From TIGER to Audit Instruments: Measuring Neighborhood Walkability with Street Data Based on Geographic Information Systems

Schlossberg, Marc

doi:10.3141/1982-08

Cited by 31 publications

(31 citation statements)

References 8 publications

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“…Walkability is calculated by dividing the length of minor roads (km) in a county by the area of the county (km 2 ). The minor road density is used as a surrogate of walkability, which is consistent with the walkability measurement method introduced by Schlossberg [77]. The road network and street classification data are abstracted from the topologically-integrated geographic encoding and referencing (TIGER) database.…”

Section: Physical Environmental Factorsmentioning

confidence: 99%

Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity

Wang

Lee

Kwan

2018

IJGI

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Considerable research has been conducted to advance our understanding of how environmental factors influence people's health behaviors (e.g., leisure-time physical inactivity) at the neighborhood level. However, different environmental factors may operate differently at different geographic locations. This study explores the inconsistent findings regarding the associations between environmental exposures and physical inactivity. To address spatial autocorrelation and explore the impact of spatial non-stationarity on research results which may lead to biased estimators, this study uses spatial regression models to examine the associations between leisure-time physical inactivity and different social and physical environmental factors for all counties in the conterminous U.S. By comparing the results with the conventional ordinary least squares regression and spatial lag model, the geographically weighted regression model adequately addresses the problem of spatial autocorrelation (Moran's I of the residual = 0.0293) and highlights the spatial non-stationarity of the associations. The existence of spatial non-stationarity that leads to biased estimators, which were often ignored in past research, may be another reason for the inconsistent findings in previous studies besides the modifiable areal unit problem and the uncertain geographic context problem. Also, the observed associations between environmental variables and leisure-time physical inactivity are helpful for developing location-based policies and interventions to encourage people to undertake more physical activity.

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Section: Physical Environmental Factorsmentioning

confidence: 99%

Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity

Wang

Lee

Kwan

2018

IJGI

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“…d. Urban land cover -The total area of land in the station zone with at least 50% coverage by impermeable surfaces. e. Impeded pedestrian catchment area (IPCA) -A measure of pedestrian access introduced by Schlossberg [23,24], making up the total continuouslywalkable area (by street network) with the station zone, after removing pedestrian-inaccessible roadways. Expressed as a ratio of total station zone area.…”

Section: Creating An Index To Measure Walkabilitymentioning

confidence: 99%

Measuring walkability and its effect on light rail usage: a comparative study of the USA and Japan

Nawrocki

Nakagawa

Matsunaka

et al. 2014

WIT Transactions on the Built Environment

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With rising awareness of global warming and its consequences, greater efforts are being made to make our cities more sustainable. Among many factors that can lead to more a sustainable future, policies encouraging walking and the use of public transportation can be considered as major priorities in planning. There is a significant body of research concerning the process of rating urban structure according to its ease of access for pedestrians and concerning the relationships between walking and public transportation. However, there are few studies focused on the direct relationship between walking and Light Rail Transit (LRT). This study sought to understand the effect of the so-called walkability of urban areas on LRT usage in the USA and Japan. To achieve this goal, an objective, an internationally applicable method for quantifying walkability, was devised using urban structure and street network data in the USA and Japan. Walkability indices derived using this method was used to measure the effect of walkability in station areas on LRT ridership in both countries. Results show that the urban structure around stations in Japanese cities can generally be considered more walkable than cities in the USA. Moreover, station area walkability has a measurable effect on LRT usage, but only in the USA.

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“…Travel behaviour is one of the areas where GIS has been used for demand modelling of public (Choi and Jang, 2000) and private modes (Choi and Kim, 1996). GIS has been used to model travel choice (Byon et al, 2007;McGowen and McNally, 2007;Bricka and Bhat, 2006;Ogle et al, 2005;Tsui and Shalaby, 2006), destination choice (Chow et al, 2005), location choice (Nicholas et al, 2004;Shelton et al, 2004), mobility (Schlossberg, 2006), and accessibility (Hodge, 1997;Miller and Wu, 2000;Casas, 2003). It has been used for travel time forecasting (You and Kim, 2000), and risk and evacuation models (Church and Cova, 2000;Alexander and Waters, 2000;Horner and Downs, 2007).…”

Section: 3geomodelling Framework In Transportation Researchmentioning

confidence: 99%

Geo-ICT in Transportation Science

Borzacchiello¹,

Casas

Ciuffo³

et al. 2009

Geospatial Technology and the Role of Location in Science

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Since the first appearances of Geographical Information Systems (GIS), transportation science has found in them its natural support, to represent, first, the spatial and, later on, the temporal aspects of transportation networks and infrastructures. As GIS developed so did their use in transportation science, and they became essential not only in visualization but also to facilitate and speed data management, algorithmic operations, and decision making. This paper analyses the contributions and influence of GIS in transport science on the basis of three frameworks: geodatabase, geomapping, and geomodelling, all of which highlight the importance of location.

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From TIGER to Audit Instruments: Measuring Neighborhood Walkability with Street Data Based on Geographic Information Systems

Cited by 31 publications

References 8 publications

Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity

Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity

Measuring walkability and its effect on light rail usage: a comparative study of the USA and Japan

Geo-ICT in Transportation Science

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