Title
A Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York
Abstract
Walking is the most common, environment-friendly, and inexpensive type of physical activity. To perform in-depth walkability analysis, one option is to objectively evaluate different aspects of built environment related to walkability. In this study, we proposed a computational framework for walkability measurement using open data. Three major steps of this framework include the web scrapping of publicly available online data, determining varying weights of variables, and generating a synthetic walkability index. The results suggest three major conclusions. First, the proposed framework provides an explicit mechanism for walkability measurement. Second, the synthetic walkability index from this framework is comparable to Walk Score, and it tends to have a slightly higher sensitivity, especially in highly walkable areas in urban core. Third, this framework was effectively applied in a metropolitan area that contains three small cities that together represent a small, old shrinking region, which extends the topical area in the literature. This framework has the potential to quantify walkability in any city, especially cities with a small population where walkability has rarely been studied, or those having no quantification indicator. For such areas, researchers can calculate the synthetic walkability index based on this framework, to assist urban planners, community leaders, health officials, and policymakers in their practices to improve the walking environment of their communities.
Year
DOI
Venue
2020
10.3390/ijgi9010036
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
walkability,GIS,data-driven method,open data,shrinking small cities,geospatial big data,smart cities,urban mapping,urban built environment,urban planning
Open data,Built environment,Population,Urban mapping,Data-driven,Computer science,Transport engineering,Walkability,Urban planning,Metropolitan area
Journal
Volume
Issue
Citations 
9
1
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Chengbin Deng1163.51
Xiaoyu Dong200.34
Huihai Wang300.34
Weiying Lin400.34
Hao Wen500.34
John Frazier600.34
Hung Chak Ho700.68
Louisa Holmes800.34