Measuring Sprawl and Its Impacts

Abstract

Across the nation, the debate over metropolitan sprawl and its impacts continues decade after decade. To elevate the debate, a decade ago, researchers developed compactness/sprawl indices for metropolitan areas and counties that have been widely used in health and other research. In this study, we develop refined compactness/sprawl indices based on definitions and procedures in earlier studies by Ewing and colleagues and validate them against transportation outcomes. The indices are being made available to researchers who wish to study the causes, costs and benefits, and solutions to sprawl and to practitioners who wish to check their community’s success in containing sprawl.

A National Study on Transportation Affordability of HUD Housing Assistance Programs

“…On the other hand, programs designed for people with special needs like Section 811 nationally spend on average 16% of their income on transportation and found to be the least transport affordable programs. Table 2 presents the top ten large regions (population of more than 0.5 million) with the highest number of unaffordable HUD-subsidized properties once accounting for transportation costs along with the sprawl index for each region [36,37]. The sprawl index value above 100 indicates more compactness, while the values below 100 indicate the sprawling region.…”

“…All HUD designated properties in San Francisco-San Mateo, CA, the region with one of the best transit system, dense, compact, and mixed-uses [36] are located in location efficient areas and are affordable in terms of transportation (as shown in Figure 4) while in Atlanta-Sandy Spring, GA (composite sprawl index of 41), almost 70% of HUD designated properties found to be unaffordable in terms of transportation costs (Figure 4). As indicated by literature, sprawl increases the travel distance, vehicle ownership and decreases the opportunities for commuting by transit, which, in turn, increases the overall household transportation costs [38][39][40] On the other hand, due to lower VMT and options for other active modes of travel, transportation costs can sharply decrease in compact areas [37]. However, this does not imply that transportation affordability could not be achieved in more sprawling regions, rather it is more important to carefully consider subsidizing the housing into location efficient places in sprawling regions.…”

Built-Up Growth Impacts on Digital Elevation Model and Flood Risk Susceptibility Prediction in Muaeng District, Nakhon Ratchasima (Thailand)

“…The FRS-GWR model predicts the area risk of flood sensitivity in the year 2022. The significant independent variables were only selected containing the normalized digital elevation model Index (NDEMI, X1), area of built-up index (ABUI, X3), density of built-up (D j , X4), curvature index (CI, X5), and slope length Index (SLI, X6) and to create a model FRS-GWR as Equation (15) when assigning Y values from GWR model = F j in Equation (5). The result of the dispersion of independent variables is as follows Figure 8b-f.…”

“…As a consequence, this fabricates land-use planning (especially the expansion of residential and building areas), which leads to substantial replacements owning to restricted resources [2][3][4]. For example, there is an inevitable rational in some areas to replace dwelling and development zones in agricultural lands [5]. In the last five years, the increased development and expansion of built-up areas has impacted dramatically on land-use and land-cover characteristics.…”

Individuals’ Demand for Ride-hailing Services: Investigating the Combined Effects of Attitudinal Factors, Land Use, and Travel Attributes on Demand for App-based Taxis in Tehran, Iran

“…The literature suggests that the diversity of urban form, in terms of compactness/sprawl measures considerably affects the transportation outcomes [39][40][41]. Thus, we considered the effects of urban form in trip origins/destinations on ride-hailing frequencies.…”