Leroy Aurelius Vevay Ingham Whlteoak Onondaga Leslie Bunkerhill Stockbrldge ion assassin Densely Urbanized Core o Local Urban Core Hew Major Urban Corridor Regional Core Major Local Corridor Major Intra-Urban Corridor Lansing Metropolitan Area — Clinton County ( 1-16) ---- Eaton County (17-32) Ingham County (33-48) Figure 36.— Concept of the New Urban Corridor in the Lansing Metropolitan Area. 194 1 Lebanon Olive 25 26 27 28 29 30 31 32 33 34 35 Victor Eagle Watertown Dewitt Bath Sunfield Roxand Oneida Delta Vermontville Chester Benton Windsor 42 43 44 45 46 47 48 2 Essex 3 Greenbush 4 Duplaln 5 Dallas 6 Bengal 7 Bingham B Ovid 9 Westphalia 10 Riley 11 12 13 14 15 16 17 18 19 20 21 22 23 24 ana LnjXiD Gr rti Kalamo Carmel Eaton Eaton Rapids Bellevue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon Wheat fie Id Leroy Aurelius Vevay Ingham Whlteoak Onondaga Leslie Bunkerhlll Stockbrldge tttTS CBD WllTlEBB on rnridiejt most densely urbanized area urbanized area The Hew Greater Lansing Area ^ " --»— « suburban1area | — Lansing Metropolitan Area — ~~| rural area Clint Clinton County ( 1-16) Eaton County (17-32) Ingham County (33-48) Figure 37.— Probable Land Uses in the Lansing Metropolitan Area due to the Development of the Lansing HSIPT Terminal. 195 urbanized core area, and the suburban area will be called the "New Greater Lansing Area." To functionalize this "New Greater Lansing Area," however, several important improvements to, or new construction of, highways will be necessary. These are: 1. the improvement of US-27 between St. Johns and Lansing; 2. the improvement of M-9 9, which now connects Eaton Rapids and Lansing; 3. the improvement of M-50 between Eaton Rapids and Charlotte; 4. the construction of a feeder highway to the site of the Lansing HSIPT system terminal from the interstate highway of 1-96. The formation of the "New Greater Lansing Area" would result in rather significant changes in land uses in the Lansing Metropolitan Area. Figure 38 illustrates the important relationships between the "New Greater Lansing Area" and four important land uses in the Lansing Metropolitan Area. As shown in Figure 38, some of the productive agricultural lands are like to be deleted and replaced by the "New Greater Lansing Area." Notable aggregations of productive agricultural lands are the agricultural lands in Bingham Township where the City of St. Johns exists; the ones in Oneida Township where the City of Grand Ledge exists; the one that lies between Eaton and Eaton Rapids Townships; and the ones located 196 1 Lebanon 2 Essex Creenbush 4 Duplain 5 Dallas 6 Bengal 7 Bingham 8 Ovid 9 Westphalia Kalano Carmel Eaton Eaton Rapids Ballsvue Walton Brookfield Hamlin Lansing Meridian Williamston Locke Delhi Alaiedon WheatfieId Leroy Aurelius 42 Vevay 43 Ingham Uhiteoak Onondaga Leslie Bunkerhill Stockbridge mm 10 Riley 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Olive Victor Eagle Watertown Dewitt Bath Sunfield Roxand Oneida Delta Vermoncville Chester Benton Windsor Productive rm w Agricultural LandB Major Foreat Lands ■Major IFlood'* Plains Lansing Metropolitan Area Groundwater KBflSHHHMost urbanized Area sensitive to i::::::: 1 Urbanized Area Development Suburban Area i iRural Area Clinton County — Eaton County Ingham County ( 1-16) (17-32) (33-48) Figure 38.— Influences of the Development of the Lansing HSIPT Terminal on Land Uses in the Lansing Metropolitan Area. 197 in the western half of Alaiedon Township. However, as shown in Figure 38, the probable damage to productive agricultural lands is minor; that is, most of the productive agricultural lands in Clinton County are preserved and the ones in Eaton County as well. In terms of the preservation of forest lands , some care may have to be taken because two large forest lands which lie between Dewitt and Victor Townships and between Maridian and Williamston Townships are likely to be consumed by the "New Greater Lansing Area." Some of the major flood plains in Victor Township may likewise be consumed. Of all the probable negative impacts on land uses due to the creation of a Lansing HSIPT system terminal the most serious may be the one on groundwater. Most of the western half of Ingham County is categorized in an area where further development is very sensitive to the amount of groundwater. Although the "New Greater Lansing Area" will stretch into the western half of Eaton County, very careful attention must be paid the relationship between the location of developable groundwater and the direction of further development in the Lansing Metropolitan Area. From these observations, the profile of the "New Greater Lansing Area" was formulated after the creation of a HSIPT system in the Great Lakes Midwest Region was developed (Figure 39). As shown, a feeder highway is extended to the Lansing HSIPT system terminal from 1-96. 19G Lebanon EaBex Greenbush Duplain Dallas Bengal Bingham Ovid Westphalia Riley Olive Victor Eagle Watertown Dewitt Bath Sunfield Roxand Oneida Delta Vemontvllle Chester Benton Windsoc Kalar.o Carmel Eaton EatOR Rapid3 Bellevue Walton Brookfield Hamlin Lansing 34 Meridian 35 Williamston Locke Delhi Alaiedon Wheatfield Leroy Aurelius Vevay Ingham Whlteoak Onondaga Leslie Bunkerhlll Stockbridge US-27 Johna Dewitt Capitol Grand a Lansln Landing Vllllatnstoa 1-96 Charlotte Hasan a ^anslng HSIPT System Terminal Eaton Rap US-127 The HSIPT System Right-of-Way Monorail or Elewated Automated Guideway Transit System c Possible extension of Monorail or Elevated Automated Guideway Transit System Improved Existing Highway System Lansing Metropolitan Area Clinton County ( 1-16) — Eaton County (17-32) Ingham County (33-48) Figure 39.— Profile of the New Greater Lansing Area After the Creation of the HSIPT System Terminal in the Lansing Metropolitan Area. 199 New improved highway systems join Eaton Rapids and Mason to the Lansing HSIPT system terminal. The existing M-50 between Charlotte and Eaton Rapids is improved significantly to be a key local corridor. Between the Capitol City Airport and the Lansing HSIPT system- terminal, new monorail or automated elevated guideway transit systems could be installed. The branch line of this automated guideway transit system could also be extended to downtown East Lansing to attract the student body of Michigan State University which could be a significant captive market for a HSIPT system. In the not far distant future, this automated guideway transit system may be extended to the Cities of Dewitt and Eaton Rapids to intensify the functions of the newly emerged urban corridor proposed in this research. A primary objective of the research reported in this chapter was the projection of the probable impacts flowing outward from the site designated for a Lansing HSIPT system terminal upon the remaining Lansing Metro­ politan Area. In particular, the research focuses on the impacts upon land use changes. Ordinarily, a major goal of a projection study is to offer the necessary information of how much and where possible growth or decay is likely to occur in certain areas or regions. The research findings reported in this chapter, however, do not speak to the issue of how much, but where. As a matter of fact, the 200 strongest constraint for new development is the availability of vacant developable lands. If no more vacant, devel­ opable lands are available in a certain region or area, the projected increase of population or employment means that there will have to be an increase of density of population or employment activities on currently used lands; and, by the same token, the projected decrease of population or employment activities means the decrease of density of those elements. made by The In fact, one of the assumptions (Lansing) Tri-County Regional Planning Commis­ sion, when it dealt with the study entitled Projected Development Patterns Year 2000, is that "the influence that existing land use patterns exert on future locations of development must remain strong." 83 Without vacant, developable lands, any significant new development cannot be implemented. In this regard, the findings reported in this chapter demonstrate that there is, and will be, ample developable land in the vicinity of a HSIPT system terminal site and all over the Lansing Metropolitan Area. The findings successfully pinpointed the direction and location of future developments due to the creation of a Lansing HSIPT system terminal in the Lansing Metropolitan Area. 83 The (Lansing) Tri-County Regional Planning Commission (1979), p. 4. CHAPTER VI SUMMARY AND CONCLUSION Summary of the Research Findings This research undertaking is an examination of the probable impacts on rural-urban structural change in the Lansing metropolitan area in the State of Michigan resulting from the hypothetical creation of a HSIPT system in the Great Lakes Midwest Region. The principal HSIPT system network is assumed to link such large U.S. SMSAs as Milwaukee, Chicago, Detroit, Cleveland, and Pittsburgh, along with such middle-sized SMSAs as Grand Rapids, Lansing, Flint, Toledo, and Youngstown. This research undertaking also assumes that a HSIPT system in the Region should be extended to such Canadian CMAs as London and Toronto. In recapitulation, the objective of this research undertaking is to identify and evaluate the probable impacts of a HSIPT system which has been assumed to be scheduled for development in the Region. The impacts in three distinct areas were examined: the probable impact of a HSIPT system on the forty local communities in the Region; the probable impact of a HSIPT system as a competitor to non-transportation land uses in a specific local area where a HSIPT system terminal was assumed to be 201 202 built {the Lansing terminal area); and finally the probable impact of the terminal on the rest of the area metropolitan area) was analyzed. (the Lansing Considerable reference was placed on the impacts produced by the Japanese HSIPT system, the Shin Kansen, as well as secondary sources. Regional Impacts The research produced a number of results which varied in each area of impact. Among the forty local communities selected for the first part of the research, such local communities as Grand Rapids, Columbus, Cincinnati, Kalamazoo, and Indianapolis are likely to be influenced most significantly by the introduction of a HSIPT system in the Region. Next, London (Ontario, Canada), Lansing, Dayton, Cleveland, and Detroit are also likely to be influenced significantly by the system. Such local communities as Flint, Saginaw, Toledo, Akron, Port Huron, Jackson, and Sarnia are less likely to be influenced by the system. And such local communities as Lexington, Pittsburgh, Battle Creek, Toronto, Milwaukee, and Chicago are least likely to be influenced significantly by the system. The remaining seventeen local communities, such as Ann Arbor, Gary, Windsor (Ontario, Canada), Youngstown, Canton, Louisville, Madison, Lima, Erie, Southbend, Rockford, Hamilton (Ontario, Canada), Fort Wayne, Niagara Falls (Ontario, Canada), Peoria, Buffalo, and Davenport 203 may experience negligible impacts (if any at all) from the creation of the system in the Region. Most of the twenty communities joined together by the system are likely to be influenced significantly by the system. This system, however, is less likely to influence large communities such as Chicago, Milwaukee, Toronto (Ontario, Canada), and Pittsburgh than such medium sized communities as Grand Rapids, Columbus, Cincinnati, Lansing, Dayton, and Flint. Among these twenty communities, the communities not influenced significantly are Gary, Youngstown, and Windsor (Ontario, Canada). Instead, such communities as Saginaw, Port Huron, Jackson, Sarnia (Ontario, Canada), Lexington, and Battle Creek, which are assumed not to be directly linked into the network by the system, are likely to feel fairly strong indirect impacts. This is an interesting finding, for it implies that the system is less likely to influence such communities which are located very close to large communities. The reason why the system is less likely to influence such communities as Gary, Youngstown, and Windsor is relatively simple; namely, these three communities are already influenced strongly by such large communities as Chicago, Pittsburgh, and Detroit, respectively, and the effects of the time reduction due to the creation of a HSIPT system from these three communities to such large communities as Chicago, Pittsburgh, and Detroit are very minor. Also, the reason 204 for fairly strong impacts on such communities as Saginaw, Port Huron, Jackson, Sarnia, Lexington, and Battle Creek are that these communities are located very close to the communities where a local HSIPT system terminal is assumed to be created. Different HSIPT system corridors are equally feasible. As a matter of fact, there could be a number of alternative HSIPT system routes and configurations. Those optimal network designs will be necessary subjects for further research. Terminal Site Selection Impact The compatibility of a HSIPT system as a consumer of land with other, non-transportation land uses, was verified in the second part of the research, especially such land uses important for preserving a living environment of desirable quality as productive agricultural lands, forest lands, flood plains, and groundwaters. Namely, this part of the research processes verified that such valuable land uses as productive agricultural lands, forest lands, flood plains, and groundwaters will not be negatively influenced by a HSIPT system terminal and right-of-way if such elements are properly planned and installed. To realize this dual objective, the following four conditions were designated as the prerequisites for a HSIPT system design. Those were: 205 1. A HSIPT system right-of-way and terminal should not be placed on productive agricultural lands, on forest lands, or within flood plains; 2. A HSIPT system right-of-way and terminal should be located so as to geographically separate from densely populated areas; 3. A HSIPT system terminal should be located so as to be functionally linked with the existing commercial center of the area (nominally the "central business district") concerned; 4. A HSIPT system terminal should be located so as to be capable of being synchronized effectively with existing transportation modes such as highways, buses, mass transits, and airlines. Based on these four prerequisites, the seven townships of Watertown, Dewitt, Bath, Delta, Windsor, Delhi, and Alaiedon (all of these seven townships are located in the "nine township" area) were selected as the prime candidates for the site of a Lansing HSIPT system terminal; in other words, each one of these seven townships could be an appropriate location for the site of a Lansing HSIPT system terminal without incurring unnecessary conflicts with other non-transportation land uses. This part of the research undertaking also dealt with the location decision process for a local HSIPT system terminal. The Japanese experience clearly showed that the 206 selection of the site for a HSIPT system terminal has to be made with extreme caution. In fact/ on the local level/ the success of a HSIPT system greatly depends on the issue of where the site for the system terminal should be. Nevertheless, special interest groups often affect location decisions on this sort of public facility, and, consequently, the decision finally made frequently represents a consensus of the wishes of various groups. To alleviate such political and pluralistic location decision problems, objectivity has to be introduced into the decision process. The "p-Median" algorithm (which is packaged in the MSU software program as PMEDIAN) was found to be the most appropriate method to introduce objectivity in the location decision process for such a public facility as a local HSIPT system terminal. As mentioned above, seven townships were selected as the prime candidates for the location of the site of a Lansing HSIPT system terminal; so, these seven townships were logged in PMEDIAN as the feasible solution. The result of the "p-Median" algorithm was the selection of Delhi Township as the optimal location for a Lansing HSIPT system terminal. After reviewing the existing land uses and covers in that particular township, the location of the site for a Lansing HSIPT system terminal was determined to be in the southwestern corner subnode (no. 147). 207 The site designated has an area of 9 square miles (3 x 3 mile square), which was considered to be more than enough to accommodate the various facilities which are often developed along with, or soon after, the installation of a system terminal. The facilities usually built on the site are such facilities as hotel and office buildings, department and retail stores, other facilities related to transportation (such as parking ramps, bus and taxi terminals), and the facilities necessary for the operation of a high-speed rail system. As can be seen, most of these facilities would be related to commercial activities. The site which accommodates such commercial facilities could become one of the main attractions in the metropolitan area and could exert a significant influence on the direction and intensity of urban development. The final location decision concerning a HSIPT system terminal in an actual situation, however, has to take into account various economic elements as described in Chapter V. In addition to the transportation costs of areas included in the model and environmental constraints mentioned above, the so-called "project costs," which are composed of such investment elements as direct costs for land acquisition and development, displacement cost, and social costs have to be figured out carefully. These costs, along with the number of demand and transportation costs, have to be taken into account so as to make the 208 final location decision for a HSIPT system terminal, more acceptable and economic. Local Community Impact As a necessary step prior to engaging the third part of the research commitment, the patterns of residential settlement in the Lansing metropolitan area were investiga­ ted. The results of this study verified that there are strong relationships between the accessibilities to attractions such as shopping opportunities, employment opportunities, and other urban functions and services and the patterns of residential settlements in the Lansing metropolitan area. The attraction-accessibility interac­ tion model used for this part of the research undertaking indicated that the population in the townships in the Lansing metropolitan area decrease in proportion to the inverse-square of the distance from the attractions described above. Among these three attractions, however, the urban functions were found to be the ones most strongly related to the patterns of residential settlement in the Lansing metropolitan area. Based on the findings described above, the probable impacts of the addition of a Lansing HSIPT system terminal (on the 147th subnode in Delhi Township) on the rest of the Lansing metropolitan area were investigated. The model used for this part of the research undertaking was the 209 aforementioned, attraction-accessibility interaction model. The probable impacts found are: 1) the likely formation of a new "urban core" around the existing Cities of Lansing, East Lansing and the western half of Delhi Township; and 2) a presumed shift in the direction of urban expansion in the Lansing metropolitan area from east-west to south-north. These findings can be more clearly shown in the following summary: 1. Lansing, East Lansing, and the western half of Delhi Township would tend to coalesce into a densely urbanized core in which most of the major employment and retail centers will be accommodated; 2. St. Johns, Charlotte, and Eaton Rapids would tend to function as regional cores and would serve for local needs; 3. Dewitt, Grand Ledge, Williamston, and Mason would tend to function as local cores, through strongly influenced by the densely urbanized core of Lansing, East Lansing, and the western half of Delhi Township. 4. Among the ten urban centers, Lansing, East Lansing, St. Johns, Charlotte, Eaton Rapids, Dewitt, Grand Ledge, Williamston, Mason, and Delhi (the Lansing HSIPT system terminal site), the most drastic change due to the creation of a Lansing HSIPT system will occur in the City of Mason. Because of its locational proximity to the new terminal, Mason would be absorbed 210 in the Lansing urban area completely. Another community which is likely to have significant impacts from the new system will be Eaton Rapids. At the southern end of a newly developing urban corridor, the role of Eaton Rapids will be intensified. Some of the urban functions now located in Charlotte might shift to Eaton Rapids. The policies and plans necessary to alleviating the probable negative impacts on social, economic, physical, and environmental structures in this case would have to be developed and implemented before the loss became irretrievable. Conclusions In conclusion, this part of the research undertaking verified the utility and workability of the "p-Median" method and the attraction-accessibility interaction model. The "p-Median" method, for instance, successfully introduced objectivity into the location decision process for a HSIPT system terminal site in the Lansing metropolitan area. The attraction-accessibility interaction model predicted the shift of the direction of urban expansion in the Lansing metropolitan area due to the creation of a Lansing HSIPT system terminal. In other words, by adopting the above method and model, the probable conflicts of social, economic, physical, and environmental factors in the Lansing metropolitan area due to the creation of a Lansing 211 HSIPT system terminal could be anticipated, examined, and perhaps reduced in advance of the product. The results of this type of research can be extreme­ ly crucial for both public and private policy decision makers. For public decision makers, the result could be referred to for future action in land management, land use control, public investment, growth management, etc., and for private decision makers, it could help to develop future investment strategies within the area concerned. More importantly, however, the application of this research method will be important to any of the potential sites for a HSIPT system terminal and to the surrounding areas within any region where a HSIPT system is planned or expected. This research undertaking has been predicted on the assumption that a HSIPT system had been authorized for development in the Great Lakes Midwest Region. Applications of the research methods formulated and utilized in this dissertation do produce convincing results and could be important to any community in any region or country where a HSIPT system is planned or expected. The general con­ clusions drawn from the findings of this research undertaking can be summarized as follows: 1. A HSIPT system, as Ogawa mentioned in his study concerning the possible impacts of the Tokaido Shin Kansen on the cities along its route and also as described in this research undertaking, would be a 212 system which joins smaller communities to larger communities, rather than the reverse. This means that the probable development impacts of a HSIPT system will be stronger on smaller communities than on larger communities. Exceptions would be cases where smaller communities are located very close to extremely large communities. In this research, such communities as Gary, Youngstown, and Windsor, which are located very close to Chicago, Pittsburgh, and Detroit, respectively, are cited as the examples of the case described above; 2. The probable impacts of a HSIPT system may not always be stronger on the communities which are directly joined by the system than on the communities not joined by the system. For instance, in this research under­ taking, the probable impacts of a HSIPT system on such local communities as Saginaw, Lexington, Port Huron, Sarnia, and Battle Creek, which would not be joined by the system, were found to be much stronger than the ones on such local communities as Toronto, Milwaukee, Gary, Chicago, Youngstown, and Windsor which are directly joined by the system. It is important to recognize this fact so as not to overestimate or underestimate the probable impacts of a HSIPT system; 3. The direction of urban expansion will shift toward the site designated for a local HSIPT system terminal where 213 various commercial activities would presumably be located. In reality, however, this shift will occur only if the site is located so as to be functionally linked with the existing commercial center of the area (CBD) and if the site is located so as to synchronize effectively with existing transportation systems such as highways, buses, mass transit, and air. If these basic prerequisites were not met the site would be left without sufficient attractiveness for development investment dynamics and inefficient and non-effective dual investments in small local areas would result; 4. The direct impacts of a HSIPT system on existing land uses would be minor because the space necessary for a HSIPT system terminal and trackage right-of-way would be considerably smaller than that necessary for the infrastructure of other transportation systems such as highways and airports. The indirect impacts of a HSIPT system on various land uses are, however, considerably significant. In fact, the creation of such an important transportation facility as a HSIPT system terminal would generate significantly improved accessibility to certain portions of the local area; it would also result in a considerable increase of the developmental potential of the portions in the area concerned. The areas most strongly influenced by the 214 creation of a HSIPT system terminal are, most probably, the areas generally adjacent to the terminal site. The impacts on investment attractiveness decrease in proportion to the distance; as found in this dissertation analysis, impacts decrease in proportion to the inverse square of the distance from the designated terminal site. The developmental potential generated by this improved accessibility is often directed into residential types of land use activity and the result is a massive conversion of irreplaceable, agricultural and forest lands into residential land use. Careful analysis and planning and rigorous public policies and controls would be necessary to preserve such important land resources for support for living environments of desirable quality (i.e. , productive agricultural lands, forest lands, flood plains, and groundwaters). Suggestions for Further Studies As mentioned in the preceding section, this research undertaking was predicted on the assumption that a HSIPT system were to be created in the Great Lakes Midwest Region. In reality, however, the time and place for the eventual implementation of a HSIPT system in the United States are still uncertain. Moreover, whenever the issue of a HSIPT system becomes the subject of 215 discussion, there is one, very basic question that the advocates of a HSIPT system in the United States must always encounter. That is the question: "Could a HSIPT system really be successful in the United States?" It is safe to say that a clear and decisive answer to this question has not yet been developed. Typical counter­ arguments to the creation of a HSIPT system in the United States which HSIPT system planners in the United States have to overcome are: 84 1. on-line population densities in Europe and Japan are much greater than in the U.S. Long-distance trains in Europe connect a series of short-distance corridors, but unlike the U.S. network, the corridors are adjacent . . . Only the Northeast Corridor has on-line population densities comparable to major West European and Japanese routes; 2. travel habits are different for Europeans and Japanese. For several decades, the overwhelming majority of Americans have relied on private transportation. The auto has largely determined our residential living patterns. Decentralization of the urban population has not only caused people to move further out into the suburban rings, but has also allowed them to disperse from the transportation spokes that radiate out from the Central Business Districts; 3. the phenomenon that we have witnessed in the U.S. is now happening in Western Europe and Japan. Rising real incomes have allowed people to desert mass transit and intercity public transport modes . . . It seems clear that the "habit" of reliance on public transportation is one that many travellers find easy to break; 84 National Transportation Policy Study Commission, AMTRAK: AN EXPERIMENT IN RAIL SERVICE, Wash., D.C.: NTPSC, August 1978, pp. 189-190. 216 4. public promotional and subsidization policies overseas have not favoured the air and highway modes at the expense of their nationalized rail systems. This is beginning to change as governments respond to their publics' demand for an improved intercity highway system; 5. the European and Japanese transport environments are characterized by: shorter travel distances between major urban centers, higher per-passengermile air fares, much higher gasoline prices, a less developed highway network, and a rail system which is dedicated more to passenger than to freight services . . . What is surprising is that foreign rail passenger systems are also losing riders and experiencing rising deficits . . . Foreign experience, therefore, is not greatly relevant to the evaluation of AMTRAK. Among these five, the issue of on-line population densities has so far been the strongest. In fact, it could be the hardest one which HSIPT system planners have to answer. For instance, more than 48 million people live along the lines of the two existing Shin Kansens, Tokaido between Tokyo and Osaka, and Sanyo between Osaka and Fukuoka. The combined total length of these two lines is approximately 670 miles persons). (Per mile population is 71,600 The Great Lakes Midwest Region, where a HSIPT system is being assumed in this research undertaking as being scheduled for installation, has approximately 40 million people (based on the population of the forty local communities selected for this research). However, the total length of the HSIPT system planned within the Region is 1,560 miles (based on the highway mileage), which is more than twice as long as the Shin Kansen routes in Japan. 217 Thus, the per mile population in the Great Lakes' case is 25,600/ which is equivalent to approximately 36 percent of the on-line population in the Japanese case. This comparison, however, ignores the fact that the development of the Shin Kansen in Japan has spurred the influx of population into the areas where the service of the Shin Kansen could have been expected or already existed. For instance, in 1960, four years before the Tokaido Shin Kansen between Tokyo and Osaka was in operation, the population on the Shin Kansen route between Tokyo and Fukuoka was 28 million (41,800 persons per mile). During the past two decades, the population along the Shin Kansen has increased by more than 70 percent. Obviously, this 41,8 00 per mile population is still larger than the Great Lakes Region's 25,600 per mile population, but the difference was reduced considerably. This may suggest that the probable impacts of a HSIPT system on population movement may also have to be taken into account as an important aspect of the system if it were planned to be created in any region or in any country. Needless to say, the circumstances in the United States require more careful analysis than those in other nations where existing geographic, demographic, socio­ economic, political, and even cultural systems are better suited to utilizing optimally such a transportation system as the HSIPT. Nevertheless, it could be safe to say that 218 the necessity for undertaking rigorous studies concerning the possible development of a HSIPT system in the United States has significantly increased. For instance, the aforementioned U.S. National Governors' Association expressed strong support for the development of a national rail passenger system that emphasizes high-density corridors: As our entire transportation system faces growing demand, deteriorating infrastructure and tighter fiscal constraints, the need for utilizing each mode to its maximum capacity is apparent. . . . Over the last few years a growing number of states have recognized the need for rail passenger transportation as an integral part of a balanced transportation system. Rail passenger service provides an alternative, especially for medium-sized cities in highly populated corridors of less than 50 0 miles. With today's average air flight over 1000 miles and the average bus trip under 100 miles, passenger rail is ideally suited to provide service to medium-distance markets along corridors throughout the country and it can be developed in a manner to provide integrated travel service with the air and bus modes. To make a HSIPT system an integral part of a balanced national transportation system, continued research in several aspects of high-speed train systems has to be undertaken by system planners in the United States. First, it is necessary to develop transportation demand models which are sufficient to be general; in other words, models have to be developed which can forecast the effects changes, such as increased speed, safety and frequency of □5 The U.S. NGA Committee on Transportation, Commerce, and Technology (1981), p. 1. 219 services on passenger demand. Concerning the limitation of existing demand models, Lave says: 86 Transportation demand models tend to be fragile and limited. They are developed for specific purposes and are unreliable when used more generally. In particular, past models have been deficient in not explaining passenger demand in terms of the attributes of the modes. This means that there is no way to forecast the effect of changes such as increased speed or safety on passenger demand. Furthermore, these models are invariably mode specific and consequently provide no way of looking at total travel time when one mode is changed significantly or a new mode introduced. [underlining, the writer.] Second, once market potentials were established for a HSIPT system in any region in the United States, the optimal HSIPT system network design will be necessary. As mentioned in the Japanese Shin Kansen's case, the disparity in terms of the level of economic development between the communities which have had the services of the Shin Kansen and the communities which have not had such services has been conspicuous. Third, along with analyses concerning optimal HSIPT system networks, studies concerning desirable systems of operation will be necessary. As a specific example, it is necessary to make a thorough feasibility study concerning an exclusive passenger operation or a passengerfreight joint operation. As mentioned earlier, the French and Japanese HSIPT installations which have exclusive and grade— separated rights-of-way have secured safety and 86 Lester Lave, "The Demand for Intercity Passenger Transportation," Journal of Regional Science, Vol. 12, No. 1, 1972, p. 71. 220 speed; however, they have proven to be an extremely costly way to develop a HSIPT system. The British system, which was designed to utilize the existing tracks with freight traffic, on the other hand, was found to be superior in terms of the cost of development. However, the number of grade crossings and severe curves on the existing tracks in the United States would jeopardize the safety of high­ speed operations. Not only the track system design but also the optimal management system for a joint passengerfreight operation should be included in this particular research category. Finally, intensive study concerning socio-economic impacts upon development within the principal HSIPT system regional corridors, at both the regional and local levels will be necessary. As a matter of fact, the probable impacts from the creation of a HSIPT system could be multifaceted. To make a HSIPT system project in the United States have any real meaning, final implementation decisions should be based on the results of the kinds of investigations research recommended above and on rigorous cost-benefit analyses which can assure the economic feasibility of any project. One clear perception about the state-of-the art of HSIPT systems gained from this study is that there is a great paucity of solid, reliable information available; it is a pioneer field for further research— hardly scratched open; indeed, intensive and extensive research needs to be 221 conducted in many areas of this technology. Technological data are substantially ahead of economic, social and behavioral, and political information. It is hoped that this dissertation endeavor, even though limited to a modest scope, can evoke interest among future research scholars, public and quasi-public agencies, and private transportation interests to build up a body of useful knowledge on this highly crucial mode of transportation. APPENDICES APPENDIX I.— Statistical Relationship between the Population Energy of 46 Prefectures and their 22 Socio-Economic Variables in 1968 (Correlation Coefficient). G b Total Prefectural Population Total DID Population Total Population of note than 100,000 cities Population la the Tertiary Industry Prefectural Per Capita Income Amount of Retail Sales Humber of Retail Stores Number of Enterprises Autoovnerahip Average Salary of Labors Number of Banks Number of Rail Passengers Amount of Industrial Output Number of Plants and Factories Amount of Cbnaumed'Electrlclty Number of Hevspaper Subscription Amount of Book Sold Number of Malls Delivered Amount of Water Supplied Number of Physicians Number of Telephones Amount Gas Supplied 1.00 0.25 0.9862 0.9622 1.00 0.50 0.9576 0.9529 1.00 0.75 0.9297 0.9400 1.00 1.00 0.9082 0.9304 1.00 1.75 0.8701 0.9151 0.9687 0.9644 0.9552 0.9481 0.9370 0.9772 0.9774 0.8923 0.9869 0.9800 0.9781 0.7363 0.9343 0.8946 0.9463 0.9126 0.9041 0.9721 0.9714 0.B832 0.9576 0.9624 0.9465 0.9214 0.9553 0.9653 0.8874 0.9637 0.9618 0.9612 0.7233 0.9253 0.9007 0.9571 0.9203 0.8985 0.9641 0.9564 0.8718 0.9602 0.9414 0.9483 0.9301 0.9493 0.9493 0.8746 0.9373 0.9390 0.9383 0.7126 0.9105 0.8993 0.9553 0.9117 0.8839 0.9512 0.9380 0.B514 0.9555 0.9184 0.9416 0.9295 0.9361 0.9361 0.8625 0.9148 0.9191 0.9166 0.7079 0.8973 0.8978 0.9475 0.8961 0.8684 0.9404 0.9230 0.8464 0.9511 0.9006 0.9341 0.9277 0.9096 0.9096 0.8352 0.8691 0.8762 0.8632 0.7119 0.8685 0.8946 0.9277 0.8374 0.8320 0.9180 0.8925 0.8264 0.9441 0.B713 0.9127 0.9235 Source: Etsuo Yamamura and Hlroyukl Maki (1973), p. 165. APPENDIX Ila.— Time-Distance Matrix between 40 Origins and 20 Destinations by Automobile. Unit: Hour Madison Miiuauk Chicago Kalamaz CrandRa BattleC Lansing Jackson AnnAtbo Flint Saginaw PottHur Detroit Toledo Southbe FortWay Lima Indiana Clnclnn Dayton Columbu Canton Akron Clevela MIL CHI KAL CRD LAN FLN DET TLD IND CIN DTK 1.6 0.5 1.8 A.4 4.7 4.8 6.8 5.6 6.3 6.8 7.5 8.2 7.2 6.6 3.5 5.1 6.4 5.4 7.7 6.8 9.4 9.5 9.1 8.7 2.8 1.8 0.5 2.6 3.5 3.1 4.1 3.8 4.5 5.1 5.8 6.5 5.5 4.7 1.8 3.4 4.6 3.7 5.9 7.1 7.2 7.8 7.4 7.0 5.4 4.4 2.6 0.5 1.1 0,5 1.5 1.3 2.0 2.6 3.0 4.0 2.9 2.8 1.4 2.2 3.5 4.7 6.2 5.1 5.5 5.B 5.4 5.1 6.3 4.7 3.5 1.1 0.5 1.4 1.4 2.2 2.7 2.2 2.3 3.6 3.0 3.6 2.5 3.3 4.6 5.7 7.3 6.1 6.3 6.5 6.1 5.9 6.8 5.8 4.1 1.5 1.4 1.0 0.5 0.8 1.3 1.1 1.5 2.5 1.7 2.3 3.3 2.8 4.0 5.2 5.9 5.5 5.0 5.1 4.7 4.5 7.9 6.8 5.1 2.6 2.2 2.1 1.1 1.8 1.1 0.5 0.8 1.4 1.2 2.1 4.3 3.8 3.7 6.2 6.3 5.2 4.8 5.0 4.6 4.3 8.3 7.2 5.5 2.9 3.0 2.3 1.7 1.5 0.8 1.2 1.9 1.2 0.5 1.2 4.5 3.3 2.9 5.7 5.4 4.3 3.9 4.1 3.7 3.5 7.7 6.6 4.7 2.8 3.6 2.3 2.3 1.7 1.0 2.1 2.8 2.4 1.2 0.5 3.1 2.1 1.7 4.5 4.2 3.1 2.7 2.9 2.5 2.3 6.5 5.4 3.7 4.7 5.7 4.2 5.2 6.0 5.5 6.2 6.9 6.9 5.7 4.5 2.8 2.5 3.5 0.5 2.2 2.3 3.6 6.0 6.1 6.4 8.7 7.7 5.9 6.2 7.3 4.9 5.9 5.8 5.2 6.3 7.0 6.6 5.4 4.2 4.7 3.1 2.6 2.2 0.5 1.2 2.2 4.7 4.7 5.0 9.9 10.0 10.2 8.8 9.4 9.1 7.1 7.2 6.2 5.1 5.5 5.4 6.1 6.3 6.1 4.5 5.0 4.8 5.5 5.0 4.7 4.7 4.6 4.2 4.0 3.9 3.4 5.2 4.8 4.6 6.0 5.5 5.3 5.4 5.1 4.8 4.3 3.9 3.7 3.1 2.7 2.5 4.2 4.7 5.6 2.7 3.1 4.3 1.5 1.8 3.1 2.3 3.6 6.1 1.2 2.2 4.7 0.5 1.5 4.0 1.5 0.5 2.6 3.9 2.5 0.5 4.0 2.6 0.5 4.3 2.8 0.8 (continued) COL AKR CLV TNG PIT 9.B 11.1 12.4 8.7 10.1 11.3 7.0 8.3 9.6 5.1 6.4 7.7 5.9 7.2 8.4 4.6 5,9 7.1 4.7 5.8 7.1 4.1 5.5 6.7 3.4 4.8 6.0 4.3 5.7 6.9 5.1 6.4 7.7 4.6 5.9 7.2 3.6 4.8 6.1 2.3 3.5 4.7 5.5 6.5 7.7 4.3 5.3 6.7 3.1 4.1 5.4 6.4 7.4 7.3 5.0 5.6 5.9 4.3 5.0 4.9 2.8 3.4 3.8 1.2 1.0 2.0 0.8 1.0 2.4 0.5 ■ 1.4 2.6 WIN LON TRO CRY 8.5 10.5 13.1 7.4 9.5 12.2 5.8 7.7 10.3 3,0 5.4 7.8 3.1 5.5 7.9 2.4 4.8 7.2 1.9 4.2 6.6 1.6 4.0 6.4 0.9 3.3 5.7 1.3 2.8 5.2 2.1 3.5 5.9 1.3 1.4 3.8 0,2 2.5 4.9 1.4 3.7 6.1 4.7 7.0 9.4 3.4 5.8 8.2 3.0 5.4 7.8 3.9 8.2 10.6 5.6 7.9 10.3 4.5 6.8 9.2 4.1 6.4 8.8 4,3 6.6 6.9 3.9 6.2 6.9 3.6 6.0 6.0 3.9 2.4 1.0 1.9 2.9 2.4 3.4 3.2 3.9 4.5 5.2 5.8 4.7 4.3 1.2 2.7 3.9 3.1 5.3 5.4 6.0 7.2 6.7 6.5 Appendix Ila.— Continued. Unit: Hour CHI KAL GRD LAN FLN DET TLD CIN DTN COL 10.1 8.3 11.3 9.6 7.4 5.8 9.5 7.7 12.2 10.3 12.6 10.8 8.3 6.5 11.1 9.3 12.5 10.7 2.4 1.0 1.9 1.8 4.5 3.2 4.1 3.4 7.7 6.0 10.7 9.0 9.2 7.5 6.4 7.7 3.0 5.4 7.7 8.5 4.0 7.0 8.1 1.9 4.3 5.9 6.0 7.3 7.1 8.8 7.2 8.4 3.1 5.5 7.9 8.6 3.6 7.1 8.2 2.9 5.4 6.7 7.0 8.3 8.5 9.8 5.8 7.1 1.9 4.2 6.6 7.3 2.5 5.8 6.9 3.4 6.7 8.1 8.3 9.1 7.1 9.2 5.7 6.9 1.3 2.8 5.2 5,9 1,5 4.4 5.5 4.5 7.7 9.1 9.3 8.6 6.6 8.1 4.8 6.1 0.2 2.5 4.9 5.6 1.2 4.1 5.2 4.7 7.3 8.7 8.9 7.5 5.5 7.0 3.5 7.4 5.6 4.7 7.3 5.9 1.4 5.9 5.6 3.7 8.2 7.9 6.1 10.6 10.3 6.2 10.2 8.8 2.4 4.6 6.6 5.3 9.8 9.5 o.4 10.6 9.2 4.3 3.1 5.3 6.6 5.5 7.7 8.0 4.3 6.5 8.3 6.3 8.5 6.3 2.5 2.1 4.3 9.1 7.7 5.8 3.8 1.6 5.0 4.9 4.5 6.8 9.2 8.1 5.5 8.4 8.5 5.4 8.8 6.6 8.6 3.2 7.0 2.7 3.4 1.0 1.4 0.5 1.4 3.B 2.4 2.6 1.4 0.5 4.1 3.9 3.6 5.0 6.2 6.4 6.2 6.0 6.9 7.5 8.8 6.9 6.0 5.9 6.5 6.7 4.8 3.9 3.8 4.4 5.1 5,3 4.6 6.0 7.2 8.0 6.0 5.1 5.0 5.6 7.1 5.7 4.3 4.2 4.8 6.0 6.7 6.5 7.7 8.9 9.0 9.1 8.0 1C.1 11.3 7.9 10.4 10.1 11.5 11.6 9.8 10.8 10.4 11.7 11.6 4.6 7,1 7.4 8.0 8.3 5.5 3.0 2.0 1.9 2.6 3.8 6.3 6.6 7.2 7.5 MIL Youngst Fittsbu Windsor London Toronto Buffalo Sarnia Hamil to Niagara Gary Rockfor Peoria Davenpo Loulsvi Erie Lexingt Note: IND AKR CLV YNG PIT WIN LON TR0 GRY 5.0 6.9 5.9 7.7 6.2 7.5 6.5 8.9 0.5 3.4 4,2 4.8 2.4 0.5 2.4 7.2 4.8 2.4 0.5 9.6 5.5 3.1 2.1 10.3 1.3 1.4 3.7 5.8 4.0 1.6 0.9 8.8 5.1 2.7 1.6 9.9 4.9 7.2 9.6 0.5 7.4 9.5 12.1 2.4 8.6 10.9 13.5 3.8 9.1 11.1 13.7 4.0 7.6 10.0 12.3 5.4 5.6 5.6 5.0 8.5 7.1 9.5 11.9 6.9 The time-distance between each node (SMSAs or CMAs) is calculated as follows: Time-distance (hour) ■ the highway mileage between nodes (miles)/ aasuned average speed of automobile (50 mph) For instance, the time-distance between Youngstown and Milwaukee - 501/50 - 10.02 -- 10.1 (hours) APPENDIX lib.— Time-Distance Matrix between 40 Origins and 20 Destinations by the HSIPT System. Unit: Hour Madison Milvauk Chicago K&lamaz GrandRa BattleC Lansing Jackson AnnArbo Flint Saginaw PortHur Detroit Toledo Southbe FortWay Lima Indiana Cincinn Dayton Columbu Canton Akron Clevela MIL CHI KAL GRD LAN FLN DET TLD IND CIN DTK 1.5 0.5 1.6 2.2 2.6 2.7 3.1 3.4 4.1 3.5 4.2 8.2 3.9 4.4 2.6 4.1 6.4 2.6 3.5 3.9 4.4 9.5 9.1 8.7 2.7 1.8 0.5 1.5 1.9 2.0 2.4 2.8 3.4 2.8 3.6 4.2 3.2 3.7 1.8 3.4 4.6 2.0 2.8 3.2 3.8 7.8 7.4 4.6 3.7 2.2 1.5 0.5 1.1 0.5 1.5 1.3 2.0 1.8 2.6 3.2 2.3 2.7 1.4 3.9 4.4 2.9 3.8 4.2 3.8 4.2 3.9 3.6 4.1 2.6 1.9 1.1 0.5 1.4 1.4 1.8 2.3 1.4 2.2 2.8 1.9 2.3 2.3 3.2 4.0 3.3 4.1 3.9 3.4 3.9 3.5 3.2 4.6 3.1 2.4 1.5 1.4 1.0 0.5 0.8 1.3 l.l 1.5 2.3 1.7 1.8 2.8 3.7 3.5 3.8 3.8 3.4 2.9 3.4 3.0 2.7 7.9 3.5 2.8 1.8 1.4 2.1 1.1 1.8 1.1 0.5 0.8 1.4 1.2 1.4 3.2 3.5 3.1 4.3 3.4 3.0 2.5 3.0 2.6 2.3 8.3 3.9 3.2 2.3 1.9 2.4 1.7 1.5 0.8 1.2 1.9 1.2 0.5 1.2 3.6 3.1 2.6 3.9 3.0 2.6 2.0 2.6 2.1 1.9 7.7 4.4 3.7 2.7 2.3 2.8 1.8 1.7 1.0 1.4 2.2 2.1 1.2 0.5 4.1 2.1 1.7 3.4 2.6 2.2 1.6 2.1 1.7 1.4 4.1 2.6 2.0 2.9 3.3 3.4 3.8 4.2 4.4 4.3 6.9 6.9 3.9 3.4 3.3 2.5 3.2 0.5 1.4 1.8 2.4 6.0 4.5 4.3 8.7 3.5 2.8 3.8 4.1 4.3 3.8 4.2 3.5 3.4 4.2 4.1 3.0 2.6 4.2 4,6 2.4 1.4 0.5 1.2 1.5 4.1 3.7 3.4 9.9 10.0 10.2 3.9 4.4 9.1 3.2 3.8 6.2 4.2 3.8 3.9 3.9 3.4 3.5 4.4 3.9 4.0 3.4 2.9 3.0 3.8 3.2 3.3 3.1 2.5 2.6 3.0 2.5 2.6 3.8 3.2 3.3 3.7 3.1 3.3 2.6 2.0 2.1 2.1 1.6 1.7 4.6 4.7 5.6 4.2 3.6 3.8 1.5 1.8 3.3 1.8 2.4 4.5 1.2 1.5 3.7 0.5 1.5 3.3 1.5 0.5 2.7 3.7 3.2 0.5 3.3 2.8 0.5 3,0 2.4 0.8 (continued) COL AKR CLV TOG PIT 9.8 11.1 12.4 8.7 10.1 11.3 4.6 8.3 9.6 3.6 4.3 7.7 3.2 3.9 4.4 3.7 4.3 7.1 2.7 3.3 3.9 3.0 3.7 4.2 2.3 3.0 3.5 2.3 3.0 3.5 3.0 3.7 4.2 3.0 3.6 4.1 1.9 2.5 3.0 1.4 2.1 2.6 5.5 6.5 7.7 3.5 4.1 6.7 3.0 3.7 4.2 4.3 7.4 7.3 3.4 4.1 4.6 3.0 3.7 4.2 2.4 3.1 3.6 1.2 1.0 2.0 0.8 1.0 1.4 0.5 1.4 1.7 WIN LON TRO GRY 8.5 10.5 13.1 4.5 9.5 12.2 3.8 7.7 10.3 2.8 3.7 4.6 2.4 3.3 4.2 2.9 3.8 7.2 1.9 2.8 3.7 1.6 3.0 3.9 0.9 2.3 3.2 1.3 2.7 3.6 2.1 2.7 3.6 1.3 1.4 2.8 0.2 1.6 2.5 1.4 2.5 3.4 4.2 7.0 9.4 3.6 4.5 8.2 3.2 4.1 7.8 4.4 8.2 10.6 3.6 4.9 10.3 3.1 4.0 9.2 2.6 3.5 4.4 3.1 4.1 6.9 2.7 3.6 4.5 2.4 3,3 4.2 3.0 1.4 1.0 1.9 1.7 1.8 2.2 2.5 3.1 2.6 3.3 4.0 3.0 3.5 1.2 3.5 3.9 2.2 3.0 3.5 4.0 7.2 6.7 4.3 Appendix lib.— Continued. Unit: Hour 10.1 KAL CRD LAM FLU DET TLO CIH DTN COL 8.3 9.6 3.8 7.7 10.3 10.8 4.2 9.3 10.7 1.0 1.8 3.2 3.4 4.2 9.0 4.4 4.3 7.7 2.8 3.7 4.6 8.5 3.3 7.0 8.1 1.9 3.3 4.6 6.0 7.3 7.1 8.8 3.9 4.4 2.4 3.3 4.2 8.6 2.9 7.1 8.2 1.7 3.7 6.7 7.0 8.3 8.5 9.8 3.3 3.9 1.9 2.8 3.7 7.3 2.4 4.4 6.9 2.2 4.2 8.1 8.3 9.1 7.1 9.2 3.0 3.5 1.3 2.4 3.6 5.9 1.5 4.0 5.5 2.6 4.6 9.1 9.3 8.6 4.3 8.1 2.5 3.0 0.2 2.0 2.5 5.6 1.2 3.6 4.5 3.0 7.3 8.7 8.9 7.5 3.8 4.6 2.1 7.4 4.1 2.6 7.3 4.6 1.4 4.4 3.6 2.5 8.2 4.5 3.4 10.6 10.3 6.2 10.2 8.8 2.1 4.6 4.2 4.0 9.8 9.5 6.4 10.6 9.2 3.5 2.2 3.0 6.6 3.7 4.6 8.0 4.3 6.5 8.3 6.3 8.5 4.6 3.4 2.1 3.4 9.1 7.7 4.1 2.9 1.6 3.7 4.2 3.1 4.0 9.2 8.1 3.7 8.4 8.5 3.5 8.8 6.6 8.6 3.0 7.0 2.5 3.1 1.0 1.4 0.5 1.4 3.6 1.4 1.7 1.4 0.5 2.6 2.7 2.4 3.1 3.6 3.5 3.6 3.3 4.0 4.5 4.4 4.5 4.2 5.9 6.5 6.7 4.6 3.9 3.8 4.4 3.2 3.3 3.0 3.7 4.2 8.0 6.0 5.1 5.0 5.6 7.1 5.7 4.3 4.2 4.8 4.0 4.6 4.3 7.7 8.9 9.0 9.1 8.0 10.1 11.3 7,9 10.4 10.1 11.5 11.6 9.a 10.8 10.4 11.7 11.6 3.5 7.1 7.4 3.0 8.3 5.5 2.8 2.0 1.9 2.9 3.1 6.3 6.6 7.2 7.5 IHD AKR CLV YHG prr CHI HIM LON TRO CRY Youngst Plttsbu Windsor London Toronto Buffalo Sarnia Hamllto Niagara Cary Rockfor Peoria Davenpo Louisvl Erie Lexlngt A.5 9.5 12.2 12*6 8.3 11.1 12.5 1.4 1.9 4.3 4.6 7.7 10.7 9.2 Note: The time-distance between each node (SMSAs or CMAa) by the HSIPT system Is calculated as follows: 11:3 For instance, the time-distance between Chicago and Flint. 3.1 4.0 5.9 7.7 3.6 4.5 6.5 8.9 0.5 1.4 2.4 3.5 1.4 0,5 1.4 4.5 2.4 1.4 0.5 9.6 4.4 3.5 2.1 10.3 1.3 1.4 2.8 4.0 3.0 1.6 0.9 8.8 3.9 3.0 1.6 9.9 3.5 4.4 7.6 0.5 7.4 9.5 12.1 2.5 8.8 10.9 13.5 3.9 9.1 11.1 13.7 4.2 7.6 10.0 12.3 4.5 4.4 5.6 5.0 8.5 7.1 9.5 11.9 4.4 In ternal traffic friction (0.5 hours) - Internal traffic friction, i.e., time to get to the terminal (0.5 hours) + highway diatance/110 oph + highway distance/ Average speed of the HSIPT system (252/110 ■ 2.3 hours) “ 2.8 hours. A6 APPENDIX III.— Population Potential at each SMSA Based on the Time-Distance by Automobile. Unit: Person/Hour Population (1 .000s) E - 0.5 E - 1.0 E - 1.5 290 1,404 6,975 272 342 363 633 280 362 1,111 867 267 1,367 853 1,018 210 763 2,064 679 394 537 2,401 264 1,349 4,435 36 220 509 234 259 424 142 539 258 259 79 286 2,628 499 303 12,199,84 14,631.69 19,561.26 13,650.09 11,677.76 11,291.92 17,321.86 15,606.17 14,991.04 14,362.60 11,727.83 11,632.03 14,271.04 14,466.05 14,733,74 15,162.18 17,186.89 16,042.06 15,573.03 15,046.12 14,661.97 14,357.22 12,629.63 11,904.49 18,604.82 15,127.32 14,209.02 15,986.93 17,525.13 15,966.09 15,643.63 15,731.69 14,506.98 15,433.77 21,860.34 15,202.74 13,334.02 13,446.18 13,193.02 12,111.61 5,720.24 9,448.72 18,641.16 7,362.77 4,999.39 4,671.07 12,578.97 9,060.15 7,914.16 8,300.64 4,980.60 4,978.43 8,605.31 8.506.57 8,705.00 8,232.35 11,490.12 11,062.94 10,083.03 9,193.22 8,829.90 9,618.29 5,897.59 5,243.38 16,165.12 8,953.05 7,622.92 10,173.66 12,456.74 9,537.96 9,362.15 9,126.21 8,023.00 8,B36.02 28,462.52 9,008.22 6,772.24 8,932.05 7,181.33 5,577.51 2,999.85 7,934.95 22,321.20 4,487.00 2,277.97 2,059.18 10,853.21 5,668.86 4,273.62 6,151.31 2,260.09 2,345.48 6,947.79 6,307.65 6,434.21 4,674.93 8,908.41 9,952.59 8,144.11 6,870.39 6,529.06 9,097.90 2,985.92 2,504.12 18,772.90 6,067.88 4,589.38 7,667.59 10,440.74 6,254.45 6,436.87 5,826.65 5,232.96 5,591.58 53,399.96 6,090.69 3,993.70 8,667.67 4,902.69 2,897.18 1,729.71 8,212.20 29,562.93 2,976.87 1,094.26 959.17 10,560.84 3,779.05 2,352.56 5,993.42 1,104.63 1,239.43 7,301.01 5,917.93 6,081.60 2,777.78 8,021.05 11,061.63 7,942.11 6,229.02 5,809.05 10,821.42 1,633.43 1,294.20 26,268.66 4,595.85 3,119.57 6 j755.78 9,886.56 4,432.91 5,182.50 4,227.40 4,259.82 4,036.39 113,704.52 4,594.16 2,882.59 11,091.74 4,069.60 1,697.90 Correlation Coefficient 0.358 0.413 0.333 0.134 SMSA 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 3S 36 37 38 39 40 Madison Milwaukee Chicago Roekford Peoria Davenport Gary Southbend Fort Wayne Indianapolis Louisville Lexington Cincinnati Dayton Columbus Lima Toledo Cleveland Akron Canton Youngstown Pittsburgh Erie Buffaro Detroit Port Huron Saginaw Flint Ann Arbor Jackson Lansing Battle Creek Grand Rapids Kalamazoo Windsor Sarnia London Toronto Hamilton Niagara Falls E - 2.0 A7 APPENDIX IV.— Population Potential at each SMSA Based on the Time—Distance by the HSIPT System (b = 1.0) Unit: Person/Hour Population SMSA 1 2 3 4 5 6 7 a 9 10 11 12 13 14 IS 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 ( 1 ,0 0 0 b ) Madison Milwaukee Chicago Rockford Peoria Davenport Gary Southbend Fort Wayne Indianapolis Louisville Lexington Cincinnati Dayton Columbus Lima Toledo Cleveland Akron Canton Youngstown Pittsburgh Erie Buffalo Detroit Port Huron Saginaw Flint Ann Arbor Jackson Lansing Battle Creek Grand Rapids Kalamazoo Windsor Sarnia London Toronto Hamilton Niagara Falls 290 1,404 6,975 272 342 363 633 280 362 1,111 867 267 1,387 853 1,018 210 763 2.064 679 394 537 2,401 264 1,349 4,435 36 220 509 234 259 424 142 539 258 259 79 286 2,628 499 303 b - 1.0 6,367.98 11,484.24 20,938.79 7,794.47 5,049.24 4,647.72 15,212.20 9,652.98 8,194.51 12,505.88 5,672.18 6,456.93 12,831.07 12,045.11 13,163.72 9,043.45 15,477.33 15,112.94 13,226.85 10,836.76 10,571.39 11,908.94 6,447.23 5,265.22 20,570.82 11,293.19 10,410.39 14,355.34 15,145.94 12,035.18 13,149.42 11,606.64 13,B61.91 13,729.19 31,577.54 11,287.27 10,172.53 10,810.08 7,534.73 5,771.46 A8 APPENDIX V.— Population Energy (Energy of Interchange) at each SMSA Based on the Time-Distance by Automobile. Unit: Square-Person/Hour SMSA 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Madison Milwaukee Chicago Rockford Peoria Davenport Gary Southhend Fort Wayne Indianapolis Louisville Lexington Cincinnati Dayton Columbus Lima Toledo Cleveland Akron Canton Youngstown Pittsburgh Erie Buffalo Detroit Fort Huron Saginaw Flint Ann Arbor Jackson Lansing Battle Creek Grand Rapids Kalamazoo Windsor Sarnia London Toronto Hamilton Niagara Falls b - 0.5 290 1,404 6,975 272 342 363 633 280 362 1,111 867 267 1,387 853 1,018 210 763 2,064 679 394 537 2,401 264 1,349 4,435 36 220 509 234 259 424 142 539 258 259 79 286 2,628 499 303 3,537,954.9 17,755,178.4 67,637,409.9 3,718,824,6 3,993,794.9 4,098,968.0 10,398,080.5 4,369,727.3 5,426,755.1 14,211,255,3 10,168,026.8 3,105,752.3 17,073,309.3 11,310,543.2 13,533,359.0 3,184,058.9 12,290,285.1 27,086,132.1 9,922,076.2 5,928,170.5 7,465,661.7 26,319,022.7 3,334,222.3 16,059,157.2 54,695,874.6 544,583.5 3,125,985.2 7,770,950.2 4,100,881.0 4,082,186.1 6,378,655.4 2,239,899.9 7,408,404.8 3,887,776.4 5,566,960.3 1,201,016.3 3,697,853.7 25,569,468.8 6,583,315.8 3,669,816.9 Correlation Coefficient 0,989 b - 1.0 b - 1.5 b - 2.0 1,658,870.1 501,616.2 869,957.9 9,323,571.2 5,565,224.4 3,645,066.1 32,720,827.3 18,085,607.0 11,598,932.6 2,002,673.4 1,220,463.5 809,708.7 374,237.3 1.709,790.7 779,064.9 1,695,598.8 747,482.0 348,180.0 7,161,109.3 5,736,761.7 5,082,255.9 2,536,841.3 1,587,279.5 1,058,133.6 2,864,924.8 1,547,056.2 851,626.8 6,753,371.9 3,342,917.3 1,721.411.1 957,754.4 4,318,181.4 1,959,500.4 330,927.5 1,329,239.7 626,243.3 8,088,031.7 4,195,338.0 2,431,426.8 5,800,887.0 3,322,440.5 2,137,559.9 6,789,038.9 3,618,855.9 2,045,773.0 583,333.7 1,723,794.0 981,734.8 7,602,623.2 5,150,496.5 3,791,381.7 14,313,725.1 8,492,774.4 5,790,823.1 5,924,298.4 4,225,829.7 3,548,527.6 3,622,127.6 2,706,932.6 2,454,235.2 4,164,916.7 2,690,474.1 1,965,986.4 11,563,901.3 5,583,747.4 2,923,027.0 431,226.0 1,556,964.8 788,282.5 1,745,882.3 7,073,314.4 3,378,061.4 32,353,872.4 27,624,830.4 37,824,598.2 165,450.6 323,309.9 218,443.8 686,306.2 1,677,042.8 1,009,663.6 4,660,230.4 3,170,013.1 2,402,370.6 2,914,876.1 2,443,133.3 2,313,455.2 2,428,405.2 1,586,757.4 1,134,869.6 3,609,999.4 2,220,751.0 1,478,274.1 600,291.2 1,295,922.0 827,383.7 3,743,355.7 1,998,847.9 1,133,957.3 775,132.0 2,146,564.2 1,254,355.5 7,237,629.7 13,640,856.2 29,181,146.5 362,938.4 711,649.1 481,164.7 497,237.6 1,773,267.4 910,843.5 1,523,563.3 9,660,665.7 3,770,028.1 3,583,485.3 2,446,442.2 2,030,731.1 514,463.0 1,689,986.8 877,844.2 0.952 0.740 0.503 A9 APPENDIX VI.— Population Energy (Energy of Interchange) at each SMSA Based on the Time-Distance by the HSIPT System (b = 0.5). Unit: Square-Person/Hour SMSA 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Population (1,000s) Madlaon Milwaukee Chicago Rockford Peoria Davenport Gary Souchbend Fort Wayne Indianapolis Louisville Lexington Cincinnati Dayton Columbus Lima Toledo Cleveland Akron Canton Youngstown Pittsburgh Erie Buffalo Detroit Port Huron Saginaw Flint Ann Arbor Jackson Lansing Battle Creek Grand Rapids Kalamazoo Windsor Sarnia London Toronto Hamilton Niagara Falls 290 1,404 6,975 272 342 363 633 280 362 1,111 867 267 1,387 853 1,018 210 763 2,064 679 394 537 2,401 264 1,349 4,435 36 220 509 234 259 424 142 539 258 259 79 286 2,628 499 303 b - 0.5 3,708,646.9 20,657,337.3 82,882,288.5 3,842,294.2 4,011,809.0 4,090,235.8 11,878,748.0 4,524,736.8 5,529,078.0 18,127,095.9 10,835,327.6 3,546,304.3 22,534,584.6 14,249,929.6 17,687,S45.2 3,335,655.7 14,798,779.5 34,318,007.0 11,640,044.9 6,355,912.2 8,333,870.1 31,212,224.0 3,486,381.7 16,092,508.1 72,499,582.7 630,522.0 3,761,444.0 9,738,580.5 4,700,002.3 4,706,099.8 7,877,121.3 2,524,004.6 10,123,928.3 4,679,902.0 6,336,323.4 1,385,521.0 4,518,069.0 30,313,974.7 6,757,707.6 3,733,657.5 A10 VII.— The 192 Nodal Accessibilities to Five Major Shopping Opportunities in the Lansing Metropolitan Area. Ai 1 2 3 4 5 6 7 B 9 10 11 12 13 14 15 16 17 IB 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 47282.B 49235.2 49235.2 51454.8 5 1 4 5 4 .B 54009.8 54009.8 56995.8 55836.2 57512.7 59131.8 61142.3 55935.7 53659.8 59250.7 56562.8 51454.B 54009.S 54009.8 56995.8 56995.8 60552.9 60552.9 64896.8 63097.7 65571.8 68000.4 71152.6 63244.1 60000.6 68188.B 64163.1 56995.8 60552.9 60552,9 64896.8 64896.8 70384.1 70384,1 77667.7 74286.7 78505.0 82782,1 88867.0 74545.4 69352.2 83177.2 76086.9 m 2 j-1 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 EJ 1 - 1 ,, ...192; j 64896.8 70384.1 70384.1 77667.7 77667.7 B8162.9 88162.9 106242.0 95261.3 105258.8 116788.8 138721.0 95992.5 85363.6 118840.8 99472.1 56995.8 60552.9 54415,7 57458.7 64896.8 70384.1 61087.5 65523,9 77667.7 88162.9 71134,0 78586.7 106242.0 143417.7 89326.4 107783.5 51814.6 54415.7 49557,0 51814,6 57458,7 61087.5 54415.7 57458.7 65523.9 71134.0 61087.5 65523.9 78586.7 89326.4 71134.0 78586.7 (continued) 97 98 99 10 0 101 10 2 103 104 105 106 107 108 109 no 111 112 113 11 4 115 1 16 1 17 118 1 19 120 12 1 122 123 124 125 126 127 128 129 13 0 131 132 133 134 135 136 137 138 139 140 141 142 143 14 4 47572.8 49557.0 45810.6 47572.8 . 51814,6 54415.7 49557,0 51814.6 57458.7 61087.5 54415.7 57458.7 65523.9 71134.0 61087.5 65523.9 44231.7 45810.6 42806.2 44231 .7 47572.8 49557.0 45810,6 47572.8 51814.6 54415.7 49557.0 51814.6 57458.7 61087.5 54415.7 57458.7 164613.9 21B 4S2.7 118975.2 142200.5 169835.3 125941.7 125941.7 116692.1 96598.4 85363.6 92855.7 81930.0 76086.9 69352.2 73312.7 67101.7 k " 0.5. 145 146 147 148 149 150 151 152 153 15 4 155 156 157 158 159 16 0 161 16 2 .163 164 16 5 166 56 7 168 169 170 171 173 17 3 174 175 176 177 17B 179 180 181 182 183 184 185 18 6 187 IB S 189 190 191 192 96802.8 107445.2 83945.6 90408,5 99472.1 92464.5 85363,6 79566.5 83063.9 73 901 .1 73901 ,1 67475.2 67475,2 62566.0 62566.0 58631.6 75205.6 79668.4 68750.2 72071.5 76086.9 71538.6 69352.2 65704.6 87475.2 62566.0 6 7 5 6 6 *0 58631.6 58631.6 5537^ .8 55376.8 52671 .3 63724.8 66321.7 59866.5 61769,4 64163.1 61164,0 60000.6 57481.7 58631.6 55376.8 55376,8 52621.3 52621.3 50246.9 50246,9 48171.8 All VII.— Continued. 1 2 3 4 5 6 7 e 9 10 11 12 13 14 15 16 17 18 1? 20 21 22 23 24 25 26 27 28 29 30 31 3? 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 7599.7 8243.9 8243.9 9008.9 9008.9 9933.0 9933.0 11072.7 10596.5 11248.9 11890.6 12723.0 10634.3 9784,4 11939.1 10876.8 9008.9 9933.0 9933.0 11072.7 11072.7 12515.6 12515.6 14406.3 13549.2 14648.8 15753.8 17276.5 13614.1 12247.0 15846.3 14018.3 11072.7 12515.6 12515.6 14406.3 14406.3 17003.8 17003.8 20833.6 18833.6 21087.4 23457.4 27152.8 18977.9 16400.6 23717.2 19786.2 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 02 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = i 14406.3 17003.8 17003,8 20833.6 20833.6 27207,4 27207.4 41252.8 31252.8 38495.6 47845.6 69041.7 31852.8 25010.6 50166.7 34277.8 11072.7 12515.6 10068.6 11234.3 14406.3 17003.B 12711.6 14648.6 20833.6 27207.4 17311.7 21237.8 41252.8 85345.6 27761.7 42061.1 9124.3 10068.6 0343.3 9124.3 11234.3 12711.6 10068,6 11234.3 14648.8 17311.7 12711.6 14648.8 21237.8 27761.7 17311,7 21237.8 {continued) 97 98 99 100 1*01 102 103 104 1 05 1 06 107 108 109 110 111 112 113 114 115 1 16 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 13 4 135 1 36 137 138 139 140 141 142 143 1 44 7686 ,3 8343.3 7125i8 7686.3 9124.3 10068.6 8343.3 9124.3 11234.3 12711.6 10068.6 11234.3 14648.8 17311.7 12711.6 14648.8 6641.9 7125.8 6219.8 6641,9 7686.3 8343.3 7125.8 7686.3 9124.3 10068.6 8343.3 9124,3 11234.3 12711.6 10068.6 11234.3 100041.7 183600.0 49138.9 71466.7 110383.3 56633,3 56633.3 58527.8 32254.4 25010.6 31065.6 23463.5 197B6.2 16400.6 18544.4 15443.8 145 146 147 148 149 150 151 152 153 154 155 156 157 15 8 159 160 161 162 163 16 4 165 166 1 67 168 16 9 170 171 1 72 17 3 17 4 175 17 6 177 178 179 180 18 1 182 183 184 185 186 187 188 18 9 190 191 19 2 32061.1 397B8.9 24011 .7 27961. 1 34277.8 31477.2 25010.6 7 7 2 1 1 *2 24433.5 18948.6 18940,6 15663.9 15663.9 13408.4 13408.4 11744.3 19237.8 21641.7 16061.7 17680.6 19786.2 17693.9 16400.6 14826.6 15663.9 13408.4 13408.4 11744,3 11744.3 10458.9 10458.9 9432.9 13791.7 14956.7 12086.6 12965.5 14018.3 12801.3 12247.0 11281.0 11744.3 10458.9 10458.9 9432.9 9432.9 8593.6 8593.6 7893.5 A.12 Appendix VII.— Continued. (continued) 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 13 4 135 136 137 138 139 140 141 142 143 144 1243.9 1407.4 1109.9 1243.9 1610.5 1866.4 1407.4 1610.5 2204.6 2657.8 1868,4 2204.6 3296.5 4253,8 2657.8 3296.5 998.5 1109.9 904 . 7 998.5 1243.9 1407.4 1109.9 1243.9 1610.5 1860.4 1407.4 1610.5 2204.6 2657,8 1868.4 2204.6 66393.6 166876.8 20850.4 37194.7 80717.1 26734.9 26734,9 39173.2 10966.9 7412.4 11217.0 6965.2 5184.1 3899. 1 4783.3 3590.9 145 14(4 147 148 149 150 151 157 153 154 155 156 159 150 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 170 179 100 1 81 182 1 071 9. <4 14954.6 6907.6 8719.1 12055. 11934. 7412. 6464• 7588. 4991. 4991, 3696, 3696. 2905. 2905. 2371. 4936. 5909. 3760. 4353. 5184,1 4476.0 3899.1 3393.9 3696.5 2905.8 2905.8 2371.6 2371.6 1987,6 1907.6 1699.2 2909.6 3382.0 2451.3 2727.0 3074.9 2706.1 hr 3226.1 4158.0 4158.8 5695.0 5695.0 8683.4 0683.4 17394.2 10400.6 14377.8 20273.5 35914.7 10773.2 7412.4 22212•4 12053.2 2162.2 2603.9 1860.4 2204.6 3226.1 4158.8 2657.8 3296.5 5695.0 8683.4 4253.8 5828.5 17394.2 62211.6 8881.9 17713.2 1610,5 1868.4 1407.4 1610.5 2204.6 2657.8 1868.4 2204.6 3296.5 4253.8 2657.8 3296.5 5828.5 8881.9 4253.8 5628.5 o -o>cn n raoi -a^(c 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 01 02 83 84 85 86 07 00 89 90 91 92 93 94 95 96 t h 1224.5 1384.3 1384.3 1582.7 1502.7 1834.4 1834.4 2162.2 2015.3 2206.3 2397.4 2656.6 2026.4 1787.7 2412.6 2096.8 1582.7 1034.4 1834.4 2162.2 2162.2 2603.9 2603.9 3226.1 2919.2 3287.1 3665.5 4219.7 2941.4 2507.6 3700.6 3074.9 2162.2 2603.9 2603,9 3226.1 3226.1 4158.8 4158.0 5695,0 4802,9 5711.3 6704,1 0400.1 4865.1 3899.1 6835.5 5184.1 w 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 20 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 40 k = 1.5. 1 8 3 2 5 0 7 . 6 184 185 186 187 1 88 189 190 191 192 2230.3 2371,6 1987,6 1987.6 1699,2 1699.2 1475.6 1475,6 1299.7 A13 ii l 2 3 4 5 6 7 8 9 10 U 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 A6 47 48 VII.— Continued. 197.8 233.1 233.1 279.0 279.0 340.2 340.2 424.4 384. 1 433.9 484.6 556.5 387.0 327.3 488. 9 405.2 279.0 340.2 340.2 424.4 424.4 545.3 545.3 728.8 630.9 740.6 856.3 1036.3 637.8 515.0 868.4 677.1 424.4 545.3 545.3 728.8 728.8 1029.9 1029.9 1587.0 1231.4 1558.5 1931.2 2627.4 1255.7 931.7 1990.8 1368.0 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 2.0. 728.8 1029.9 1029.9 1587.0 1587.0 2868.7 2868.7 7952.4 3507.9 5465.6 8892.0 19299.3 3712.6 2220.7 10307.9 4318.8 424.4 545. 3 347.7 434.3 728.8 1029.9 558.5 747.0 1587,0 2868.7 1055.9 1626.3 7952.4 52642.0 2932.0 8064.7 284.9 347.7 237.9 284.9 434.3 558 .5 347.7 434.3 747.0 1055.9 558.5 747.0 1626.3 2932.0 1055.9 1626.3 97 98 99 10 0 10 1 102 103 104 105 106 107 108 109 1 10 111 1 1.2 113 114 115 1 1.6 1 17 1 18 119 120 121 122 123 1 24 125 126 127 128 129 130 131 132 133 134 135 136 137 1 38 1 39 140 141 142 143 14 4 (continued) 201 . 6 237.9 173. 1 201 . 6 284.9 347. 7 237.9 284.9 434.3 558.5 347.7 434. 3 747.0 1055.9 558.5 747,0 150.3 173.1 131 . 7 150.3 201 .6 237,9 173.1 201 . 6 284.9 347.7 237.9 284.9 434.3 558.5 347.7 434,3 48243.7 158498.1 9121.9 19905.6 6530B .3 13181.9 13181.9 32610.5 3792.5 2220.7 4414 .6 2153.7 1368.0 931.7 1260.8 850.1 145 146 147 148 149 150 151 .152 153 154 155 156 .157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 IBS 186 187 188 189 190 191 192 A14 Appendix VII.— Continued. J. 2 3 4 rj 6 7 8 9 10 11 12 13 1A 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 32.0 39.4 39.4 49.3 49.3 63.3 63.3 83.7 73.3 85.5 98.2 116.9 74.1 60.0 99.3 78.5 49.3 63 .3 63.3 03.7 83.7 115.0 115,0 166.1 136.7 167.5 200.8 255,8 138,8 106, 1 204.7 149.6 83.7 115.0 115.0 166. 1 166. 1 258.2 258.2 450,9 317.3 428. 1 560.4 029.7 326.3 223.7 505,7 363.4 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 2.5. 166. 1 258.2 258.2 450.9 450.9 980 .5 980.5 3900,1 1198.5 2108 .0 4041.0 10610.8 1302.8 672.1 4990.0 1574.5 83.7 115.0 64.9 85.9 166. 1 258.2 118.0 170.5 450.9 980.5 265.0 461.7 3900.1 48530.7 999.5 3937,2 50.5 64.9 40.3 50.5 85.9 118.0 64.9 B5.9 170.5 265.0 118.0 170.5 461 . 7 999.5 265, 0 461.7 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 11 4 115 1 16 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 14 4 (continued) 32.7 40.3 27.0 32.7 50.5 64.9 40.3 50.5 85.9 118.0 64.9 85.9 170,5 265.0 118.0 170.5 22.7 27.0 19.2 22.7 32 . 7 40.3 27.0 32. 7 50.5 64.9 40.3 50.5 85.9 118.0 64,9 85.9 38226.6 154142.5 4127.4 10802.5 57052.9 6745.0 6745.0 30344.5 1332.2 672.1 1890.1 695.7 363.4 223.7 340.2 203.8 14 5 14 6 14 7 1 48 149 15 0 151 152 153 154 155 1 56 157 158 159 160 161 162 1 63 1 64 1 65 166 167 16 8 1 69 170 171 17? 173 1 74 175 176 177 178 1 79 1.80 101 182 183 184 185 186 187 IBS 189 190 191 192 1235.7 2194.4 579.4 866 • 9 1574.5 2419,1 672 . 1 635. 1 8B6, 3 38.1 . 2 381. . 2 217.9 217.9 141 . 7 141.7 99. 4 32S .2 447. 1 207. 5 266 . 6 363 . 4 310. 1 223. 7 186.0 217. 9 141.7 141.7 99.4 99.4 73. 3 73. 3 36,0 141.1 174 . 2 101 . 2 121 . 4 149.6 125. 1 106. 1 89.3 99.4 73,3 73 • 3 56.0 56.0 44 . 1 44 . 1 35. 4 A15 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 97 98 99 1 00 101 102 103 10 4 105 10 6 107 10 8 109 110 111 112 113 114 115 116 117 118 119 120 121 1 22 123 1 24 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 5« 5 6.8 4.2 5.3 9.0 12.2 6.8 9.0 17". 1 25. 1 12.2 17.1 39.2 67.2 25.1 39.2 3.4 4.2 2.8 3.4 5.3 6.8 4.2 5.3 9.0 12.2 6.8 9.0 17.1 25. 1 12.2 17.1 32614.5 151811.2 1935.0 6044.1 52527.9 3557.4 3557.4 29548.4 474.7 205.3 869,3 234.8 97.2 54.0 94.1 49,6 145 146 147 148 149 150 151 152 15 3 15 4 155 156 157 158 159 160 161 162 163 1 64 165 16 6 167 16 8 16 9 170 171 172 173 1 74 175 176 177 1 78 179 18 0 181 182 183 18 4 185 18 6 187 188 189 190 191 192 o n -o ci 38.2 65.6 65.6 130,5 130,5 346.0 346.0 2019,6 414.7 822.6 1903.7 5926.3 465.2 205.3 2519.5 583. 1 16,6 24.4 12.2 17.1 38.2 65.6 25.1 39.2 130.5 346.0 67.2 133 . 4 2019.6 46695.4 3 51 . 5 2031.5 9.0 12.2 6.8 9.0 17.1 25.1 12.2 17. 1 39.2 67.2 25. 1 39.2 133.4 351 . 5 67.2 133.4 426.5 853.9 169.2 276.0 583. 1 1243.2 205.3 215.0 332.9 111.0 111.0 54.6 54.6 32.0 32.0 20.6 85.0 12^> * 8 48.9 66.3 97.2 85.3 5 4 .O 45.0 54.6 32,0 32.0 20.6 20.6 14.2 14.2 10.3 30.7 39.7 20. 6 25.7 33.2 27.4 21 . 9 18.1 20. 6 14.2 14.2 10.3 10.3 7. 7 7 */ 5.9 o o- O' o o -o cj m rg 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 0- o 3 4 5 6 5.2 6.7 6.7 8.8 8.8 11.8 11.8 16.6 14.0 16.9 19.9 24,6 14.2 11.0 20.2 15.2 8.8 11.8 11.8 16.6 16.6 24,4 24.4 38.2 29.7 38.0 47.2 63.4 30.3 21 . 9 48.5 33.2 16.6 24.4 24.4 38.2 38.2 65.6 65.6 130.5 82. 1 118.3 163.8 264.2 85.3 54.0 174.0 97.2 v) j. m 'j o- 'J 'j jj :j io o> j- o o > o o oi iJ ii <) a o 1 2 k = 3.0. j w &(!o u s. Appendix VII.— Continued. A16 VIII.— The 192 Nodal Accessibilities to Six Major Employment Opportunities in the Lansing Metropolitan Area. Ai - 2 - ------- J-i DU 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 19864.4 20703.6 20703.6 21660.3 21660.3 22765.2 22765.2 24061.7 23597.B 23225.2 25045.1 24597.0 22673.8 21691.9 23953.9 22803.1 21660.3 22765.2 22765.2 24061.7 24061.7 25613,5 25613.5 27519,9 26800.3 26247.4 28993.0 28287.2 25484.2 24108.5 27361.6 25673.6 24061.7 25613.5 25613.5 27519.9 27519.9 29946,5 29946.5 33199.3 31846.9 30901.8 35793.9 34434.7 29748.0 27601.4 32944.9 30065.8 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 where i - 1 . . . 27519.9 29946.5 29946.5 33199.3 33199.3 37946.2 37946.2 46227.5 41835.2 39630.6 53315.3 48683.1 37622,3 33395,7 45937.8 38339.8 24061.7 25613.5 23366.1 24775.5 27519.9 29946.5 26481.6 28608.8 33199.3 37946.2 31372.5 35192.0 46227.5 63966.8 41055.9 52401.8 22175.5 23366.1 21151.7 22175.5 24775.5 26481.6 23366.1 24775.5 28608.8 31372.5 26481.6 28608.8 35192.0 41055.9 31372.5 35192.0 97 98 99 100 101 102 103 104 105 1 06 107 108 109 110 111 112 113 1 14 115 116 1 17 118 119 120 121 12 2 123 124 125 126 127 128 129 130 131 132 133 1 34 135 136 137 138 139 140 141 142 143 144 (continued) k - 0.5 20259.0 21151.7 19471.2 20259.0 22175.5 23366.1 2115.1 . 7 22175.5 24775.5 26481.6 23366.1 24775.5 28608.8 31372.5 26481.6 28608.8 18769.3 19471.2 18138.7 18769.3 20259.0 21151.7 19471.2 20259.0 22175.5 23366.1 2115.1 . 7 22175.5 24775.5 26481.6 23366.1 24775.5 79939,0 68498.8 67968.1 55256.9 63602.6 47401.9 50271.7 43693.5 37342.5 33395.7 36276.1 32526,4 30065.8 27601.4 29400.5 27076.6 145 146 147 148 149 150 15 1 15 2 153 154 155 156 157 158 159 160 161 162 163 1 64 165 166 167 168 169 170 171 172. 173 174 175 176 177 178 179 180 181 1 82 183 184 185 186 187 188 189 190 191 192 48009.5 42951,2 38903,5 36555.8 40143.0 36131.1 34667.0 31742.8 32977.7 29685,8 29685.8 27282.9 27282.9 25406.8 25406.8 238B2.3 3383^ .6 32413.0 30419.0 29436.2 31025.4 28810.1 28359.3 26609.9 27282.9 25406.8 25406.8 2388.7. 3 23882.3 22608.7 22608.7 21522.6 27889.1 27159.9 25913.2 25344,7 26292.1 24065.6 24625.7 23433.5 23R82.3 22608.7 22608.7 21522.6 21522.6 20581,5 20581.5 19755.3 A17 ii. VIII.— Continued. 1 2 3 4 5 6 7 B 9 10 11 12 13 14 15 16 17 IS 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 3228.0 3507.8 3507.8 3841.3 3841.3 4245.9 4245.9 4747.4 4556.9 4410.5 5136.2 4949,0 4211.6 3853«5 4704.9 4261.6 3841.3 4245.9 4245*9 4747.4 4747.4 5386.2 53B6.2 6229.4 5886.5 5638.9 6898.4 6555.6 5332.3 4768.4 6159.5 5415.7 4747.4 5386.2 5386.2 6229.4 6229.4 7398.4 7398.4 9141 .7 8341.7 7835.7 10580.2 9758.3 7305.6 6273.8 9016.7 7472.2 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 1.0. 6229.4 7398.4 7398,4 9141.7 9141.7 12080.2 12080.2 18583.3 14583.3 13011.1 24400.0 20083.3 11925.0 9283.3 18611.1 12425.0 4747.4 5386.2 4473.9 5034.7 6229.4 7398.4 5759.9 6736.5 9 1 4 1 .7 12080.2 8128.6 10291.7 18583.3 39400.0 14194.4 24083.3 4026.8 4473.9 3661 .7 4026.8 5034.7 5759.9 4473.9 5034.7 6736.5 8128.6 5759.9 6736.5 10291.7 14194.4 8128.6 10291.7 97 98 99 100 101 102 10 3 10 4 105 106 107 108 109 110 111 112 113 114 115 1 16 117 118 119 12 0 121 1T ? 123 1 24 125 ' 126 1 127 128 129 130 131 132 133 1 34 135 1 36 137 138 139 140 141 142 143 144 (continued) 3357.7 3661.7 3100.7 3357.7 4026.8 4473.9 3661.7 4026.8 5034.7 5759.9 4473.9 5034.7 6736.5 8128.6 5759.9 6736.5 2B80.5 3100.7 2689.6 2880.5 3357.7 3661.7 3100.7 3357.7 4026 ,8 4473.9 3661.7 4026.8 5034.7 5759.9 4473.9 5034.7 59000.0 42500.0 44666. 7 25916.7 40583.3 19944.4 21944.4 18491.7 11744.0 9283.3 11239.0 8841.5 7472.2 6273.8 7154.2 6040.4 145 14 6 147 148 149 15 0 151 152 15 3 154 155 15 6 157 158 159 16 0 161 16 2 163 16 4 165 166 167 16 8 169 170 171 172 173 174 175 17 6 177 178 179 180 181 182 183 18 4 185 18 6 187 188 189 190 191 192 20083. 3 15277. 8 12694. 4 10991. 7 13491, / 11283. 3 9950. 0 8429. 4 9155. e 7316, 0 7316. 0 6143. 0 6143, 0 5310. 3 5310. 3 4683. 1 9491 . 7 8616. y 7628. 6 7096, O 7929. 4 6873, B 6607. 1 5836. 3 6143. 0 5310. 3 5310. 3 4683. 1 4683. 1 4191 . 6 4191. 6 3795. 2 6393, 7 6035. 7 5509. 9 5253. 0 5669. 6 5082. 7 4968. 4 4506. 6 4683. 1 4191 . 6 4191. 3795. 3795, 3468. 3 3468. 3 3193. 9 Aia Appendix VIII.— Continued. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 525.6 595.8 595.8 683.2 683,2 794.7 794.7 940.8 882.1 838.9 1056.4 997.8 7B5.2 686.8 928.4 799.7 683.2 794.7 794.7 940.8 940.8 1139.0 1139.0 1420,6 1297,8 1214.7 1649.6 1524,8 1122.5 948.0 1398,0 1150.0 940.8 1139,0 1139.0 1420.6 1420.6 1846.9 1846.9 2557.3 2200,5 1997.4 3161.5 2788.4 1815.4 1438.9 2514.1 1881.2 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 1.5. 1420,6 1846.9 1846.9 2557,3 2557.3 3953,2 3953.2 7979,9 5182.5 4338.0 11702.5 8635.1 3909.8 2633.0 8186.8 4173.8 940.8 1139.0 859,8 1027,9 1420.6 1846.9 1260.3 1598.8 2557.3 3953.2 2129,6 3060.6 7979.9 28477.8 5049,8 11775.6 733.4 859.8 635,5 733.4 1027.9 1260.3 859,8 1027.9 1598.8 2129.6 1260.3 1598.8 3060.6 5049.8 2129,6 3060.6 97 90 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 13 1 132 133 134 135 136 137 138 139 140 141 142 143 144 (continued) 557.7 435.5 494.7 557.7 733.4 859.8 635.5 733.4 1027.9 1260.3 859.8 1027.9 1598.8 2129.6 1260.3 1598.8 442.8 494.7 399.4 442.8 557.7 635.5 494.7 557,7 733.4 859.8 435.5 733.4 1027,9 1260.3 859.8 1027.9 48247.0 29530,7 34188.5 12628.9 31266.0 9119.3 10174.9 10241.3 3814.1 2633.0 3701.3 2473.3 1881.2 1438.9 1768.7 1361.4 145 146 147 148 149 150 151 152 153 15 4 155 15 6 157 158 159 16 0 161 162 16 3 16 4 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 8978.2 5512.6 4 2 5 8 . 1. 3330.0 4649.5 3828.6 2896.1 2300,8 2646.7 1839.8 1839.0 1400.5 1400.5 1119.5 1119.5 924. 1 2703.8 2301.4 1932.3 1716.1 2044.9 1668.0 1549.i 1294.1 1400.5 1119,5 1119.5 924. 1 924. 1 780.9 780.9 671,8 1476.0 1344.4 1177.7 1090.7 1228.3 1047.0 1006.0 871 . 7 924. 1 780.9 780.9 671 . 0 671 . 8 586.3 586.3 517.7 A19 VXIX.— Continued. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 *72 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 85.8 101.4 101.4 121.9 121 . 9 149.3 149.3 187.2 171 .1 159.8 217.9 201.6 146.9 122.8 184.1 150.7 121.9 149.3 149.3 187.2 187.2 242.2 242.2 326.3 287.2 262.4 396.4 356.0 237.7 189.4 320.0 245.9 187,2 242.2 242,2 326.3 326.3 465.8 465.8 726.6 584.4 511.8 954.4 803.6 456.7 333.0 714,5 479.8 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 2.0. 326.3 465.8 465.8 726.6 726.6 1329.4 1329.4 3652.8 1875.0 1469.6 5850.7 3879.6 1326.7 761 .9 3887.3 1451.7 187.2 242.2 165.8 210. B 326.3 465.8 277.3 382.3 726.6 1329.4 563.8 924.3 3652.8 23350.7 1842.4 6046.3 134.0 165.8 110.6 134,0 210.8 277.3 165.8 210.8 382.3 563.8 277.3 382.3 924.3 1842.4 563.8 924.3 97 98 99 100 101 102 103 104 105 1 06 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 12 4 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 14 1 142 143 144 (continued) 92.8 110.6 79.1 92.8 134.0 165. 8 110.6 134.0 210,8 277.3 165.8 210.8 382.3 563.8 277.3 382.3 68,2 79.1 59.4 68.2 92. 8 110.6 79.1 92.8 134.0 165.8 110.6 134.0 210.8 277.3 165.8 210.8 42541.7 22051.9 29231.5 6375.0 27338.0 4479.9 4979.9 7474.7 1278.3 761 . 9 1316.6 716.0 479.8 333.0 445. 3 310.4 145 146 147 148 149 150 151 152 153 15 4 155 156 157 158 159 16 0 161 162 1 63 16 4 1 65 166 167 168 1 69 170 171 172 173 174 175 1 76 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 A2 0 VIII.— Continued. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 IS 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 14*0 17.3 17.3 21.8 21.8 28.1 28.1 37.4 33,3 30.5 45.1 40.8 27.6 22.0 36,7 28,5 21,8 28. .1 28,1 37,4 37,4 51.8 51,8 75,5 63.8 56.8 95.7 83.4 50.7 38.1 73.9 52.9 37.4 51.8 51 , 8 75.5 75.5 118.7 118.7 209,6 156.2 131.9 290.9 233.6 116.3 77.8 207.0 124.0 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 2.5. 75.5 118.7 118.7 209.6 209.6 458.9 458,9 1770.2 689.6 506.0 3029.4 1821.9 465.3 224.8 1964.7 5 21 . 3 37.4 51 . 8 32.1 43.4 75.5 118.7 61 . 4 92.1 209.6 458.9 150.7 283.0 1770.2 20825.2 686.9 3218.7 24.5 32.1 19.3 24.5 43.4 61.4 32. 1 43.4 92. 1 150,7 61 . 4 92. 1 283.0 686.9 150.7 283.0 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 11 4 115 116 117 1 18 1 19 120 121 122 123 124 125 126 127 128 129 130 13 1 132 133 134 135 136 137 138 139 140 1 41 142 143 144 (continued) 15.5 19.3 12.7 15.5 24.5 32.1 19.3 24.5 43.4 61.4 32.1 43.4 92.1 150.7 61.4 92. 1 10,5 12.7 8.8 10.5 15.5 19.3 12.7 15.5 24,5 32.1 19.3 24.5 43.4 61.4 32. J 43.4 39440-7 19317.9 26775.0 3318.7 25605.7 2324,9 2548.9 6524.5 441.1 224.8 511.0 215.7 124.0 77.8 114.4 71 . 6 145 14 6 147 148 149 150 151 152 153 1 54 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 1 84 185 186 187 188 189 190 191 192 A21 Appendix VIII.— Continued. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 2.3 3.0 3,0 3.9 3.9 5.3 5.3 7.5 6.5 5,8 9.3 8.3 5.2 4.0 7.3 5.4 3.9 5.3 5.3 7.5 7.5 11.1 11.1 17.6 14.2 12.3 23.2 19.6 10.9 7.7 17.2 11.5 7.5 11.1 11.1 17.6 17.6 30.5 30.5 61.3 42.0 34.2 89.4 68.5 30.0 18.3 61 .1 32.4 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 17.6 30,5 30.5 61.3 61 . 3 162.4 162.4 899.4 257.5 177. 1 1613.4 892,1 168.1 67.6 1039.6 192.5 7.5 11.1 6.2 9 .0 17.6 30.5 13.6 22.3 61 . 3 162.4 40.6 87.7 899.4 19530.1 260.7 1757.8 4.5 6.2 3.4 4.5 9.0 13.6 6.2 9.0 22.3 40.6 13.6 22.3 87.7 260.7 40.6 87.7 k = 3.0. 97 98 99 100 101 102 1(^3 .1yJ4 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 2.6 3.4 2.0 2.6 4.5 6.2 3.4 4.5 9.0 13.6 6.2 9.0 22.3 40.6 13*6 22.3 1.6 2.0 1.3 1.6 2 .6 3 .4 2 ,0 2.6 4.5 6.2 3.4 4.5 9.0 13.6 6.2 9.0 37725.7 17406.4 25508.7 1772.4 24805.3 1253.6 1350.8 6190.5 156.2 67.6 216.2 67.9 32.4 18.3 30.1 16.8 145 146 147 148 149 150 151 152 153 1 54 155 156 157 .158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 1115.9 280.8 187. 8 96. 7 218.3 291 . 3 77. 3 61 . 3 89.7 34.3 34.3 18.2 18.2 11.1 11.1 7.4 68.4 45. 1 33.3 24.7 36,9 27.2 20.7 15.3 18.2 11.1 11.1 7.4 7.4 5.2 5.2 3.8 18.9 15.1 11.9 9.9 12.8 9.7 a. 5 6.6 7.4 5.2 5.2 3.8 3.8 2 .9 2.9 2.2 A22 IX.— The 192 Nodal Accessibilities to Nine Major Urban Centers (Urban Functions) in the Lansing Metropolitan Area. m Ej A* - I ---- £- 1 2 3 4 5 6 7 8 9 10 U 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 3822.6 3982.8 3993.0 4179.4 4152.4 4358.4 4381.5 4639.5 4614.3 4488.7 5004.5 4792.8 4423.3 4197.2 4701.4 4428.2 4190.9 4413.6 4371.1 4617.1 4666.4 5033.2 4884.7 5235.9 5640.5 5217.2 5735.5 5462.2 5052.4 4707.2 5363.7 4970.7 4593.1 4B78.9 4867.1 5214.5 51B6.6 5594.1 5588.3 6109.5 6150.5 5882.0 6873.9 6492.9 5804.6 5316.3 6433.1 5775.5 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 whore 5212,4 5659.3 5642.4 6266.3 6137.4 6877.8 6871.4 7972.9 8120.9 7425.0 10327.3 8851.2 7410.7 6416.6 9248.7 7367.0 4537.2 4829.3 4335.2 45B7.1 5190.9 5659.9 4892.1 5274.8 6266.5 7264.0 5685.3 6296.6 8101.8 10335.2 6890.9 7978.0 4168.8 4394.5 4036.0 4248.7 4666.9 5011.5 4513.9 4892.8 5299.3 5715.1 5041.3 5336.4 6164.8 6856.1 5680.3 6178.6 i - 1.....192; j - 1,...,9; k - 0.5 97 98 99 100 101 102 103 104 105 106 107 108 109 110 HI 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 (continued) 3936.6 4155.4 3770.6 3948.2 4474.6 5031.9 4169.6 4492.6 4929.9 5089.2 4567.6 4762.4 5350.2 5742.8 5007.8 5370.6 3631.8 3784.9 3498.6 3631.8 3966.2 4193.5 3784.9 3966.2 4325.2 4522.8 4094.9 4263.2 4782.8 5209.2 4457.3 4732.0 15823.9 12151.0 10286.8 8862.3 13431.4 9231.6 9293.6 7417.8 7176.3 6443.5 6623.3 6142.7 5750.2 5258.3 5495.6 5047.8 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 7957.9 7409.7 6864,7 6576.5 7480.9 6476.6 6633.1 5896.2 6018.0 5537.0 5532.4 5133.9 5082.2 4737.7 4779.1 4493.7 6222.9 6088.1 5677.2 5533.2 6276.0 5550.9 5562.9 5090.8 5197.0 4847.2 4853.8 4567.0 4545.4 4297.7 4314.8 4102.6 5319.8 5152.0 4901.3 4791.9 5115.3 4762.8 4755.1 4476.1 4569,2 4329.0 4320.2 4116.6 4114.2 3939.8 3931.8 3770.7 A23 XX.— Continued. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 632.4 688.7 692.0 761.8 751.6 835.1 843.3 962.2 953.8 883.4 1184.2 1022.1 852.8 764.8 969.8 854.6 765.6 856.2 827,9 927.7 972.3 1194.3 1042.7 1213.3 1817.7 1270.6 1516.6 1314.0 1135.0 971.9 1260.2 1076.0 912.7 1033.6 1026.4 1184.4 1168.7 1367.6 1358.5 1634.6 1676.2 1506.2 2109.8 1837.8 1475.5 1230.8 1828.0 1459.6 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 1. 1182.9 1408.9 1398.5 1776.2 1650.4 2104.5 2084.5 2849.2 3092.9 2431.6 5048.1 3467.8 2476.9 1820.3 4089.4 2449.7 890.9 1012.2 812.6 912.1 1175.1 1410.4 1041.6 1219.6 1776.9 2650.7 1419.9 1788.9 2975.1 5034.3 2089.4 2941.8 753.5 840.8 712.1 796.6 955.1 1118.2 917.4 1148.2 1229.4 1432.6 1130.8 1246.3 1652.0 2055.7 1398.9 1658.1 97* 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 (continued) 689.9 788.7 625.9 694.7 989.7 1617.5 795.0 998.3 1165.2 1154.8 942.5 1001.9 1252.3 1444.0 1104.4 1302.7 577.7 632.1 533.5 577.7 703.3 807.5 632.1 703.3 835.0 911.4 738.7 798.4 1052.3 1447.7 878.8 1029.2 13217.2 6705.8 4993.1 3465.4 9924.0 4083.4 4114.4 2480.9 2322.3 1866.9 1979.5 1818.6 1459.1 1210.2 1352.5 1118.2 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 2827.8 2389.8 2063.3 1879.0 2516.6 1851.5 1985.2 1530.5 1593.8 1369.7 1338.6 1155.1 1131.5 976.5 993. B 875.2 1695.0 1658.6 1411.5 1339.9 2041.2 1405.8 1412.7 1143.2 1190.8 1028.9 1031.2 908.9 898.8 800.5 807.8 728.2 1279.7 1165.5 1054.7 998.7 1159.1 992.4 9B9.3 871.3 909.3 814.0 809.8 734.1 733.0 667.4 668.2 613.7 A2 4 Appendix IX.— Continued. 1 2 3 4 5 6 7 3 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 105.9 121.1 121.9 142.1 139.2 166.0 168.3 213.7 211.6 179.4 336.3 231.2 167.6 141.3 205.8 168.1 143.1 172.2 158.8 189.7 216.6 339.0 227.9 293.7 979.9 362.7 451.2 327.2 268.2 206.4 302.4 236.4 183.1 222.1 219,0 274.0 266 *8 340.8 334.9 446.3 472,3 390.8 675.6 527.1 382.0 288.3 533.0 375.4 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 1.5. 273.3 362.3 357.4 546.3 453.4 670.8 649.0 1054.6 1341.5 817.8 2638.3 1383.6 864.6 530.3 1976.0 B51.2 176.6 215.0 153.7 183.6 271.1 362.9 225.7 289.6 546.7 1289.0 365.6 550.2 1147.5 2618.5 648.9 1047.0 138.2 164.1 129.3 156.2 201. 7 264.1 202.6 332.8 292.5 369.6 268.2 298.3 448.5 627.5 348.2 450.4 97 98 99 100 101 102 103 104 105 106 107 108 109 no 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 (conClnued) 128.7 167.8 108.2 130.2 287.4 975.5 169.9 290.5 338.7 277.2 211.6 219.4 300.1 372.4 253.2 349.2 94.8 110.3 83.3 94.8 133.3 174.8 110.3 133.3 171.2 195.2 138.5 154.8 268.4 661.3 183.0 260.5 12257.6 3796.4 2593.9 1378.7 8608.7 1974.8 1986.9 866.4 784.1 570.2 629.3 702.2 380.6 283.9 357.1 255.0 145 146 147 148 149 150 151 152 153 154 155 156 157 153 159 160 161 162 163 164 165 166 167 163 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 ■ 185 186 187 188 189 190 191 192 1039.9 779.0 631.9 544.0 882.8 543.2 634.9 409.0 432.9 362.6 330.6 267.3 2S8.9 204. 7 210.2 172.5 472.1 487.8 360.2 334.0 972.5 398.1 401.0 267.5 283.7 224.5 225.2 184.6 180.9 151.0 153.4 130.7 341.3 273.3 235.5 212.3 275.1 212.3 211-3 172.6 184.5 155.5 154.0 132.2 132.1 114.4 114.7 100.6 A25 Appendix IX.— Continued. I 2 3 4 5 6 7 8 9 10 U 12 13 1A 15 16 17 18 19 20 21 22 23 2A 25 26 27 28 29 30 31 32 33 3A 35 36 37 38 39 AO A1 A2 A3 AA A5 A6 A7 A8 18.0 21.7 21.9 27.A 26.6 3A.8 35.3 52.6 52.1 38.1 122.7 57.1 33.7 26.5 A5.3 33.8 27.6 36. A 30.9 39.6 53.3 123.3 51.3 75.A 79 A. 0 129.9 158.A 85.3 67.9 A5.A 7A.1 52.7 37.1 AS.A A7.3 6A.7 61.7 86.5 83.6 12A.3 137.8 102.6 227.2 152.9 100.A 6B.6 158.9 98.1 A9 50 51 52 53 5A 55 56 57 58 59 60 61 62 63 6A 65 66 67 68 69 70 71 72 73 7A 75 76 77 78 79 30 31 32 83 8A 85 86 87 88 89 90 91 92 93 9A 95 96 k = 2.0. 6A.5 97.0 9A.9 188.7 127.3 22A.6 206.6 A00.9 705.7 283.5 1A37.A 557.6 313.0 158.1 1019.1 306.8 35.A A6.3 29.A 37.5 63.9 97.1 A9.3 70.9 188.9 877.3 97.7 189.8 A62.A 1A20.0 205.9 396.2 25.8 32.9 2A.A 32.7 AA. A 67.6 50.6 126.7 71.7 98.9 68.7 73.5 123.2 19A.6 87.5 123.7 (continued) 97 98 99 100 101 102 103 10A 105 106 107 108 109 110 ill 112 113 UA 115 116 117 118 119 120 121 122 123 12A 125 126 127 128 129 130 131 132 133 13A 135 136 137 138 139 1A0 1A1 1A2 1A3 1AA 26.A 42.2 19.8 26.8 115.0 853.9 A2.8 116.0 128.5 71.8 53.5 50.5 73.9 99.0 61.3 110.A 16.2 20.A 13.A 16.2 27.8 AA. 5 20.A 27.8 38.0 A5.7 27.3 31.5 87.1 A95.7 A1.6 8A.6 11890.2 2173.0 1A07.5 55A.1 8098.2 1019.1 1023.A 313.7 27A.2 185.6 216.a A07.5 102.0 67.8 105.8 60.A 1A5 1A6 IA7 1AS 1A9 150 151 152 153 15A 155 1S6 157 158 159 160 161 162 163 16A 165 166 167 168 169 170 171 172 173 17A 175 176 177 178 179 180 181 182 183 18A 185 186 187 188 189 190 191 192 393.0 255.8 196.7 159.7 320.8 163.0 221.2 112.9 120.5 107. A 83.3 6A.2 61.5 A3.8 AS.A 3A.5 134.7 162.1 94.9 86.7 698.7 133.6 134.7 66.A 71.3 50.7 51.0 38.5 37.2 28.9 29.6 23.7 108.0 67.5 55.7 46.3 69.5 46.9 46.7 34.9 38.3 30.2 29.8 24.2 24.1 19.8 19.9 16.6 A2 6 Appendix IX.— Continued. 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 18 19 20 21 22 23 2A 25 2c 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 3.1 4.0 4.0 5.5 5.3 7.8 7.9 14.7 14.6 8.6 56,0 15.8 7.0 5.1 10.4 7.0 5.5 8.2 6.1 8.5 14.9 56.1 12.0 20.9 752.3 57.8 66.5 23.6 18.8 10.5 18.6 11.9 7.6 10.7 10.4 15.7 14.5 22.4 21.2 35.3 41.7 27,2 81.2 44.8 26.8 16.4 48.3 26.0 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 '70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 2.5. 15.6 27.3 26.5 75.0 36,5 80.0 67.1 155.4 467.5 102.2 802.6 226.0 116.7 48.1 549.2 113.9 7.2 10.1 5.7 7.8 15.4 27.2 11.3 18.0 75.0 750.4 27.4 75.3 193.9 789.9 66.6 153.0 4.9 6.8 4.9 7.5 10.3 19.1 14.6 60.0 18.2 27.7 19.4 18.7 34.2 61.1 22.2 34.3 97 96 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 (continued) 6.1 12.7 3.9 6.2 57.2 830.6 12.9 57.5 60.5 20.4 15.5 12.4 18.7 27.3 16.0 42.9 2.9 4.1 2.2 2.9 6.5 13.4 4.1 6.5 9.3 12.0 5.7 6.8 36.5 460.6 10.7 35.8 11746.1 1249.6 784.0 224.1 7896.0 549.3 550.8 116.9 98.6 65.4 82.9 328,1 28.1 16.5 37.0 15.1 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 135 186 187 188 189 190 191 192 151.7 84.4 62.0 47.6 119.9 49.9 85.4 32.3 34.4 37.4 21.5 16.2 15.3 9.6 10.0 7.0 39.5 63.1 26.0 23.7 627.6 54.6 54.9 17.8 19.2 12.0 12.1 8.3 7.9 5.6 5.8 4.4 42.2 17.9 14.3 10.5 19,0 10.8 10.7 7.2 8.2 6.0 5.9 4.5 4.5 3.5 3.5 2.8 A27 Appendix IX.— Continued. 1 2 3 4 5 6 7 8 9 10 LI 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 .6 .8 .8 1.2 1.1 1.9 1.9 4.7 4.7 2.1 29.2 4.9 1.5 1.0 2.5 1.5 1.2 2.0 1.2 1.9 4.7 29.2 2.9 6.3 742.8 29.7 32.2 7,0 5.7 2.5 4.8 2.7 L. 6 2.4 2.3 3.9 3.4 5.9 5.4 10.3 13.1 7.3 31.2 13.3 .7.2 4.0 14.9 7.0 49 50 51 52 53 54 55 56 57 5B 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 SO 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 k = 3.0. 3.9 8.1 7.8 34.1 10.7 30.8 22.1 61.1 376.2 38.8 454.7 91.9 44.5 14.9 304.3 43.3 1.5 2.2 1.1 1.6 3.8 8.1 2.6 4.7 . 34.1 710.6 8.1 34.1 84.5 446.1 21.9 60.0 1.0 1.5 1.0 1.9 2.5 6.0 4.8 32.0 4.8 8.2 6.1 4.9 9.6 19.4 5.7 9.6 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 1.6 4.4 .8 1.6 31.3 826.1 4.4 31.4 32.2 6.3 5.1 3.2 4.9 7.9 4.6 20.0 .6 .9 .4 .6 1.7 4.6 .9 1.7 2.5 3.6 1.3 1.6 IB.3 453.1 3.2 18.1 11688.7 720.2 443.4 90.9 7815.0 304.4 304.9 44.6 36.3 25.3 35.8 306.9 8.0 4.1 15.5 4.0 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 59.5 27.9 19.8 14.4 45.9 15.5 36.7 9.6 10.1 15.6 5.6 4.4 4.1 2.2 2.3 1.4 11.9 28.6 7.5 6.9 608.8 26.1 26.3 5.2 5.6 3.0 3.0 1.8 1.7 1.1 1.2 .8 19.8 5.1 4.0 2.5 5.7 2.6 2.6 1.5 1.8 1.2 1.2 .9 .8 .6 .6 .5 BIBLIOGRAPHY BIBLIOGRAPHY Alcaly, R. 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