?\ ‘ c 3 \w’ Ii 5*" -‘ I: n ‘00".8 :- x 1 2L: 1R... Pt .. . r. y. .. 3 .- v. . .5. o. O. N'- 9. 8.3“. I!“ n T... . . I3... 2",. r ,. . O n . I5.- 7‘..-‘ .. C _ ‘ l. .. .. .. f...- .0 DAL“ f-.. an fl. is? g ! THESIS LIBRARY Michigan State University ABSTRACT INDICATORS OF GENERAL AVIATION ACTIVITY FOR PLANNERS OF SMALL COMMUNITIES by John T. Smith The value of an airport and aviation to a community has long been recognized by those who have a financial or aeronautical interest in aviation. Community planners and city officials, however, often have not given adequate recog- nition to the value of the airport to the community. This is especially true for smaller cities where general aviation activity (i.e., all civil air traffic except scheduled air- lines) may be the only aviation activity. The basic problem, then, beyond that of increased awareness of the value of general aviation, is one of determining the potential gen- eral aviation activity of existing or possible airports so that more adequate and realistic plans can be made. This thesis points out first what general aviation is and the part it plays in the total air transportation system. Examples of general aviation activity are given as well as its effect on the growth of a specific southern com- munity. Various studies are reviewed which outline in con— siderable detail the characteristics of the people who fly, John T. Smith i.e., their income, education, and occupation. Covered last is general aviation use by different industries. In an approach to the problem of determining poten- tial general aviation activity, a study of the characteris- tics of forty-eight Michigan cities within the population range of 2,500 to 50,000 was undertaken. All characteris- tics were based on data published in the g.§, Census 2: Population: 1960. The objective of the study was to deter- mine what, if any, community characteristics relate to gen- eral aviation activity. Two separate methods of analysis were used to determine which characteristics were related to general aviation activity. The related characteristics were then tested on certain cities with known activity levels as a check on their degree of accuracy. It was found that nine of the twenty-eight character- istics considered, when used together, could be useful in determining potential general aviation activity. Indicators relating to the agriculture and finance industries proved most related to general aviation activity as did the indica- tors related to agriculture and management occupations. Examples are given of how the indicators might be of use to community planners and aviation agencies when studying a given community. INDICATORS OF GENERAL AVIATION ACTIVITY FOR PLANNERS OF SMALL COMMUNITIES BY John T. Smith A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER IN URBAN PLANNING School of Urban Planning and Landscape Architecture 1966 Copyright by JOHN THOMAS SMITH 1966 ACKNOWLEDGMENTS are made for the cooperation and understanding shown by all who gave assistance to this under— taking, not the least of whom were Ward J. May- rand, Donald A. Krueckeberg, Charles A. Hansen, and my wife. iii TABLE OF CONTENTS ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . LIST OF TABLES . . . . . . . . . . . . . . . . LIST OF APPENDICES . . . . . . . . . . . . . . INTRODUCTION . . . . . . . . . . . . . . . . . Chapter I. GENERAL AVIATION TODAY . . . . . . . . II. A STUDY OF COMMUNITY CHARACTERISTICS OF MICHIGAN CITIES . . . . . . . . . . . Top lZ-Bottom 12 Method . . . . . . Coefficient of Correlation Method . Application of Methods . . . . . . III. INDICATORS OF GENERAL AVIATION ACTIVITY APPEM ICES O O O O O O O O O O O O O O O O O O BIBLIOGMPHY O O O O O O O O O O O O O O O O 0 iv Page iii vi 23 31 35 37 41 50 59 5. 6. ll. 12. 13., LIST OF TABLES Personal characteristics . . . . . . Occupations . . . . . . . . . . . . Employment capacity . . . . . . . . Relationship between active corporations plane-owning firms by major industrial groups for the United States . . . Forty-eight selected cities . . . . Selected cities and rankings . . . . Characteristics considered . . . . . Top 12-Bottom 12 indicators . . . . Coefficient of correlation indicators Selected indicators and relation to general aviation activity . . . . . . . . Indicators of general aviation activity General aviation users by occupation and industry 0 O O O O O O O O O O O 0 Application of indicators . . . . . Page 14 15 16 21 26 28 30 34 36 38 42 43 46 LIS T OF APPEND ICES Appendix Page A. x Values of Characteristics--T-B 12 Me thOd O O O O O O O O O O O O O O O O O O 5 l B. Characteristic Values (T-B 12 Method) . . . 53 C. Characteristic Values (C of C Method) . . . 54 D. Evaluation of Indicators . . . . . . . . . . 55 Table l—-Six Active Cities . . . . . . . 55 Table 2--Six Non—Active Cities . . . . . 56 Table 3-—Accuracy of Indicators Applied to Cities . . . . . . 57 Table 4--Accuracy of Indicators by Rank and Method . . . . . . . 58 vi IN TRODUC TION Plaintiff argues that the acquisition of an airport or landing field is not a city purpose, even if a public one, and that the bonds, if issued, will be void. We think the purpose to be served is both public and municipal. A city acts for city purposes when it builds a dock or a bridge or a street or a subway. Its purpose is not different when it builds an airport. Aviation is today an established method of trans- portation. The future, even the near future will make it still more general. The city that is without the foresight to build the ports for the new traffic may soon be left behind in the race of competition. Chalcedon was called the city of the blind because its founders rejected the nobler site of Byzantium lying at their feet. The need for vision of the future in the gover- nance of cities has not lessened with the years. The dweller within the gates, even more the stranger from afar, will pay the price of blind- ness. The value of an airport and aviation to a community has long been recognized by those who may have a financial or aeronautical interest in aviation. This value has also been recognized by the courts. Nearly forty years ago Justice C. J. Cardozo of the New York Court of Appeals, in ruling for the city of Utica, New York, handed down the above statement as part of his ruling that the city had a lHesse v. Rath 23 31., l64.Northeastern Reporter, p..342, December 7, 1928. Reprint obtained from Piper Air- craft Corporation, Lock Haven, Pennsylvania. right to issue corporate bonds to purchase land on which to establish an airport. Community planners and city officials, however, often have not given adequate recognition to the value of the airport to the community. This is particularly true in the smaller cities where general aviation activity (i.e., all civil air traffic except scheduled airlines) may be the only aviation activity. The words of Justice Cardozo are even more timely today because of the advancements made in the field of aviation, and particularly general aviation, than when they were written in 1928. This thesis attempts to point out in the first chap- ter what general aviation is today. Special attention is given to the magnitude of general aviation and how it has effected people and business. A specific example of its effect on a community is related to help point out the impor- tance of this segment of the air transportation system. Various studies are then reviewed concerning the peOple who fly--who they are and why they fly. The second chapter is based on a study of the char- acteristics of forty-eight Michigan cities within the popula— tion range of 2,500 to 50,000. The objective of the study was to determine what, if any, community characteristics relate to general aviation activity. Two separate methods of analysis were used to determine which characteristics were related to general aviation activity. The related characteristics were then tested on certain cities with known activity levels as a check on their degree of accuracy. The final chapter combines the findings of the study of Michigan cities with the nature of general aviation as outlined in the first chapter in order to arrive at some indicators of general aviation activity. Examples are given of how the indicators might be used by community planners and aviation agencies when studying a given community. It is hOped that the indicators will be of value in better understanding and evaluating the value of airports in small communities. CHAPTER I GENERAL AVIATION TODAY In the last sixty years aviation has developed from virtually nothing to its present position as one of the most important components of the national transportation system. To many persons and many communities, however, aviation is thought of only in terms of the scheduled airlines or air carriers. Often overlooked is the largest segment of avia- tion, commonly called "general aviation." The term "general aviation," as widely used by aviation agencies and the avia- tion industry, may be defined as all air traffic except that of the military and scheduled airlines. A few areas of comparison between general aviation and scheduled airlines will help point out the importance of general aviation in the area of air transportation. Of the 90,935 active aircraft registered with the Federal Aviation Agency at the beginning of 1965, general aviation accounted 2 for 88,742, air carriers only 2,081. 0f the 9,490 airports- on record at the beginning of 1965, 8,791 were general 2FAA Statistical Handbook of Aviation (Washington, C.: U.S. Government Printing Office, 1965), pp. 53-54, aviation airports and only 709 were airports with regular airline operations.3 The charts on the following page show the percentages of planes in the air and hours flown for the three types of aviation activity. As suggested above, this prominent role of general aviation is too often not realized by those in a position to capitalize upon it most, namely, the community officials, leaders, and planners. As pointed out in a report by the Eastern Region of the Federal Aviation Agency, "community officials all too frequently have failed to recognize that the airport, and the business it generates, is an economic asset that should be afforded every protection possible to assist in maintaining economic flexibility of the communi— ties which it serves."4 They go on to say that "failure on the part of a community to incorporate its airports into the community development plan can be attributed to ignorance of the importance of aviation in the scheme of transportation."5 With this in mind, it is important that planners obtain a better understanding of aviation, and general aviation in particular, so they will be able to recognize the impact of general aviation upon future community growth and then 3Ibid., p. 5. 4General Aviation and Its Relationship E9 Industry and the Community (Jamaica, New York: Federal Aviation Agency, Eastern Region, Airports Division, 1964), p. 4. 5 Ibid., p. 5. Chart 1. Planes Airlines C; 1.9% Militar 18.3% General Aviation 79.8% 1963 in the air Airlines 65 1.1% Milit y 13.4% General Aviation 84.9% 1969 ForecASt * Chart 2. Hours in the air Military 32.3% General Aviation 51.9% 1963 * Air ' es 13.6% Military 26.6% General Aviation 59.9% 1969 Forecast Source: General Aviation--Today and Tomorrow. prepare a development plan which is more realistic and that better serves the needs of the community. General Aviation General aviation may be broken into four basic cate- gories or types of flying. They are business flying, com- mercial flying, flight instruction, and personal or pleasure flying. Business flying covers the use of private aircraft as a means of transportation in the conducting of some busi- ness enterprise. During 1962, a business fleet of approxi- mately 34,000 airplanes flew a total of 5.5 million hours.6 Flying for business purposes accounts for about thirty—seven per cent of the total general aviation hours flown.7 Commercial flying includes the use of private air— craft to perform a service for hire. Examples of this type of use are air taxi and charter flying. This type of flying amounts to about twenty-one percent of the total general . . 8 avration hours. 6Joseph T. Geuting, Jr., "General Aviation: What It Is and Why Important to You," Speech given at NAEC Annual Meeting, Miami Beach, Florida, July 10, 1963, p. 6. (Mimeo- graphed.) 7Robert L. Parrish, "General Aviation 1966," The AOPA Pilot, IX (March, 1966), 28. 8Ibid. The smallest segment is that of flight instruction. It accounts for about eighteen percent of the total general aviation hours.9 The last group, personal or pleasure flying, cover- ing those persons who fly strictly for the fun of flying, accounts for about twenty—four percent of the total hours.10 This is the fastest growing type of flying and in the last five years has increased more than fifty percent.11 From these four categories it is easy to see that general aviation covers a broad range of aviation activity. Specifically, it might be worth elaborating on some of the ways private aircraft are used. As Senator Proxmire read into the Congressional Record, "so conglomerate is the mix- ture of people, business, aircraft and activities, that while the term 'general aviation' is hardly descriptive, it is about the only one that describes it all."12 The use of general aviation aircraft has done much to improve farming and ranching. Nearly every kind of crop can be treated in some manner with the use of aircraft, from 9Ibid. lOIbid. llGeutling, "General Aviation: What It Is and Why Important to You," p. 6-7. 12William Proxmire, "Significance of General Avia- tion to the National Economy," U.S., Congressional Record, Senate, 1962. Reprint obtained from Piper Aircraft, Lock Haven, Pennsylvania, p. l. seeding and fertilizing a new crop to weeding a more mature crop. Ranchers inSpect fences and pastures from the air as well as note livestock movements. Forestry has been effected much the same way as agriculture. Of primary importance is forest preservation, ranging from fire spotting to fire fighting with the drop- ping of men and equipment by parachute. The airplane has even had its influence on real estate development. A new subdivision in Fresno, California, provides for the aircraft to be taxied from the landing strip right up to the owner's residence and parked under his planeport next to the house.13 The use of private aircraft has effected the recrea- tion and pleasure patterns of many people. Many dude ranches, hunting and fishing lodges, and resorts of all kinds have put in landing strips for their guests. Boyne Mountain ski lodge is but one example here in Michigan of a resort, with an airstrip adjacent, which attracts many pilots. Aircraft are widely used in politics and government, too. Few are the candidates aspiring to a major political office who don't make use of private planes in some manner in meeting their tight campaign schedules. Various levels of government use the personal airplane, from transporting l3"An Aviation Subdivision," Urban Land, XXIV (February, 1965), 9. 10 the President or the Governor, to highway patrol and aerial survey work. Not only has general aviation had a tremendous effect on other business activity, as evidenced from many of the examples above, but it has spawned a whole host of enter- prises just to serve itself. Different manufacturers pro- duce a wide variety of equipment necessary for aircraft operation, including engines, tires, and radio and elec- tronic equipment. At most any airport can be found all sizes of businesses which repair and maintain the aircraft, train pilots and mechanics, as well as provide special ser- vices such as air taxi, charter flying, and crop dusting. Most of the examples cited thus far relate to those persons who already fly or are aware of the value of general aviation. Not to be overlooked is the effect the airport has on those who do not fly. A recent article in The AOPA l4 23193 gave an example, which is worth repeating here, of the value of an airport to a community. The peOple of Cartersville, Georgia, were seeking to attract a branch plant of the Oster Company with a potential employment of five hundred to six hundred people. The city did not yet have an airport even though it had one planned. In deciding for Dayton, Tennessee, over Cartersville, the l4Charles Spence, "Airports Are for People Who Don't Fly," The AOPA Pilot, IIX (September, 1965), 28. 11 vice president in charge of manufacturing wrote the mayor of Cartersville: "I feel quite certain that had Carters— ville had an airport adjacent to the town, our decision probably would have been in favor of Cartersville. Unfortu- nately, we cannot wait until an airport is built before opening our next facility."15 The United States Chamber of Commerce has estimated that for every one hundred new factory jobs there is $710,000 more annual personal income. This means $331,000 more in retail sales, $229,000 more in bank deposits, 97 more auto- mobiles, 3 new retail businesses, 65 new non-manufacturing 16 It is not too hard jobs, and a population increase of 359. for the people of Cartersville to figure out what over one- and-a-half million dollars a year in retail sales would mean to their community. This is not just one community in Georgia, though. This is repeated over and over each year in communities everywhere, even in Michigan. And it is not just any airport over no airport, either. A well-kept airport with adequate facilities, one which the people are proud of, means much more than the run-down airport with weeds growing all around. Another major benefit of the airport is bringing transient money into the community. The Michigan Aviation lsIbid. 16Ibid. 12 Fact Finder Survey, which studied aviation activity at Michigan's licensed airports in 1962, found that the average expenditure for a non—resident general aviation pilot was $15.44 while for non-resident general aviation passengers the amount was $21.34.17 This amounted to about fifteen thousand dollars to twenty thousand dollars annually for some of the less active airports to well over five hundred thousand dollars annually at some of the more active air- ports. And this is just by general aviation pilots and passengers, not airline passengers. The reason aviation and an airport can mean so much to a community is more easily understood when looking at the peOple who fly and their reasons for flying. Their use of the airplane gives a better idea of the potential at some communities as well as pointing out those to whom it has the greatest importance. Looking first at new pilots, why do they learn to fly and what are some of their characteristics? A recent survey from Time gives some of the necessary information from those who obtained a private pilot license in 1963.18 Fifty-seven percent of those surveyed listed pleasure as their main reason for flying, while forty percent combined 17Michigan Aviation Fact Finder Survey (Lansing, Michigan: Michigan Department of Aeronautics, 1963), p. 7. 18New Pilots, A Survey of the Individuals Obtaining Pilot's Licenses in 1963, Research Report 1301 (New York: Time Marketing Information, 1964). 13 business and pleasure. They felt the most important benefits of flying were that it was fun and enjoyable, was stimulating and challenging, saved time (convenience), and was a safer method of travel. The new pilots were well educated, with seventy-five percent having gone to college. Their median family income was $10,110 a year. They were a fairly young people, having an average age of 31.6 years. The largest area of employment was listed as business, accounting for sixty-seven percent of the total. Among the professional, those persons in medicine were the most apt to fly. Since business was the largest category for the new pilots, it was broken into type and job title. Manufacturing lead the list, followed by Construction/Engineering/Architec- ture, Transportation/Communication/Public Utilities, Retail, Service, and Finance/Real Estate/Insurance. As to the posi- tion within the business of the new pilots, Top Management accounted for thirty-one percent; Middle Management, and Professional and Technical, each twenty-one percent: Other White Collar, eleven percent; and Blue Collar, fifteen per- cent. Tables 1, 2, and 3 show the personal characteristics, occupation, and employment capacity of the new pilots along with that of two other pilot groups discussed later. 14 Table 1. Personal characteristics fifi New AOPA New Plane Pilots Profile Purchasers Average Annual Income $10,110 $18,499 $33,333 Education College graduate or beyond 42% 47% 42% Attended college 33%. 26% 26% High school graduate 20% 20% 22% Some education but not high school graduate 5% 7%. 10% Average Age 31.6 yr 41.9 yr 43.4 yr 15 Table 2. Occupations New AOPA New Plane Pilots Profile Purchasers (%) (%0 0%) Business Manufacturing 24 20 21 Wholesale 4 3 4 Retail 6 8 9 Service 5 .. 3 Finance/Real.Estate/ Insurance 5 5 6 Transportation/Com- munication/Public Utilities 7 8 ll Farming/Agriculture, 2 5 14 Construction/Engi-' nearing/Architecture 13 21 9 “OERSr business 1 .. l 67 70 78 Professional Medicine 3 6 8 Dentistry 1 1 2 Education 2 4 1 Clergy l l .. Law 1 2 3 Other professional 3 .. 2 ll 14 16 Other (includes Armed Forces, Government, Student, Housewife, Retired, etc., and not stated) 22 22 6 Total 100 106* 100 *Exceeds 100% because of multiple mentions. 16 Table 3. Employment capacity* New AOPA New Plane Pilots Profile Purchasers (%) (%) (%) Top Management 31 37 70 (includes Owners, Partners, Presidents & Other Corp. Officers, General Mgrs., etc.) Middle Management 21 13 14 (includes Managers and Dept. Heads, Superintendents, etc.) Professional & Technical 21 34 6 (includes Engineers, Chemists, Other Tech— nicians, etc.) Other White Collar 11 3 2 (includes salesmen, clerical, etc.) Blue Collar 15 4 7 (includes skilled, semi-skilled & unskilled, farmers, etc.) Not stated 1 9 1 Total 100 100 100 *Capacity of those engaged in Business, Table 2. 17 In 1964, the FAA Statistical Handbook 2; Aviation indicated that 378,700 general aviation pilots flew a total of 15 million hours. Of these totals, the 110,000 AOPA members/PILOT readers flew over 11.9 million hours. In other words, twenty-nine percent of the licensed pilots flew over seventy-nine percent of the general aviation hours.19 This information is given as a base for a survey of AOPA members/PILOT readers and published as Profile 2f_F1ying g 20 It is probably most representative of general Buying. aviation today in that its number accounts for such a large percentage of the total hours flown. The following informa— tion points out the main characteristics of the pilots most likely to bring business and money to the community. AOPA members/PILOT readers were well-to-do persons, having an average annual income of $18,499. Nearly seventy percent had an annual income of $10,000 or more. They were a fairly well-educated group, with seventy-three percent having attended college or beyond. Their average age was about forty-two, or ten years older than that of the new 193593113 9; Flying and Buying (Washington, D.C.: Aircraft Owners and Pilots Association, 1965), p. 1. 20AOPA (Aircraft Owners and Pilots Association) is the world's largest organization of civil airplane pilots and owners. It was founded primarily to stimulate the growth of general aviation in the United States. The PILOT (The AOPA Pilot) is the monthly magazine published by the association. 18 pilots mentioned earlier. Table 1 shows the personal char- acteristics of the AOPA group. Like new pilots, seventy percent of the AOPA members/ EIEQE readers listed some type of business as their major occupation. Construction/Engineering/Architecture ranked slightly ahead of Manufacturing, followed in turn by Trans- portation/Communication/Public Utilitiies, and Retail. Of the professions listed, medicine again ranked first. Table 2 gives the percentages in each category. Table 3 shows the capacity of employment within business, lead by Top Manage- ment. Eighty—four percent of the group were in the three areas of Top Management, Middle Management, and Professional and Technical. A third group of interest is those who buy new pri- vate airplanes. A recent study of new airplane buyer521 produced some results that generally fit the pattern estab- lished by the two studies already described. About sixty- eight percent of the new plane buyers had attended college. Their average age of 43.4 years was slightly higher than that of the AOPA group and considerably above that of the new pilots. The greatest difference, however, was in annual income. New plane purchasers had an average income of over 21The Men Who Buy New Private Airplanes, Research Report 1302 (New York: Time Marketing Information, 1964). 19 $33,000. A comparison of this group with the other two groups is shown on Table 1. Occupation distribution of new plane buyers varied little from that of the other two groups. The most signif- icant change was in the rise of Farming/Agriculture to second place following Manufacturing in the business ranking. Also of note is that nearly twice the percentage of new plane purchasers were in Top Management when compared to the other two groups of new pilots and AOPA members/PILOT readers. In summary then, and as shown in Tables 1, 2, and 3, it can be said that the average or typical general aviation pilots and plane owners are well-educated, financially well- off, and between thirty and forty—five years old. The major- ity of the pilots are in business with most of them being in a management capacity. Turning now to a look at the industries, rather than the people and their occupations, we can get a deeper in- sight into the uses of private planes. A report of the National Business Aircraft Association points out the rela- tionship between active corporations, by major industrial group, and the number of plane-owning firms in the United States. Of the approximately 1.1 million active corporations, just over one percent were identified as plane-owning firms.22 22Business Flying, Special Report 66-4 (Washington, D.C.: National Business Aircraft Association, Inc., 1966), 20 Table 4, taken from the National Business Aircraft Associa- tion report, shows the numbers and percentages for each industrial group. From the above mentioned table, it is easy to see that Manufacturing firms lead the list in plane-owning firms, followed by Retail, Transportation, Construction, Services, Wholesale, Agriculture, Finance, and Mining. Of equal impor- tance, however, is the fact that of the percentage of plane- owning firms in any given industry to the total firms in that industry, the order is quite different. Agriculture leads the list, followed by Transportation, Mining, Construc— tion, Manufacturing, Services and Wholesale, Retail, and Finance last. Since Manufacturing is one of the most important groups in both listings, a breakdown of the different types of manufacturing is useful. A study by Cessna Aircraft Company found that of the manufacturers maintaining their own aircraft, the largest users were the manufacturers of metal products and the manufacturers of machinery other than electrical. Following these were manufacturers of miscella- neous products, electrical machinery, transportation equip— ment, lumber and wood products, paper products, petroleum products, textiles, stone-clay—glass, and primary metals.23 23The Flyfi g COnceEt, A Reference Study by Industrial Development and Manufacturers Record (Atlanta, Georgia: Con- way Research, Inc., 1965), p. 16. 21 0.6 o.ooa 060.6N H.H o.ooa Hmm.ma o.ooa omm.Noa.H Hmuoa m.m o.NH Nmm_m ~.H h.HH ©06.H o.HH 6NO.HNH muw>umm H.6 m.6 moH.H N.o m.© own m.om mmm.6mm mucmcwm m.m m.ma mmm.6 m.o 0.6a mmm.a h.mH mom.ham meuwm 5.0 n.m ooa.~ N.H o.HH Nmm.a 0.0H >m6.haa madmmaonz 6.~H m.om mom.6 m.m N.ma omo.a 0.6 Nmm.m6 coaumuuommcmus N.N 6.mH mah.m ©.H H.HN mm©.~ o.ma www.moa chHSDUmmscmz h.m H.> nmo.a H.N m.HH ©m6.a ©.© mmm.Nw coauosuumcoo m.oH m.m Rom ¢.m m.m ~46 N.H nao.ma manna: v.6 h.m mmm.m m.6 v.0 N6m @.a mma.ha musuasoaumfi .02 .x. .02 x x. .02 x. .02 mommoamEm Umc3o ummnouwd .mmnoo mEHHm mcowumnomuoo mdonw ooo.oa Hmm Hmuoe mcHCBOImcmam .m.D m>fluo< HmwuumsccH ummnoufim mo mEHHm cmamwucmoH mcac3o ImcmHm mmumum cmuflsb on» now masonm Hmwnu Imswcfi HoflmE ma mEHHm mcHCBOImsmHm 6cm mcowumnomuoo m>wuom cmmzumn mflnmcowumamm .6 mHQMB 22 Any study of general aviation in relation to commu- nity development presupposes a certain importance of one element in regard to the other. In the case of this thesis, the importance of general aviation's influence upon commu- nity development is assumed. This chapter, in effect, attempted to justify that assumption by giving background information supporting and describing the importance of general aviation today. CHAPTER II A STUDY OF COMMUNITY CHARACTERISTICS OF MICHIGAN CITIES Community leaders and decision makers, urban plan- ners and planning consultants, as well as federal, state, and local airport agencies and authorities, are faced with the problem of determining the potential of existing or pos- sible airports if they are to adequately and realistically plan for them. Most airport planning and development in the past has related more to solving existing problems and meet- ing existing needs and demands than to meeting future needs and demands. Much community planning has either ignored the airport or only given passing recognition to it. If in the future we are to have airports and an air transportation system which does not conflict with other elements of the urban community, we must plan for it now. The general aviation segment of air transportation was chosen for this thesis because, as pointed out in the first chapter, it is the largest segment and because it does not include the scheduled airlines. It is in the smaller cities, many of which are without airline service, that general aviation often plays its most important role. It 23 24 is also the smaller cities that most often overlook their general aviation activity. This may be eXplained for the most part, as suggested previously, by the fact that most people equate air transportation with airline service. The objective of this chapter is to identify and examine community characteristics in an attempt to find some which might serve as indicators or guidelines of general aviation activity. These indicators would then be useful to urban planners and to aviation agencies in more effectively planning and coordinating aviation activity and growth with community growth. In order to have some common source of measurement, while at the same time increasing the sc0pe of usefulness, the Egg, Census 2£_Population was used as the source of community characteristics. As mentioned earlier, small cities are most prone to overlook general aviation activity because of a lack of air- line service or scheduled activity. To cover most of the smaller cities, and at the same time keep the project within workable limits, a population range of 2,500 to 50,000 was selected. The lower limit was determined by a population breaking point used by the Census Bureau in categorizing cities and in giving community characteristics. The upper limit of 50,000 was based on a requirement for federal plan- ning assistance. The Urban Planning Assistance Program, as authorized by Section 701 of the Housing Act of 1954, as ammended, provides for federal funds for the planning of 25 incorporated areas less than 50,000 population.24 The pOpulation limits give a workable range for an intitial search of indicators. From the U.§, Census 2£_Population: 1960, all Michigan cities within the selected population range were listed. Since the objective was to establish indicators of general aviation activity, it was necessary that all cities studied have an airport. Accordingly, cities within the population range and without airports were rejected. Second, in order to relate a given city to activity at a given airport, it was necessary to eliminate as many outside influences as possible. All cities with more than one airport were rejected, as were two or more adjacentcities served by only one airport. Cities having their own airport but which were adjacent to or suburbs of a larger city were also rejected because of the difficulty in relating the general aviation activity to the particular city. Table 5 lists the forty—eight cities selected for study. The Michigan Department of Aeronautics, in its avia- tion survey for 1962,25 studied the aviation activity at all 137 of the licensed airports in the state. The forty-eight cities selected for this study were ranked according to their 4"Policies and Requirements for Local Public Agen- cies" (Book III), Urban Renewal Manual (Washington, D.C.: Housing and Home Finance Agency, Urban Renewal Administra- tion, 1960), Pt. 40, chap. 2, sec. 1. 25Michigan Aviation Fact Finder Survey. 26 Table 5. Forty-eight selected cities 1960 1960 City POpulation City Population Adrian 20,347 Iron Mountain 9,299 Allegan 4,822 Ironwood 10,265 Alma 8,978 Lapeer 6,160 Alpena 14,682 Ludington 9,421 Bad Axe 2,998 Manistee 8,324 Big Rapids 8,686 Manistique 4,875 Blissfield 2,653 Marine City 4,404 Boyne City 2,797 Marshall 6,736 Cadillac 10,112 Mason 4,522 Caro 3,534 Midland 27,779 Charlevoix 2,751 Milan 3,616 Charlotte 7,657 Mt. Pleasant 14,875 Cheboygan 5,859 Munising 4,228 Chesaning 2,770 Niles 13,842 Coldwater 8,880 Rogers City 4,722 Dowagiac 7,208 Romeo 3,327 Escanaba 15,391 St. Ignace 3,334 Fenton 6,142 Sault Ste.Marie 18,722 Fremont 3,384 South Haven 6,149 Gaylord 2,568 Sparta 2,749 Grand Haven 11,066 Sturgis 8,915 Hastings 6,375 Tecumseh 7,045 Howell 4,861 Three Rivers 7,092 Ionia 6,754 Traverse City 18,432 27 Total General Aviation Operations as listed in the Fact Finder Survey.26 The cities with their total operations rank (T0) are shown in Table 6.27 In a study making a comparison of general aviation activity at cities of different sizes, it may be expected that to a certain extent the size of the city itself will influence the amount of activity. For example, in a study comparing Lansing, Michigan, to Detroit, Michigan, part of any difference in activity could be explained on the basis of population difference alone. The same would hold true for a comparison of one of the selected cities of this study with 3,000 population compared to one of 25,000 population. In order to minimize this population difference influence when comparing cities, a ranking of operations per person (O/P) was figured by dividing the Total General Aviation Operations at each city by the population of that city. This ranking is shown in Table 6 along with the total opera- tions ranking. As mentioned earlier, the Egg, Census 9: Population was used as the source for community characteristics. From the Michigan census report on "General Social and Economic Characteristics," figures for occupation and industry were 26Ibid., pp. 10-14. 27The term "operation" in aviation basically refers to an aircraft landing or take—off. Total Operations is the sum of all landings and take-offs over a given period of time. 28 Table 6. Selected cities and rankings Rank* Rank*- City TO O/P City T0 O/P Adrian l 13 Iron Mountain 32 38 Allegan 36 34 Ironwood 24 30 Alma 28 31 Lapeer 14 10 Alpena 7 l7 Ludington 30 33 Bad Axe 13 3 Manistee 18 20 Big Rapids 2 6 Manistique 41 39 Blissfield 46 43 Marine City 34 29 Boyne City 44 37 Marshall 20' 21 Cadillac 37 45 Mason 26 16 Caro 29 15 Midland 3 26 Charlevoix 31 14 Milan 8 2 Charlotte 23 27 Mt. Pleasant 9 18 Cheboygan 45 46 Munising 38 35 Chesaning 43 36 Niles 16 25 Coldwater 12 12 Rogers City 42 42 Dowagiac ll 7 Romeo 6 1 Escanaba 33 44 St. Ignace 21 ll Fenton 47 47 Sault Ste.Marie 5 22 Fremont 39 32 South Haven 4 4 Gaylord 27 8 Sparta l9 5 Grand Haven 15 19 Sturgis 25 28 Hastings 48 48 Tecumseh 35 40 Howell l7 9 Three Rivers 22 24 Ionia 40 41 Traverse City 10 23 * TO - Total General Aviation Operations: O/P - General Aviation Operations per Person. 29 taken for each city. Three additional characteristics con- cerning number, income, and education of the population were also considered for a total of twenty-eight characteristics. Characteristics relating to occupation were based on the employed male civilian labor force. Male employment was used rather than total employment because it was listed separately in the census and because of the fact that approx- imately ninety-seven percent of all licensed pilots are males.28 The occupation characteristics are listed in Table 7. The figures for each characteristic used in the analysis represent the percentage of employed males. Industry characteristics were based on the combined employed civilian labor force of both sexes. The figures used in the analysis represent the percentage of total em- ployment. These characteristics are also listed in Table 7. Three other characteristics were selected for consid- eration. Two were based on a study for the Michigan Aeronau- tics Commission which found that the number of aircraft based in a community could be expressed as a function of the population over twenty—five years with some college educa— tion, or as a function of disposable income.29 Census infor- mation most closely corresponding to these findings were 28FAA Statistical Handbook gquviation, pp. 65, 67. 29Interview with Edward A. Mellman, Statistician, Michigan Aeronautics Commission, June 21, 1966. 30 Table 7. Characteristics considered Selected Characteristics 1. Population (number) 2. Percent persons 25 yrs old and over who completed 4 years High School or more 3. Families median income Occupation Characteristics 4. Professional, technical, and kindred workers 5. Farmers and farm managers 6. Managers, officials, and proprietors, except farm 7. Clerical and kindred workers 8. Sales workers 9. Craftsmen, foremen, and kindred workers 10. Operatives and kindred workers 11. Private household workers 12. Service workers, except private household 13. Farm laborers and farm foremen l4. Laborers, except farm and mine Industry Characteristics 15. l6. l7 0 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. Agriculture, Forestry and Fisheries Mining Construction Durable Goods Manufacturing Nondurable Goods Manufacturing (total manufacturing)* Transportation, Communication, and Other Public Utilities Wholesale and Retail Trade Finance, Insurance, and Real Estate Business and Repair Services Personal Services Entertainment and Recreation Services Professional and Related Services Public Administration *This characteristic not listed as such in Census report but used in this study by combining values for Durable Goods and Nondurable Goods Manufacturing. 31 percentage figures for persons twenty-five years old and over who completed four years of high school or more, and the median income of families eXpressed in dollars. The third characteristic of city population was selected to see if in fact there is the relationship between general avia- tion activity and city size which was assumed earlier and which served as the basis for the second ranking of the cities studied. Two methods were used in attempting to identify cer- tain characteristics that might relate to general aviation activity. The first method, referred to as Top lZ-Bottom 12 (T-B 12), considered only the twelve most active cities and twelve least active cities from both rankings. The second method, which was to figure the coefficient of correlation (C of C) for each characteristic, considered all forty-eight cities selected. Both methods were applied to each ranking of the cities and are discussed separately below. Top 12—Bottom 12 Method In the Top l2-Bottom 12 (T-B 12) method, the average value for each characteristic was computed based on all forty-eight cities. The characteristic value for each city of the twelve most active and twelve least active cities on each ranking (TO and O/P) was compared to the average value of that characteristic. A tabulation was made of the cities with characteristic values above the average and below the 32 average of that characteristic. Characteristic values equal to the average were figured as one-half above and one-half below the average. In combining the values of the top twelve cities with those of the bottom twelve cities, an x value representing the sum of the above average figure for the top cities and the below average figure for the bottom cities was determined for each characteristic. Out of a total possible twenty-four, the characteristics with x values closest to zero or twenty-four were considered most related to general aviation activity. Tables showing the x values of the characteristics are given in Appendix A. As an example of the above procedure, take the popu— lation characteristic in Appendix A. The average population of all forty-eight cities was 7,919. Of the twelve most active cities ranked by total operations, eight had a popu- lation above the average while four had a population below the average. Of the twelve least active cities, one was above the average while eleven were below. The x value for population in this ranking (l9), relating population to general aviation activity, was determined by combining the above average figure (8) for the top cities with the below average figure (11) for the bottom cities. This procedure was repeated to determine the x value for each characteris— tic on each ranking. 33 The mean of x values for the twenty-eight character- istics was then figured for each ranking (T0 = 12.32: O/P = 12.34). Assuming a normal distribution around the mean for the x values of the twenty-eight characteristics, the stand- ard deviation for each ranking was figured (2.82 for both TO and O/P). Characteristics with x values in a range covering the central seventy-five percent of the possible x values were excluded as having no significant relation to general aviation activity. Accordingly, only characteristics with an x value equal to or less than nine, or equal to or great- er than sixteen were considered. The characteristics accepted by this method as being related to general aviation activity are shown in Table 8 for both rankings. The characteristic value of indicators found by the T-B 12 method, as described above, was based on the combina- tion of above average and below average figures for the twelve most active and twelve least active cities. The farther the x value from the mean, the greater the relation— ship to general aviation activity. x values of sixteen or larger have a direct or positive (+) relation to general aviation activity, while x values of nine or less have an inverse or negative (-) relation to aviation activity. The x value and relation to general aviation activity are shown in Table 8 for the accepted characteristics. Values for all twenty-eight characteristics are shown in Appendix B. 34 Table 8. Top 12-Bottom 12 indicators Total Operations Characteristic Value Relation* Population 19 + Operatives 6 _ Professional & Related 18 + Managers & prOprietors 8 — Finance & Insurance 8 - Operations/Person Characteristic Value Relation* Operatives 6 - Agriculture, Forestry, & Fisheries 18-1/2 + Farmers & farm managers 16-1/2 + Entertainment 8-1/2 - Professional & Related 16 + Managers & proprietors 9 - it + = direct relation; — = inverse relation. 35 Coefficient of Correlation Method Coefficient of correlation is a mathematical analysis to determine the degree of relationship between two variables. The coefficient of correlation value is expressed as‘g and tells the strength of the linear relation between the two variables considered. Values of.£ may range from +1 to -l. Anig close to zero would indicate a very weak or nonexistant relationship, while a value close to +1 or -1 is indicative of a strong relationship. If one variable tends to increase as the other increases, there is said to be positive correla- tion and £_will have a positive (+) sign. If one variable tends to decrease as the other increases, there is negative correlation and £_wi11 have a negative (-) sign. In using the coefficient of correlation method, the forty-eight cities were listed in order of general aviation activity and in order of characteristic value for each of the twenty-eight characteristics. Using the Spearman for- mula for rank correlation,30 g values for each characteris- tic were figured. Values of‘p for characteristics ranked by total Operations ranged from +.424 to -.385. The range under operations per person was somewhat smaller, being from 30John E. Freund, Modern Elementary Statistics (Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 1960), pp. 346-348: Murray R. Spiegel, Theory and Problems pf Statistics (New York: Schaum Publishing Co., 1961), . 246. The Spearman formula for rank correlation is l-ggd 2 _ l) r: n (n 36 +.375 to -.395. All characteristics with an.£ value greater than +.300 or -.300 were considered to have enough correla- tion with general aviation activity to be termed indicators. These indicators, along with their value and relation, are shown in Table 9. Values for all twenty-eight characteris- tics under each ranking are shown in Appendix C. Table 9. Coefficient of correlation indicators Total Operations Characteristic Value Relation* Population .424 + Operatives -.385 - Managers & proprietors -.378 - Farm laborers .324 + Operations/Person Characteristic Value Relation* Operatives —.395 - Farm laborers .375 + Agriculture, Forestry, & Fisheries .314 + *+ = direct relation; - = inverse relation. 37 Application of Methods The above discussions set forth the methods used in arriving at community characteristics considered to be re— lated to general aviation activity. The resulting character- istics were termed "indicators" of general aviation activity and are proposed as guides for use in study and planning of general aviation facilities in communities within the popula- tion range of 2,500 to 50,000 used in this study. Applica- tion of the indicators is described below. The relation of each indicator to general aviation activity is shown by a plus (+) or minus (-) sign. A plus sign means there is a direct relation between that character— istic and general aviation activity. In other words, a city with considerable general aviation activity should have a value for that particular characteristic above (+) the aver- age characteristic value for other cities in the same class. A minus sign, showing inverse relation, means that a city with considerable general aviation activity should have a value for that particular characteristic below (—) the aver- age characteristic value for other cities in the same class. The average value figures constitute the base from which measurements for each city are taken. The relation, by method and ranking, along with the average or base figures for each indicator, are shown in Table 10. 38 Table 10. Selected indicators and relation to general avia- tion activity Relation* T-B 12 C of C Average of I 1' 1 48 Selected Indicator TO O/P TO O/P Cities Operatives - - - - 23.7% Managers & prOprietors - - - 13.8% Farm laborers + + 0.6% Agriculture, Forestry, & Fisheries + + 1.2% Population + + 7919 Professional & Related + + 15.4% Farmers & farm managers + 0.4% Entertainment - 0.7% Finance & Insurance - 3.E% * + = direct relation; — inverse relation To test the results, each of the nine indicators was applied to the six most active cities appearing on both rankings and the six least active cities appearing on both rankings. A plus sign was given to a characteristic value above the average and a minus sign to a value below the aver- age. Signs for the characteristics of each city were com- pared to the sign it should have according to the indicator and the city's known rank by general aviation activity. 39 (See Appendian, Tables 1 and 2.) The accuracy of the indi— cators applied to the most active cities ranged from a low of 33.3 percent to a high of 77.8 percent with the average being 63 percent. For the least active cities the range was 55.6 percent to 88.9 percent with an average of just over 74 percent. Applied to the twelve cities the indicators aver- aged 68.5 percent accuracy. Various other measurements were made concerning the accuracy of the indicators when applied to the specific cities. In figuring ratios and percentages of the combined accuracy of the indicators, extra weight was given to those indicators which appeared more often than did others (i.e., Operatives appeared four times but Entertainment only once; see Table 10). The weighted average accuracy for the most active cities was nearly 65 percent to over 73 percent accuracy for the least active cities. The weighted average for the twelve cities was 69 percent, only 0.5 percent higher than the non-weighted average. Accuracy of individ- ual indicators ranged from 33.3 percent to 100.0 percent. (See Appendix D, Table 3.) Using the nine indicators, there proved to be very little difference in accuracy based on the two methods of analysis used in the study (68.9 percent for T-B 12, 69.0 percent for C of C). Accuracy based on ranking was somewhat different, however. The ranking by total operations was 40 over 70 percent accurate, while the Operations per person ranking was less than 68 percent. (See Appendix D, Table 4.) An additional comment relating to the study and over- all accuracy might be warranted at this point. Normally when comparing two variables, an.£ value of about 1.600 or larger is considered necessary in order to have a moderate or strong correlation between the variables. In this study it was necessary to use a value of i.300 or larger in order to establish a relation between variables. While the accu- racy of measuring general aviation activity approached sev- enty percent, the inclusion Of those indicators fOund or reinforced by the coefficient of correlation method was based on a fairly weak correlation between the characteris- tic and general aviation activity. Additional study in the area Of determining aviation activity, using the indicators found here and other methods of analysis, such as multiple correlation, may provide stronger indicators of general aviation activity. This does not, however, detract from the value of this study in providing initial indicators and a base for additional study. CHAPTER III INDICATORS OF GENERAL AVIATION ACTIVITY What do the indicators found by the characteristic study of Michigan cities really mean, and do the indicators really relate to general aviation activity? How might the indicators be used by community planners, aviation agencies, and other interested persons or groups? This chapter points out the relationship between the indicators found in Chapter II and the nature Of general aviation as outlined in Chapter I, concluding with an eXplanation of the proposed use of the indicators. Of the twenty-eight community characteristics studied, nine showed a considerable relation to general aviation activ- ity. The nine indicators included four related to occupation, four related to industry, and one of the selected character- istics. The relation of each indicator to general aviation activity, along with the base value of that indicator, is shown in Table 11. As somewhat of a cross check on each of the indi- cators, it is interesting to note that for several areas there is multiple coverage. For example, the area of agri- culture is covered by Farm laborers, and by Farmers and farm 41 42 managers under occupation, and by Agriculture, Forestry, and Fisheries under industry. There is also a definite relation between Managers and proprietors (occupation) and Finance and Insurance (industry). This comparison is relatively easy as the Census Bureau defines what is included in each category under both occupation and industry. Table 11. Indicators of general aviation activity Relation to Base Value Gen. Aviation (Average of Indicator Activity 48 cities) Selected Characteristics Population + 7,919 Occupation Characteristics2 Farmers and farm managers + 0.4% Managers, officials, and proprietors, except farm - 13.8% Operatives and kindred workers - 23.7% Farm laborers and farm foremen + 0.6% Industry Characteristics3 Agriculture, Forestry, and Fisheries + 1.2% Finance, Insurance, and Real Estate - 3.h% Entertainment and Recreation Services - 0.7% Professional and Related Services + 15.4% 1+ = direct relation; — = inverse relation. 2Figures are percentage Of employed male civilian labor force. 3Figures are percentage of total employed civilian labor force. 43 A composite of the general aviation users by occupa- tion and industry, based on Chapter I, is given in Table 12. Comparing the indicators with the general aviation users is more difficult because of the lack of standard definitions. However, because Of the similarity of some terms with those used by the Census Bureau, and with some general knowledge of the fields associated with the terms, it can be assumed that there is a relation where there is a similarity in terms. Table 12. General aviation users by occupation and industry Occupation Industry 1. Manufacturing 1. Transportation 2. Professional 2. Manufacturing 2. Construction/Engineering/ 3. Agriculture Architecture 4. Construction 4. Transportation/Communication/ Public Utilities 5. Retail 5. Retail 6. Services 6. Farming & Agriculture 7. Mining 7. Finance/Real Estate/Insurance 8. Wholesale 8. Service 9. Finance 9. Wholesale 44 In comparing the indicators (Table 11) to the compos- ite of general aviation users (Table 12), it is apparent that the indicators do have some relation to the users. For example, there is a definite relation under occupation between the indicator Managers and proprietors and the Retail, Service, and Wholesale users. This is especially true when it is remembered that over fifty percent of the users are employed in a management capacity. Farming and Agriculture users are covered by the indicators Farm labor- ers, and Farmers and farm managers. The relationship between users and indicators under industry is not quite so evident. The most obvious relation- ships are in the fields of agriculture and finance. Based again on the high ranking of persons employed in a manage- ment, professional, or technical capacity, it seems reason- able that there would be an industrial relation between the indicator Professional and Related Services, and Manufactur- ing users. To summarize the community characteristics as they relate to general aviation activity, it might be said that a community with a high percentage of employment in agricul- ture occupations and agriculture and professional industries is more likely to have a high level Of general aviation activity. Communities with a low percentage Of employment in proprietary and Operative occupations and in finance and entertainment industries are also more likely to have a high 45 level of general aviation activity. According to this study then, communities with these combined characteristics would, in all probability, have a significant amount of general aviation activity or potential activity and should have adequate consideration given to general aviation and its effect on their future development. Recognizing that there is some relation between the indicators and known general aviation users, we turn now to an explanation of how the indicators might be applied to various cities. Each indicator has a base value and a sign showing its relation to general aviation. A positive sign shows that the indicator is directly related to general avia- tion, and the value of a corresponding characteristic for a given community should be above the base value in order to have potential general aviation activity. Conversely, a negative sign shows that the indicator is inversely related to general aviation, and the value Of a corresponding char- acteristic should be below the base value in order to have potential general aviation activity in the city. Table 13 gives four hypothetical cities and charac- teristic values corresponding to the indicators. Cities A and B will serve as examples of the use of the indicators to community planners. City A presently has an airport but little or no present aviation activity. In applying the indicators to the city, there is nearly eighty-nine percent accuracy, indicating a potential general aviation activity 46 RB: R000 R~.m~ R000 6333 + Rm.ma Ra.~m : RM.HH RH.0H + R6.ma Omumaom w Hmaoammmmoua + Rm . 0 RH . H + R0 . 0 R0 . 0 . RR . 0 “$630305 u Rm.~ RDN + Rmé Rozm .. Rim 80353 a 8:ng + Rm; R54 + R64” RmJ + Rm; 3:233 .0 .muummuom .mnfluasuqumm + Rm.0 R50 .. R64 R50 + R00 3300.3 5mm + Roam Rm.mm + RDmm RNA: 1 RDmm mmfiumummo u RTE R23 + R93 R93 u R93 33380.6 a 352...: + Rm.0 Rm.0 + Rmé Rm.0 + R00 mummmama 53 a 39580 + 00~.0H 00m.HH . 00~.m 000.5 + 0H0.R coaumHsaoa cmam Ozam> swam mdam> cmflm Ozam> swam m5am> soap mDHm> HoumoHUcH ImHmm mmmm o 36 o 36 m 36 a 8.3 mucumoflccw mo coaumowammd .MH OHQMB 47 exists. Since the planner would probably be concerned only with his city, population would be a factor only to the extent that it is increasing or decreasing. If it is rap— idly increasing, and may soon be over the base value of the indicator, the total accuracy would improve to one hundred percent (assuming no changes in the other characteristics). If the planner knew Of trends changing the composition of the city, he would also know if the potential was increasing or decreasing. City B, on the other hand, is quite different, being like City A only in the fact that it too has an airport and little present activity. The indicators applied to it show an accuracy of only twenty-two percent, indicating little potential activity. Here again, the planner or planning consultant, knowing the changing trends of the city, would be able to estimate what influence general aviation might have on airport and community growth. Cities C and D help point out possible use of the indicators by an aviation agency, such as a state aeronau- tics commission. They have the problem of allocating funds in such a manner as to best serve aviation. If two cities appear on the surface to be equal in all respects, yet there are funds only for the improvements at one, the use of the indicators may help determine which city should have the funds first. 48 Application of the indicators to Cities C and D pro- duce an accuracy of approximately eighty-nine percent and seventy-eight percent, respectively. At first glance it would appear that the money should go to City C as it has the greater accuracy or potential. On closer examination, however, the accuracy difference lies primarily in the value of the Operatives characteristic. City D is only one-tenth of one percent from the indicator base value and three- tenths of one percent from the value of City C. Disregard- ing Operatives as an indicator in this particular case, the two cities would have the same level of accuracy. Since population is also an indicator, and benefit tO most people may be a criteria for spending state money, City D might get the nod as it is considerably larger than City C and farther from the indicator base value. It may be concluded then, that the indicators of general aviation activity arrived at in this thesis are related to general aviation users. Other considerations, not within the sc0pe of this present study, however, should not be overlooked. Such factors as travel time and distance of the airport from the center of population, and the rate of change of a characteristic value from one year to the next may also be important and helpful in determining poten- tial general aviation activity. 49 As the examples in this chapter point out, the indicators could be useful to community planners and to aviation agencies when used in the manner described. Of greater importance, however, is the hOpe that this study may re-emphasize an area largely ignored by planners, and in doing so serve as a base for an improved method of studying and relating aviation activity and growth to the planning of our cities. APPEND ICES 51 L Q. 0 mm mHH 6H 0H 0H HH HH H “R 0H 0H NH 3 w Wm m .m I 3 “EH “RH 0H 0 «H 2 2 0 “SH 0H 6H NH HH x - w _ m. mmmum>mn. o I. 0 0H m0 m m 0 m 0 .6 m m R O m 033%. mm m m MHO>M m / m m m... 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T. 8 T: 8 S . E E T. U 1. . 9 S T. U..1 I. rte 1 o u 1.8 s e D o 1 u a D E S 1. u n3 D T. S d T. O O I 5 I H 1.8 E E 8 E O O D. n 1.0 V Her. I. T. H T. 1 W D. s 3 H01 m. D. O W a no a 1. 1.. S 1. S . u S .d e 6 W I. . T. E a a E I n4 1. . W T: O u T. U I I. u I. (\ I. .b u n. o 1- A I ma m rm“ 0 UOSGHHCOUllfi NHQZWQQfi POP r... I! N. Cg IECb (I TL C Ck APPENDIX B CHARACTERISTIC VALUES (T-B 12 Method) TO Rank Value O/P Rank Value Population 19 Operating 6 Operatives 6 Ag.,For., & Fisheries 18% Professional & Related 18 Farmers & farm mgrs. 16% Managers & proprietors 8 Entertainment 8% Finance & Insurance 8 Professional & Related 16 Other laborers 15% Managers & proprietors 9 Farm laborers 15 Farm laborers 15% Wholesale & Retail 15 Other laborers 15 N.D. Goods Mfg. 10 Wholesale & Retail 15 Public Admin. 10 N.D. Goods Mfg. 10 Sales 10 Public Admin. 10 Personal Services 14% Business & Repair Serv. 10 Entertainment 10% Professional & technical 10 Clerical 14 Household 10 Mining 14 Family income 14 Transportation 14 Craftsmen 14 Farmers & farm mgrs. 11 Construction 14 Family income 11 Population 11 (total manufacturing) 11 Finance & Insurance 11 Ag., For., & Fisheries 11% (total manufacturing) 11 Education 13 Personal Service 13% Business & Repair Serv. 13 Mining 11% Professional & technical 12 Sales 13 Craftsmen 12 Clerical 13 Household 12 Education 12 D. Goods Mfg. 12 D. Goods Mfg. 12% Construction 12% Transportation 12% Service 12% Service 12% 54 APPENDIX C CHARACTERISTIC VALUES (C of C Method) TO Rank £_ O/P Rank .5 Population .424 Operatives -.395 Operatives -.385 Farm laborers .375 Managers & proprietors -.378 Ag., For., & Fisheries .314 Farm laborers .324 N.D. Goods Mfg. -.270 Mining .254 Professional & Related .252 Clerical .202 Other laborers .240 Professional & Related .159 Managers & proprietors -.210 Service .137 Service .198 Professional & tech. .137 Farmers & farm mgrs. .182 Craftsmen .129 Personal Service .178 Other laborers .126 (total manufacturing) -.159 Household .112 Craftsmen .142 N.D. Goods Mfg. -.110 Mining .134 Finance & Insurance -.108 Population -.131 Farmers & farm mgrs. .102 Construction .129 Wholesale & Retail .078 Sales .119 Entertainment -.067 Entertainment -.115 Family income .066 Wholesale & Retail .098 Personal Service .064 Public Admin. .094 (total manufacturing) -.054 Transportation -.082 Education .048 Clerical .077 D. Goods Mfg. —.045 Business & Repair Serv.-.060 Construction .031 Professional & tech.‘ -058 Public Admin. -.031 Education .049 Ag., For., & Fish. .028 Family income .025 Sales -.020 Finance & Insurance -.021 Business & Repair Serv.-.003 D. Goods Mfg. -.011 Transportation —.001 Household .001 55 cowumamm R0.RR Rfi.00 Rfi.mm R0.00 R0.RR Rfi.00 humusoo< :0.N um.N um.N :0.H :6.N +N.m I RH.m mocmnsmcH 0 mocmcflm. 10.0 16.0 +H.H 10.0 +H.H +m.H I _$R.0 ucmacflmuumucm +004.- +moo 000 000 moo ¢oo + O\Odoo mummmcmg I I + I 8000 w meEHmm +H.Hm IR.0 10.0H +0.0m +N.RH +0.6m + + R6.0H cmumamm 0_Hmcowmmmmonm +0000 I00NR Im6H0 I0H0m IRNmm +0000 + + mHmR soaumHsmom 0.H 0.0 0.H IR.0 0.0 0.H + + RN.H mmflumnmam + + + + + 0 .wuummnom ..m« 10.0 +H.N 10.0 I6.0 +0.0 +0.H + + $0.0 mnmuoan EH00 +6.6H 16.0H Im.mH IH.HH 10.0 10.0 I I I .fi0.mH muoumflumonm w mummmcwz um.HN +6.0N +R.0N IN.mH IR.0N -0.0H I u n . RR.NN mm>Humumao H0003 DammMBOQ cm>mm cmaflz 00800 moflmmm 0R0 OB MNO OB 05Hm> ;10Hoo nusom 0H0 6 00 O NH mus mmmm mMHBHU W>HBO¢_NHm 4H mam¢e Q NHQmemd 56 R0.00 R0.RR R0.00 R0.00 R0.RR Rm.00 mO0HSOO¢ 0.6 6.0 0.0 0.0 0.H 0.0 I RH.0 moc0HSmsH + + I + I + w 0000GHm IN.0 IR.0 +6.H +0.0 I6.0 +0.H I RR.0 HamecH0uHmucm +HOI—H '00. IMOO +000 '00. I... + XVOO mhwmmcmg EH00 0 mHmfiH0m I0.0H IN.6H I0.NH I0.6H I0.NH +0.0H + + R6.0H 00H0H00 0 H0sowmmmMOHm ImRm0 INaHm Immmm ImmoN INNRa IemRo + + mHmR aoHumHsmom +0.H I0.0 +0.0 I0.0 I~.0 I~.0 + + RN.H mmHHmanm 0 .mHHmmHom ..m¢ lm.O lm.O +0.0 I... I... I... + + $0.0 mHOHOQMH EHmm Im.mH Im.R +m.0N +N.mH R.mH +¢.mH I I I R0.mH mHoumHHaoum + 0 mHmm0c0z 0 I 0 o o o o | I. I ' 00 O Q IR 0H +0 00 I0 0H +0 00 +0 00 +0 60 \R mm mm>Hu0Hm 0 mmcH coucmm G0mmonmnu 0H0Hm muHO 0HcoH m\o OB m\O OE 05H0> l m lmm m u 00 HHm mHo om O 00 O NH mIe .mmmm cowumHmm mmHBHO m>HBO¢Izoz me .m mqmde 57 TABLE 3. ACCURACY OF INDICATORS APPLIED TO CITIES Six Cities* Six Cities* (active) (non-active) Combined Indicators ratio % ratio % avg. % Operatives 16/24 66.7 16/24 66.7 66.7 Managers & proprietors 15/18 83.4 12/18 66.7 75.0 Farm laborers 6/12 50.0 10/12 83.4 66.7 Ag., For., & Fisheries 10/12 83.4 8/12 66.7 75.0 Population 4/12 33.3 12/12 100.0 66.7 Professional & Related 8/12 66.7 10/12 83.4 75.0 Farmers & farm managers 3/6 50.0 4/6 66.7 58.3 Entertainment 3/6 50.0 3/6 50.0 50.0 Finance & Insurance 5/6 83.4 4/6 66.7 75.0 Weighted avg. of 9 Indicators 70/108 64.8 79/108 73.2 69.0 Non-weighted avg. of 9 Indicators 34/54 63.0 40/54 74.1 68.5 *Accuracy of active cities measured by city's Char- acteristic with sign corresponding to that Of indicator: non-active cities measured by city having Characteristic sign opposite that of indicator. 58 TABLE 4. ACCURACY OF INDICATORS BY RANK AND METHOD (figures in percent) Six Active Cities Rank Method Combined TO 0Q TO 66.7 66.7 T-B 12 O/P 66.7 64.8 C of C TO 58'3 61.9 O/P 66.7 wt. avg. 62.9 66.7 Six Non-Active Cities Rank Method Combined m O/P TO 76.6 T-B 12 71.2 66.7 O/P 73.2 C of c To 79'2 76.2 O/P 72.2 wt. avg. 77.8 68.5 Rank Method _._.._.__..__. Com... TO O/P T-B 1; COfC bined Six Active Cities 62.9 66.7 -66.7 61.9 64.8 Six Non-Active Cities 77.8 68.5 71.2 76.2 73.2 Combined 12 Cities 70.3 67.6 68.9 69.0 69.0 BIBLIOGRAPHY BIBLIOGRAPHY‘ Printed Sources "An Aviation Subdivision," Urban Land, XXIV (February, 1965), 9. Business Flying. Special Report 66-4. Washington, D.C.: National Business Aircraft Association, Inc., 1966. Dinning, R. G. "Integration Of Airport and Municipal Planning," Journal 9f the American Institute 2: Planners, XIX (Summer, 1953), 124-130. FAA Statistical Handbook 2: Aviation. Washington, D.C.: U.S. Government Printing Office, 1965. The Flyjlp Concept. A Reference Study by Industrial Development and Manufacturers Record. Atlanta, Georgia: Conway Research, Inc., 1965. Freund, John E. Modern Elementapy Statistics. Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 1960. General Aviation and Its Relationship 39 Industry and the Community. Jamaica, New York: Federal Aviation Agency, Eastern Region, Airports Division, 1964. General Aviation-~Today and Tomorrow. Transcript of Conference-Briefing. Washington, D.C.: Utility Air- plane Council of Aerospace Industries Association, 1965. Geuting, Joseph T., Jr. General Aviation: What lt_l§ Egg Why Important £9_Ygu. Speech given at NAEC Annual Meeting, Miami Beach, Florida, July 10, 1963. (Mimeographed.) Hesse v. Rath, g; 31., 164 Northeastern Reporter, p. 342, December 7, 1928. Reprint Obtained from Piper Aircraft Corporation, Lock Haven, Pennsylvania. The Men Who Buy New Private Airplanes. Research Report 1302. New York: Time Marketing Information, 1964. 60 61 Michigan Airport Directory. Lansing, Michigan: Department of Commerce, Michigan Aeronautics Commission, 1966. Michigan Aviation Fact Finder Survey. Lansing, Michigan: Michigan Department of Aeronautics, 1963. National Airport Plan: Fiscal Years 1966-1970. Washington, D.C.: Federal Aviation Agency, Airports Service, 1965. New Pilots. A Survey of the Individuals Obtaining Pilot's Licenses in 1963. Research Report 1301. New York: Time Marketing Information, 1964. Parrish, Robert L. "General Aviation 1966," The AOPA Pilot, IX (March, 1966), 27-30. "Policies and Requirements for Local Public Agencies" (Book III), Urban Renewal Manual. Washington, D.C.: Housing and Finance Agency, Urban Renewal Administration, 1960. Profile 2f_Flying and Buying. Washington, D.C.: The Air- craft Owners and Pilots Association, 1965. Proxmire, William. "Significance of General Aviation to the National Economy," U.S. Congressional Record, Senate, 1962. Reprint Obtained from Piper Aircraft Corporation, Lock Haven, Pennsylvania. Spence, Charles. "Airports Are for People Who Don't Fly," The AOPA Pilot, IIX (September, 1965), 28—29. Spiegel, Murray R. Theory and Problems Of Statistics. New York: Schaum Publishing Company, 1961. U.S. Bureau Of the Census. "General Population Characteris- tics, Michigan." Final Report PC(l)-24B. Egg, Census .9: Population: 1960. Washington, D.C.: U.S. Government Printing Office, 1961. ’ U.S. Bureau of the Census. "General Social and Economic Characteristics, Michigan." Final Report PC(l)-24C. ggg, Census Q: Population: 1960. Washington, D.C.: U.S. Government Printing Office, 1962. 62 Other Sources Michigan Aeronautics Commission. Personal interviews with William E. Hamlen, Chief of Planning, Engineering Division. Spring, 1966. Michigan Aeronautics Commission. Personal interviews with Ward J. Mayrand, Aviation Information Supervisor. Spring and Summer, 1966. Michigan Aeronautics Commission. Personal interviews with Edward A. Mellman, Statistician, Engineering Division. Spring and Summer, 1966. MICHIG GAN STATE UNIVERSITY LIBRARIE IIIII III I III I|I||I IIIIII I IlII