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TCRP H-12 Final Report 3.0 EMPIRICAL FINDINGS AND IMPLICATIONS FOR MODELING 3.! Introduction This chapter reports Me results of a review of the empirical literature on the transportation land-use interaction, at both We "macro" level of urban fonn (density of development, overall urban structure, etc.) arid the "micro" level of loch area design. The objectives of this review are: to identify our current state of knowledge concerning the transportation - land-use interaction, particularly with respect to the impacts which various land-use and transportation policies are likely to have on the system, to identify gaps in our understanding (i.e., areas in which eve are unsure of the direction/magn~tude of policy impacts), as a guide to fiercer research. arid to discuss We implications of these findings for the development and application of integrated transportation - land-use models. The recent series of reports by Parsons Brinkerhoff. Quade arid Douglas Inc. (PBQD) tI995, 1996a, 1996b, 1996c] provided art excellent starting point for this study, as well as a comprehensive review of the literature up to 1994. Thus. although studies up to ~ 994 are also reviewed in this report, greater emphasis is placed on the more recent studies which have been published since ~ 994. The review is divided into two main parts. The first reviews the empirical literature on the impact of urban form on Gavel behavior. The second then considers the problem from the other Ejection by examining the evidence concerning the impact of transportation fin particular. transit) on urban form. Deviled results from the review are presented in Appendix A. Section 3.2 of this chapter surnmanzes these results with a focus on their implications for the design and use of integrated urban models. 3.2 Implications for Integrated Transportation - Land-Use Models 3.2.1 Impacts of Urban Form on Transit Table 3. ~ attempts to summarize the empincal evidence conceding urban form impacts on Ravel which is discussed In greater detail in Appendix A. To bnug some structure to this summary, the table is divided into four main categories: residential density impacts, employment density impacts, accessibility impacts, arid neighborhood design impacts. The first three of these categories can be thought of as "macro" properties of urban form, while the fourth is intended to capture more - 27

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TCRP H-17 Final Report Table 3.! Summary of Empirical Evidence Concermng Urban Form Impacts on Travel (a) Residential Density Impacts Transit demand function of: she of downtown, distance from downtown, residential density Transit use increases sharply when residential density goes from 7-16 dwelling un~ts/acre 1973 NETS data -- density does not explain . . . . much variance In transit usage, soc~o-econom~cs more important . [PusDkarev & Zup an, 1977, 1980; pg. 177] [Smith, 1984, pg. 177] [PMM, 1975. pg. 177] 1990 NETS data -- threshold for relationship [Levison & Kumar, 1994, pg. 177] between density & mode choice is 10,000 persons/sq.mi. 1991 FHWA Highway Statistics -- urban regions with higher densities generate higher transit trips per capita and less VMT per capita, trends hold when analyzed at the zonal rather than regional level; total trip rates do not vary substantially with density Households in higher density neighborhoods have lower auto ownership levels (after controlling for income); people with fewer cars use transit more and generate less VMT; net density effects, however, are generally small In practical terms Density has negligible impact on travel behavior (except with respect to auto ownership) once accessibility is accounted for Higher densities, in combination with neighborhood design, reduce trip rates & encourage non-auto travel tDunphy & Fisher, 1996, pg. ~ 78] [Shimek, 1996b, pg. 179] ~Kockelman, 1997, pg. iS0] [Cervero & Kockelman, 1997, pg. ISi] - 28

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TCRP H-12 Final Report Table 3.l, cont'd Higher residential densities, combined win greater concentration of employment In the CBD & inner suburbs, plus socio-economic differences, contribute to higher transit mode splits In Toronto relative to Boston 1985 American Housing Survey Data -- density has a significant Impact on work trip auto and transit mode shares; this Impact is greater than the land-use mix impact Increased density, combined win mixed land-uses, reduced auto ownership levels and commuting distances Density greatly influences commuter mode choice, transit Hip rates and rapid rail boardings. much more so man urban design or land-use mix Rail access walk mode shares affected by neighborhood density and land-use mix; the distances walked, however, are not; rail access transit mode share primarily affected by transit service levels and not density/land-use mix per se Catchment areas for rail stations vary with density of development Density affects auto ownership, which, In turn, affects transit ndership Density does not directly affect commuting VMT/worker Residential density near commuter rail stations not significant in explaining choice of walk access mode, once socio-economic factors properly [Schimek, 1996a, pg. 1811 ECervero, 1996, pg. IS4] [Cervero, 1996, pg. 184] [PBQD, 1996a, pg. 186] EPBQD, 1996c, pg. 187] [PBQD, 1996c, pg. 187] [Messenger & Ewing, 1996, pg. 189] [Miller & Ibrah~m, 1998, pg. 189] [Loutzenheiser, 1997, pg. 192] - 29

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TCRP H-12 Final Report Table 3~l, cont'd (b) Employment Density Impacts Increased concentration of employment in CBD & inner suburbs contributes to higher transit modal shares Employment density thresholds exist for modal shifts from SOV to transit/walking: 20-50 employees per acre -- moderate shifts; > 75 employees per acre -- significant shifts Station area employment density influences commuter raid boardings Suburban employment centre density affects work trip mode split The larger the size of a suburban employment center, the more potential exists for ride-shar~ng (ride sharing increases by 3.5% for every 5000 jobs) (c) Accessibility Impacts Accessibility an unportant determinant of VMT and mode choice A stronger relationship between mode choice and urban form exists when both ends of the trip are considered Increases in both "local" and "regional 't accessibility results in shorter shopping Hip distances, but no reduction in shopping trip frequency . Residences and commercial areas must be close and barriers [Schimek, 1996a, pg. ISI] [Frank & Pivo, 1994 pg. ISI] [PBQD, 1996a, pg. IS6] [Cervero, 1989, pg. IS6] [Cervero, 1989, pg. IS6] [Kockelman, 1997, pg. IS0] [Frank & Pivo, 1994, pg. 181] tHandy, 1993, pg. IS2] tHandy, 1995, pg. 183] - 30

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TCRP H-12 Final Report Table 3.l, cont'd Increased employment In the Toronto central area offset by Increased residential development, resulting in little net growth In peak-period connoting into the central area Commuting cost (and hence jobs-hous~ng balance) has little Impact on residential location choices in Los Angeles region Jobs-housing balance, In combination with auto ownership level and transit service level, affects transit mode split VMT/worker increases with distance from the COD and/or other major employment centres; jobs-hous~ng balance has little impact on VMT/worker Good regional accessibility to activities is more important Can localized density or use Iriix In reducing vehicular travel; iobs-hous~n~ balance has little , .~ , I. Impact on vehicular travel, but accessibility of residences to a range of land-uses does reduce vehicular travel Distance from home to store Important in Me choice of destination for walk shopping trips (~1) Neighborhood Design Impacts Comparison of new, mixed land-use comrnun~ties with "semi-planned" traditional suburbs -- no significant difference in VMT or transit usage, except for recreational trips Pre-war, traditional comrnun~ties versus standard, post-war suburbs: transit use & walking significantly higher In traditional communities; total trip rates and auto-driver trip rates [Nowlan & Stewart, 1991, pg. 188] [Giuliano & Small, 1993, pg. lSS [Messenger and Ewing, 1996, pg. ~ 89] [Miller & Ibrahim, 1998, pg. 189] [Ewing, 1995, pg. 190] tHandy, 1996b, pp. 191] [Burby, et al., 1974, pg. 178] [Friedman, et al., 1994, pg. 178] - 31

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TCRP H-12 Final Report Table 3.l, cont'd Land-use mixing, land-use balance and accessibility important in detennining VMT, auto ownership and mode choice [Kockelman, 1997, pg. 180] Land-use diversity & pedestrian-oriented tCervero & Kockeknan, 1997, pg. iS1] designs reduce trip rates & encourage non-auto travel Travel behavior depends on the nature and range of travel choices available within a neighborhood, rather than on the "neighborhood design" per se (e.g., "new" versus "old") M~xed-use development Is more important than density in affecting non-motor~zed work trip mode shares Neighborhood design variables have little impact on work trip mode choice, although a "traditional neighborhood" dummy variable showed some statistical significance Land-use mix affects work trip mode choice In suburban office centers Neighborhood type not statistically significant in explaining travel behavior once socio-economic factors are accounted for Individual motivations and Imitations central to the decision to walk; urban fonn then encourages or discourages walking, given the motivation to do so [Handy, 1995, pg. iS3] [Cervero, 1996, pg. 184] [PBQD~ 1996a' pg. 186] [Cervero, 1989' pg. 186] [McNally & Kulkarni7 1997' pg. 188] [Handy' 1996b' pg. 191] 'micro" considerations of neighborhood design. It is recognized however that the distinctions ~ , , between these categories tespeclally the last two) can' at times' be fairly arbitrary. For each paper reviewed in Appendix A, a very brief summary of key findings is presented, alters with the paper citation. Since these summaries may often not do justice to the nuances of the papers' findings, the

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TCRP H-12 Final Report number of the page where each paper is first discussed in Appendix A is also shown, so that the reader Carl refer back to the more detailed discussion of Me paper if so desired. Despite Me diversity of results presented in this long table several generalizations, "working hypotheses", etc. can be drawn from this review. These are itemized and discussed briefly below. 1. Residential density. The empirical evidence concerning Me role which residential density plays in the determination of transit usage (as well as the use of non-motorized modes of travel such as walk and bicycle) is very mixed. The debate concerning the role of residential density in determining urban transportation "efficiency" or "sustainability" is one which has been ongoing within the urban and transportation planning communities for some time. The "pro density" argument is often associated with the work ofKenworthy end Newman [1989], among others, in which density seems to be the single most important factor explaining macro differences in transportation energy use, etc., among cities. Many other studies however, including several cited in this review, find the evidence much less clear. In particular, the role of density as a direct explanatory variable with respect to transit usage, auto VMT, etc. typically declines significantly within the statistical analyses once "other factors" such as socio-economic characteristics of the trip-makers, accessibility by mode to destinations, auto availability, etc. are accounted for te.g., PMM, 1975; Kockelman, 1997; PBQD, ~ 996c, Messenger and Ewing, ~ 996; Loutzenheiser, ~ 997; Miller and Ibrahim, ~ 9981. This issue is pursued in more detail in the following discussion of these "other factors". 2. Transit supply. Relatively few studies explicitly include measures of transit supply in their analyses of urban form impacts, presumably due to data limitations. As noted above, however, when such variables are included in the analysis, they often are found to play a significant role in explaining modal choices, VMT levels, etc., and to reduce the explanatory power of density measures within Me analysis tPBQD, ~ 996c]. In order to understand this result, one must note that a classic demand-supply relationship exists between factors such as residential density and transit service levels. That is, the better the transit service, the more people will use it, the more people potentially available to use a given service, the higher the level of service which can be cost- effectively provided. Figure 3.~(a) illustrates this relationship between potential transit demand arid the supply of transit service. The demand curves Do, etc., represent the potential demand in different corridors, which is presumably determined by factors such as their densities, accessibilities by transit to desired destinations, population socio-economic attributes, etc. The "supply curve", S. represents a simple "scheduler's rule"; i.e., a simple model of the transit agency's scheduling process as a function of expected demand. The points of intersection between the supply curve S and the various demand curves, D, represent the equilibrium ridership levels that result from the transit agency's decisions on how much service to supply in each comdor arid travelers' responses to these service decisions.

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TCRP H-12! Final Report Figure 3.! Transit Demand-Supply Relationships ._ - . _ o ;^ - . ct a ._ u, sit .~ o - ._ cot / - ~/ / / D4 D3 D2 -- D1 Number of Daily Bus Runs (a) Transit Ridership and Service Supply - Demand Relationships (aclapted from Gonzales, 1980) Combor Residential Density (b) Transit Ridership Density Relationships Implied by Figure 3.l (a) - 34

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TCRP H-17 Final Report Assuming Mat average condor density is one of the determinants of the demand curves, the equilibnum demand levels can be replotted versus average corridor density, as illustrated in Figure 3.~(b). While this figure is completely hypothetical. it does represent a plausible relationship ~ , . _ _ ~ ~ , , ,: , , ~ between ndership and density. In particular. it is consistent with the "threshold effects" which are reported with some consistency in the literature te.g.. Pushkarev and Zuparl, 1977, 198O, Smith, 1984; PMM, 1973], in which transit usage is found to increase dramatically once certain density thresholds are exceeded. At least two important points relevant to the current discussion can be drawn Mom Figure 3. ~ . First, and most fundamental note that the points shown in Figures 3. ~ (a) and (b) do not trace out the demand curve for transit as a function of either Posit service level or residential density. Rather, the pouts in Figure 3. ~ (a) trace out the transit operator's supply curve. while the specific shape of the curve described by the points in Figure 3. ~ (b) depends upon the equilibrated supply responses ofthe transit operator, along with all the other factors relevant to Me determination oftransit demand (auto ownership levels, population socio-economic attributes, etc.). Identification of the transit demand function (and, thereby, determination ofthe "true" relationship between ridership and service levels, density, etc.) requires explicit consideration of both the demand arid supply processes ~ d Me inclusion of the relevant variables associated with each of these processes -- within some form of"simultar~eous equations" analysis. In the absence of such a comprehensive, simultaneous analysis the results are inevitably subject to ecological fallacies. aggregation errors, etc. of unknown but potentially major proportions, rendering the models armor policy implications drawn Mom such partial analyses extremely suspect. Again, to take the hypothetical but realistic case of Figure 3 . I: Fissure 3. ~ (a) does not provide us with a basis for predicting hove ndership in any of the four corridors being modeled (let alone any other corridors not included in the base data) will respond to a change in transit se} vice level. Similarly, Figure 3. ~ (b) does not provide a reliable basis for predicting how- density- changes within a corridor might affect transit demand, since the details of this curve are based upon the combination of a wide range of factors, which cannot be expected to extrapolate readily to other situations. A second. much more minor point to draw Dom Figure 3. ~ (a) relates to the relative statistical significance of variables such as transit se - -ice level and density in explaining observed travel behavior. In such a situation it is not surprising that if one regressed transit demand (or any other equivalent measure, such as auto VMT) versus transit service variables and density (among other factors). density would not appear to be overly significant given that the relationship being traced by the data points is between eldership arid service level, with density entering the relationship orgy indirectly (via the supply-demand relationship discussed above). 3. Auto ownership. One quite consistent finding in the literature reviewed is that households in higher density neighborhoods tend to own fewer vehicles, and that households owning fewer cars then tend to use transit more Ad generate less VMT tShimek, 1996; Kockelman, 1997; Cervero,

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TCRP H-12 Final Report 1996; Messenger and Ewing' 1996]. The role of auto ownership within the overall transportation - land-use interaction is often overlooked. This may reflect the assumption that auto ownership in many portions of the United States is so high arid so pervasive that it ceases to be an ~nteresi~ng explanatory (or policy) cleanable. It may also result Tom the view Mat auto ownership is just one more socio-economic descriptor of trip-makers. determined largely exogenously to the travel decision-making process. In our view, these assumptions significantly underestimate the extent to which auto ownership decisions are integral to the transportation - land-use interaction. In particular, auto ownership is a critical "intermediate link" between household location choices (where to live, where to work) and their subsequent activity/trave} decisions. Households who choose to live and/or work in low density suburban areas wall of necessity (if not also preference) be "auto oriented". tend to have a high auto ownership levels and make most if not all DIPS of any significant distance bY auto. ~, TY ~1 1 1 ~ 1 ~1 1 ., , 1 Households Who live anchor work In denser, trans~t-onenteo communities (where the transit- orientation arises from the trar~sit/lar~d-use Interaction discussed above), may opt to own fever cars (east., only one instead of two or more). Once a household decides to own, say, one less car, it by necessity is committed to driving less and using other modes of travel (transit, warm more, if it is going to maintain a comparable level of activity. relative to a household which owns that "extra" car. Thus as in the transit service case previously discussed, a proper specification of the urban form travel demand interaction requires including auto ownership as an endogenous component of the system. , ~ . , ~ , . In add~i~om it is worm noting that marry policy issues of current relevance (hoar carbon taxes to vehicle technology options) have direct or indirect Contacts on vehicle ownership decision-makinc. A. . . . .. .. , ~ . . .. , , l his Adam Implies the need tor ~nciuct~ng auto ownership as an endogenous mode] component, so that the mode! can adequately respond to these types of policies. 4. Socio-economics. It is not in the least surprising that socio-economic factors (over and above auto ownership' discussed above) such as income, age, gender. occupation, etc. have a sigmficant impact on travel behavior tPMM, 1975; Schimek' 1996b. Loutzenheiser, 19973. It is well known that people's travel needs and capabilities vary dramatically by- such factors. Indeed, the primary reason why most current travel demand modeling methods (e.~., random utility models; activity- based models) are developed at the disaggregate level of the individual tup-maker is so that they can properly capture the diversity of behavioral responses which occur among different types of people. Two points need to be made concerning the role of socio-economic factors within integrated urban models. First, as with Me other factors discussed above it is the interaction between socio- econorriics and urban fonn which is central to the urlderstanding and modeling of people's locational and activity/~ave} decision-making. Different people will respond to different density levels/urban designs in different ways. It is, therefore, not a question of "which is more important", density or - 36

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TCRP H-17 Final Resort socio-economics. In explaining behavior. Rawer, it is a question of understanding how behavioral responses to chances in density, etc. will vary by socio-economic characteristics. Second, given the importance of socio-econom~c factors, it is imperative that they be explicitly represented within our modeling. systems, and that our models be sufficiently disaggreaated to properly capture their effects .. ., . . ~. , . _ - ^^ . This implies the need to include within model systems explicit representations of demographic arid economic process. A strong case can be made that one of the reasons why- many advanced disaggregate modeling methods have not yet achieved wide-spread adoption within operational planning contexts is the inability to predict credibly the detailed socio-economic attributes which they require. S. Employment Density. Employment density impacts have not been investigated to the same extent as the residential density case. The reported findings, however, are quite consistent: increased employment concentrations do have significant impacts on transit usage, walking (where feasible) and ride-sharing [Schimek, 1996a, Frank and Pivo, 1994; PBQD. 1996a; Cervero, 1989]. These results tend to hold for central business districts (CBDs), suburban employment centers, and employment centers located near commuter rail stations. This strong, clear result relative to the more ambiguous residential density case is likely due to the more direct relationship which almost certainly exists between employment density and transit service supply (i.e., such centers are readily Rentable loci for transit services', as well as the "levels of service" for other modes as well (e.a.- ~ ~ ~ . ~ . - .~ ~ higher employment densities Increase the chances of ride-share "matches"; higher density areas, particularly In CBDs' tend to have higher parking costs and/or walk times from parking). ~an, Perhaps the single most important Implication for integrated urban modeling is to reinforce the importance of the employment/activity center end of the trip. There is a strong tendency in both theory and practice to focus on the residential side of the land-use problem. The spatial distribution of employment (and, more generally, out-of-home activities, both work and non-work related), however, may well be a much stronger "driver" of travel behavior and transportation supply options. It is also arguable that this aspect of land-use may be more susceptible to successful planning control. 6. Accessibility. For current purposes, the tenn accessibility is used here simply to mean a variety of measures of "how well connected" a given location is with activities of a given type (work opportunities, shopping destinations, etc.), usually in terms of how much of a given activity is located how close to the location in question. Thus, for example, one can speak of the accessibility of a residential zone to employment opportunities. A specific variant on the accessibility theme is the question of "jobs-housing balance" which is concerned with the extent to which job opportunities exist within some fairly localized region for a set of workers within a given residential area. While the literature is somewhat mixed with respect to this issue -- particularly with respect to the efficacy of jobs-housing balance on VMT, etc., generally the discussion is about how important accessibility is relative to other factors' not whether it is important. Conceptually ~ 7 _ ~ I _

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TCRP H-12 Final Report accessibility is central to transportation planning -- it is. very s~mply~ what we are in the business of providing. The accessibility of people to workplaces and other activities, the accessibility of jobs to workers, of stores to their market must be of some relevance to the activity/travel process if this process is the least bit rational. Indeed, one of the reasons why the literature on the impact of factors such as residential . .. . . density or neighborhood design is so mixed is that it tends to ignore the critical question of connectivity: it is of little use having a dense neighborhood which does not have good access to relevant activity destinations; transit requires travel corridors of reasonable density, consisting of both "production" and "attraction" points to be most effective, waking requires close proximity between origins and destinations, etc. This is not to sail Mats in areas possessing very high degrees of connectivity, etc. accessibility may be so universally high that it may not seem to matter; this simply represents one extreme point on the continuum of possible situations. Linking origins with destinations to create flows is the fundamental task of travel demand models. Understanding how urban form combines with the transportation system to provide accessibility to activities and how people respond to accessibility in both their location and activity/travel choices is central to this travel demand forecasting process. To address this issue comprehensively clearly requires an integrated approach to the modeling of location choice and travel behavior. 7. l\ieighborhoo(1 design. Particularly in the last fear years. marry researchers have focussed on more "micro-level" questions concerning the role which local neighborhood design plays in determining travel behavior. In particular, advocates of "neo-traditional neighborhoods" and town planning have argued that such neighborhoods should encourage more walk and transit trios. shorter trips. etc. thereby contributing to reductions in auto VMT' emissions etc. - -r - ~ Me literature dealing with this issue which has been reviewed in this report is' again quite mixed in its findings, again probably for many of the reasons previously cited (lack of comprehensive analysis' methodological weaknesses data limitations' etc.). The key issue here however. is almost certainly that our "activity- time-suace prisms" extend well beyond the local nei abhorEc)od given both the levels of accessibility available to many people and their ~, expectations/needs concerning their part1clpatlon in activities ot various types. Jobs-houslng balances, for example, are virtually impossible to achieve in practice, given the nature and dynamics of our complex labor markets. Similarly, our desire for the widest possible range of consumer goods, experiences, etc. Bleary that our "action spaces" will inevitably extend well beyond the neighborhood boundary. This is not to say that the details of neighborhood design are not important. It is such design details, after all, which determine the residential and employment densities within the neighborhood, the ease and attractiveness of walking' and the ease and efficiency of providing transit services ~ O - 30 -

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TCRP H-17 Final Report within the neighborhood. to name just a few- important issues. From a modeling point of view, however, the key point is. again, the need for a comprehensive, integrated view of the problem -- neighborhood design within the overall transportation - land-use interaction -- which is cntical to achieve, bow In order to few ur~derstand the nature of the interactions involved, arid then to generate useful analyses and forecasts based upon this understar~ding. Figure 3.2 represents one rather messy but still overly simplified summary of this discussion. In this figure, act~vity/trave] behavior is shown to be We "outcome" of a complex set of interactions among the various factors discussed above. This figure is intended to illustrate two key points: 1. ''Urbar1 form" or "larld-use" or "physical design" (as represented by residential density, employment density and neighborhood designs provides a context for human behavior, which, in this case, includes location decisions (residence, job locations), auto ownership decisions, and. ultimately, activi07/trave! decisions. That is, increased residential density does not directly "cause" reductions in auto VMT. Rather, under the right circumstances, it may attract a resident population with particular socio-economic charactenstics and desired activity patterns who Bill make auto ownership and travel decisions that will result in increased transit/walL usage, reduced VMT. etc. relative to what they might do in other urban form contexts. Numerous "supply-demand" or "feedback" Interactions exist within the system (travel decisions affect road congestion levels, which, in turn, affect travel decisions, residential densities combined With attributes of the resident population affect the level of transit service provided, which, in turn, affects the attractiveness of the residential area for people of different types; etc.~. Ignoring these complex interactions and ar~alyzing the system In a partial. overly simplified was- almost inevitably leads to misleading or even erroneous results. 3.2.2 Impacts of Transit on Urban Form To this point the focus has been on discussing urban form impacts on travel behavior. Reversing the direction of causation, Table 3.2 provides a brief summary of the empirical evidence conceding transit system impacts on urban foe which was discussed in greater detail in Appendix A. In this case, findings are summanzed within the table by urban area given the "case studs-" nature of this literature. As in Table 3. i. the citation for each paper reviewed is provided, as is the page number in Appendix A where a more detailed discussion of the paper can be found. Again, a diversity of findings is reported concerning the impacts of light rail, subway and commuter rail lines and stations on residential density, employment density, property values, etc. Without attempting to discuss or reconcile these results in any detail, there are at least four main points to be drawn from Table 3.2 which have implications for integrated urban modeling. ~9

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TCRP H-12 Final Report Figure 3.2 Urban Form Impacts on Activity and Travel ~ \~ (Accessibility) (Demographic) - - - 40 ,~ \ I ACTIVITY / TRAVEL

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TCRP H-17 Final Report Table 3.2 Summary of Empirical Evidence Concerning Transit Impacts on Urban Form Atlanta Population adjacent to raid stations decreased; employment increased but employment share decreased relative to the rest of the region San Francisco/Bay Area After ~ year of operation, only 35% of B ART users were former car users; 50% previously used bus Transportation access to jobs seldom a factor in job location choice; access to BART a minor consideration in household location choice; BART unpact on land-use after 5 years of operation was insignificant After 20 year of operation, land-use unpacts of BART focussed in downtown San Francisco and Oakland' plus a few suburban stations; neighborhood opposition and/or poor local real estate markets prevented significant impacts elsewhere; general freeway-oriented growth occurred despite BART's presence; stronger public policy initiatives would be required to generate a compact, multi- centered urban fonn around BART Property values increased as one moves closer to a commuter rail station and decreased with proximity to a freeway, for a selected B ART station Boston Nielson & Sanchez, 1997, pg. 198] [Webber, 1976, pg. 196] [Giuliano' 199S, pg. 196] [Cervero & Landis, 1997, pg. 197] [Workman & Brod. 1997, pg. 197] Rail extensions/improvements had a strong [Knight & Trygg, 1977, pg. 199] influence on development within North Quincy along with other complementary factors; elsewhere, little impacts observed - 41

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TCRP H-12 Final Report Table 3e2, contld C~g~' Residential location preferences strongly affected by transportation system; significant premium exists for housing within walking distance of a light rail station (Calgary) Chicago Rail system improvements generated no discernable land-use impacts, although one must note He high level of CBD development high cost of land, and the "mature" nature of the existing system Cleveland Subway construction had minimal land-use impact; note lack of complementary policies/factors relative to the Toronto case Glasgow. One year after major rail upgrades, planning applications in adjacent areas increased; some reversal of population decline observed; fairly small number of new induced trips and diversions from auto Montreal Nature and intensity of CBD retail activities influenced by the Metro, but, as in Toronto, other development factors were also of unpor~nce; outside the CBD, little development impact generally occurred. tHunt, en al., 1994, pg. 28] [Knight & Trygg, 1977. pg. 31] [Knight & Trygg, 1977. pg. 31] [Gentlemen, et al., 1983, pg. 29] [Knight & Trygg, 1977, pg. 31] - 42

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TCRP H-12 Final Report - Table 3e2, cont~d Philadelphia Substantial increase in property values along the Lindewold tine; influenced zoning and actual investments ~ suburban office and apa~-ln~ent buildings although growth along the line was not higher than in other portions of the urban region Portland Property value Trip acts of Me Portland light-rai! line difficult to identify No statistically significant impact of proximity to rail stations on property values for Portland stations Significant new development observed adjacent to Portland light rail stations Toronto Significant development occured around many stations; some evidence of increased proper values and densities adjacent to stations; however, much of this results from aggressive zoning, joint public-private development, and, in general carefully coordinated transit and land-use development Washington, D.C. 1979-1982, 54% of nonresidential construction in the metropolitan areas occured within 0.7 mi. Of a Metro station. Rail corridors have developed more than other places, with majority of this growth occuring Knight & Trygg, 1977, pg. 199] "Workman & Brod, 1997, pg. 197] [Al-Mosaind, et al., 1993, pg. 197] Barrington, 1989, pg. 197] Knight & Trygg, 1977, pg. 199] [Baker, 1983, pg.198] [CIreen and James, 1993, pg. 198] - 43

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TCRP H-12 Final Report First, notable by their absence is any mention of land-use impacts of shared-nght-of-way bus systems. HOV systems, etc. This reflects a widely held belief that it is only major fixed-guideway infrastructure which wall have a discernable impact on urban form development. Bus routes can charge on a mon~-to-month basis, HOV Cartes can generally be converted to general traffic usage with minimal effort. Further, such systems (especially bus systems) are often fairly ubiquitous, providing a "background, base" service over an extended area. Such flexible relativeiv ubiquitous systems Carl provide reasonably high levels of accessibility, which, in nine influence location and Ravel choices, but which, In and of themseIves. are assumed to be unlikely to stimulate major land development decisions. Second, many of the studies cited suffer Tom methodological and/or data limitations. Two of these are particularly notable: I. Many studies involve very short analysis time penods (the extreme being Webber's 1976 study of BERT impacts one year after beginning operations. Urban form evolution, however, operates on a time scale of decades; short-run impacts are inevitably negligible and short-run responses need not be indicative of Ton~-run impacts. Practical difficulties exist, however, in long-run empirical studies. . . . . . . . is, First, simply being able to observe a system over a very long penoa or time IS a major undertaking. Second, over the Tong run many factors change. making unambiguous determination of the transit system impact difficult, if not impossible. All empirical studies are either "before-and-after" studies of the impact of a given facility in a given location or (less commonly) a comparison of two "comparable" locations, one in which the facility was constructed, and one in which it was not. Both are intended to approximate a "w~th-and-without" analysis, which is what is really required in order to sort out the actual impacts of the transit facility. Neither the before-and-after or the comparable location approaches, however. provide an adequately controlled "experiment" to oronerIv isolate the transit facility impact: . ~. ~ . ],_ _ ~ ,, ~ ~e~ore-ano-atter comparisons are Inevitably confounded by all the other evolutionary factors at work within the given urban area and no two combers cities. etc. are ever so "identical" that one can conclude that the only explanation for differences between the two locations' development is the presence of the transit facility. It can be argued that the only way to identify the "true" impacts of raid transit systems on a long-run, with-and-without basis is through the use of an integrated transportation - land-use model. That is, it is argued that it is only through the exercising of such a model that one can trace the long-r~ evolution of an urban system within a controlled setting (i.e., one Carl control other exogenous inputs into the urban system being modeled). Further, with such a mode! one can test the sensitivity of the transit impacts to changes in these "exogenous inputs" so as to explore the extent to which robust, generalizable results Carl be obtained. - 44

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TCRP H-12 Final Report . . . Third, it is noteworthy that We focus of many of these studies is on land value. particularly given the total absence of land or housing prices from the "urban form impact" literature summarized in Table 3.1. Land development, building stock supply, and residential and commercial location decisions all occur within economic markets, within which supply-demand processes (for land. buildings, etc.) exist and are reconciled through the determination of market-clearing prices. The development of land and the supply of building stock is primarily the task of private sector agents seeking to maximize profits (within whatever "rules of the game" exist with respect to zoning, etc.), subject to anticipated demand levels. The decision concerning where to live or where to locate one's Finn depends in no small way on the prices of different building types at different locations. Given the absolutely fundamental importance of market processes in both land development and location choice, it is essential that these processes be explicitly included in any integrated model of transportation and land-use, if a proper understanding of urban system dynamics and evolution is to be achieved. Finally, Me one absolutely clear result which emerges Mom Table 3.2 is that transportation in general =d rail transit In particular is a facilitator of development, not a cause: a "necessary but not sufficient condition" for development to occur. Although note- over twenty years old, the work of Knight and Try go remains the most comprehensive and definitive study of this issue to this day. In their 1977 study, they build a compelling case that transit ins estment is but "one piece of the pu=]ett~ and Mat loch land-use policies, over government policies. the local and regional economic climate, etc. all must interact in a mutually reinforcing way in order for positive land development impacts to occur. Much earlier, Spen;,ler L1Y301 came to very star conclusions in his study ofthe impact of the New York subway system on land values dunng the period 1909-1930. As summarized by Libicki t1 975], these conclusions w-ere: "a. transit served to shift as much as augment land values; b. neighborhoods which were 'marked out' for certain Acres of development and already so developed would show little increase in land value; most of the large increase in land value arose not from the rail transit system, but from subdividing arid building ore land; d. e. declining neighborhoods did not stop declining, stag t neighborhoods did not stop stagnating and the character of art area around a station strongly resembled the character of the surrounding neighborhood in an`; case, so that consequently; rather than to be considered a cause of land value changes, a transit facility should more properly be regarded as a construction which permits or facilitates under certain circumstance. an emergence of tared values, the values being determined largely by other factors." ~LJibicki, 1975, pp. 6-7] - 4:

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TCRP H-12 Final Report Figure 3.3 is taken Tom Knight and Trygg [1977] and summarizes their findings concerning the land development process. This figure illustrates both the complexity of this process and the role which transit ~nvestrnent can play within it. Some of the actors and their interactions shown in this figure Carl (at least In principle) be modeled within an Integrated urban model, some almost certainly can not. The lesson, however is Me same as has been stated at venous points throughout this section: the need for integrated urban models as the only to feasible method for properly analyzing and forecasting the land development process. - 46

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| Ease of Private L Assembly! I I Infrastructure | | Capacity . Public Facilities | Urban l | Renewal ~OTHER NEW NEARBY LAND Prig ate ~ INVESTMENTS Dcvclopment l cighborhood ~LOCAL LAND I Aninades I USE POLICIES _ 1 / Zoning & / I Development Incentives TCRP H-12 Final Report Figure 3.3 Factors Influencing Land-Use Impact (Source: Knight aIld TIygg t19774) Cost of Land &` Site Preparation Public Assembly Activities Urban Renewal Transit Excess (Young Amend,T~cut) i AVAILABILITY OF DEVELOPABLE LAND Phvsical . Blimp \ ATTRACTIVENESS OF SITE FOR \ DEVELOPMENT COMM}'TMENT ~ ~ ~ ~_ ITO SPECIFIC J ~ ~ | DECISION IS TO |~ IMPACT | OF TRANSIT ~_ IMPROVEMENT ~ IMPROVEMENT IN ACCESSIBILITY' ~ /, l OTHER / . GOVERNMENT ~, / POLICIES ~ ~ Taxation and 1 Goals of Larger | / ~ other l Community, ~ | \ | Assessment Growth I ~ Social Character | I Compliance | ~nfras~uculrc | Plan & Dollar I | withother | | Provisions | Pnont~es ~ I Public I I Programs I Environmental | Impact Review ~ Equal | Opponunit~ - 47 |REGION S DEMAND| I FOR NEW L | DEVELOPMENT L ~ | Economy | Regional | I Economy I

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TCRP H-12 Final Report - 48