A Semi-Automated Method to Generate GIS-Based Sidewalk Networks for Asset Management and Pedestrian Accessibility Assessment. Issue 44 (December 2018)

• Record Type: Journal Article
• Authors: Li, Hanyan; Cebe, Jack; Khoeini, Sara; Xu, Yanzhi "Ann"; Dyess, Chelsea; Guensler, Randall
• Is Part Of: Transportation research record. Volume 2672:Issue 44(2018)
• Page Start: 1
• Page End: 9
• Publication Date: 2018-12
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198118757981
• Languages: English
• ISSNs: 0361-1981

Abstract

Pedestrian infrastructure that is comfortable, connected to destinations of interest, and accessible to those with disabilities is vital to a safe, accessible, equitable, and sustainable transportation system. Planners recognize the benefits of providing well-maintained sidewalks and curb ramps, but often lack the asset management systems necessary to inventory sidewalk maintenance problems, prioritize sidewalk maintenance needs, and track the implementation of sidewalk improvement projects. Communities that are managing sidewalk presence and condition data typically link the data to their roadway network, which makes tracking specific sidewalk assets difficult. This paper introduces an affordable, semi-automated, and easy-to-implement process to generate a GIS-based sidewalk network with associated links and nodes representing crosswalks and intersections. Quantitative sidewalk condition data can be loaded onto the network, which allows it to be used to manage sidewalks as transportation assets, assessing pedestrian accessibility, prioritizing repairs or improvements, and to automatically identify accessible routes between origins and destinations. System inputs include parcel-level land-use and roadway centerline data, both of which are publicly available and free in most cases. The network is generated within the ArcGIS environment, using Python scripts to implement embedded ArcGIS functions. The method requires few computational resources, and tremendously reduces the manual labor required to develop a fully interconnected sidewalk network. Examples from multiple communities are presented to show how quantitative sidewalk condition data are loaded onto the network, and illustrate the network's potential for pedestrian navigation and routing applications.