A Spatial Analysis of the Relationship between Pedestrian Crash Events and Features of the Built Environment in Downtown Atlanta

Pedestrian injuries and fatalities due to motor vehicle crashes are a significant public health concern, and the urban campus of Georgia State University poses unique challenges to pedestrian safety issues. Previous studies of the built environment have link several features to increased pedestrian crash occurrences. Once identified, these features can be modified to create a healthier environment for pedestrians. This study examines the relationship between specific features of the built environment and pedestrian crash events. Environmental audits were conducted to collect information about the built environment around Georgia State campus, and pedestrian crash data was obtained from GDOT. Geographic Information Systems (GIS) was used to create a visual representation of this data in order to establish spatial relationships between the built environment and pedestrian crash events. Results show both positive and negative correlations between certain built environment features and pedestrian crashes. GIS was established as a useful tool for evaluating the spatial distribution and relationship between the built environment and pedestrian injury within a localized area, and provides a springboard for future research that seeks to study this association on a larger scale

The Impact of Built Environment on Pedestrian Crashes and the Identification of Crash Clusters on an Urban University Campus

Objectives: Motor vehicle-pedestrian crash is a significant public health concern. The urban campus of Georgia State University poses unique challenges due to a large number of students and university employees. The objectives of this study are twofold: (1) to examine the correlation between specific features of the built environment on and around the University campus and pedestrian crashes; and (2) to identify crash clusters in the study area using network-based geospatial techniques.Methods: We obtained pedestrian crash data (n=119) from 2003 to 2007 from Georgia Department of Transportation and evaluated environmental features pertaining to the road infrastructure, pedestrian infrastructure and streetscape for each road segment and intersection. Prevalence rate of each feature with pedestrian crashes present was calculated. We used network-based Kernel Density Estimation to identify the high density road segments and intersections, then used network-based K-function to examine the clustering of pedestrian crashes.Results: Over 50% of the crosswalk signs, pedestrian signals, public transit, and location branding signs (more than three) at intersections involved pedestrian crashes. More than half of wider streets (greater than 29 feet), two-way streets, and streets in good condition had pedestrian crashes present. Crashes occurred more frequently in road segments with strong street compactness and mixed land use present and were significantly (p<0.05) clustered in these high-density zones.Conclusions: Findings can be used to understand the correlation between built environment and pedestrian safety, to prioritize the high-density zones for intervention efforts, and to formulate research hypotheses for investigating pedestrian crashes. [West J Emerg Med. 2010; 11(3): 295-302.

The Impact of Built Environment on Pedestrian Crashes and the Identification of Crash Clusters on an Urban University Campus

Objectives: Motor vehicle-pedestrian crash is a significant public health concern. The urban campus of Georgia State University poses unique challenges due to a large number of students and university employees. The objectives of this study are twofold: (1) to examine the correlation between specific features of the built environment on and around the University campus and pedestrian crashes; and (2) to identify crash clusters in the study area using network-based geospatial techniques.Methods: We obtained pedestrian crash data (n=119) from 2003 to 2007 from Georgia Department of Transportation and evaluated environmental features pertaining to the road infrastructure, pedestrian infrastructure and streetscape for each road segment and intersection. Prevalence rate of each feature with pedestrian crashes present was calculated. We used network-based Kernel Density Estimation to identify the high density road segments and intersections, then used network-based K-function to examine the clustering of pedestrian crashes.Results: Over 50% of the crosswalk signs, pedestrian signals, public transit, and location branding signs (more than three) at intersections involved pedestrian crashes. More than half of wider streets (greater than 29 feet), two-way streets, and streets in good condition had pedestrian crashes present. Crashes occurred more frequently in road segments with strong street compactness and mixed land use present and were significantly (p&lt;0.05) clustered in these high-density zones.Conclusions: Findings can be used to understand the correlation between built environment and pedestrian safety, to prioritize the high-density zones for intervention efforts, and to formulate research hypotheses for investigating pedestrian crashes. [West J Emerg Med. 2010; 11(3): 295-302.