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Article: A Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York

TitleA Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York
Authors
Keywordswalkability
GIS
data-driven method
open data
shrinking small cities
Issue Date2020
PublisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/ijgi
Citation
ISPRS International Journal of Geo-Information, 2020, v. 9 n. 1, p. article no. 36 How to Cite?
AbstractWalking 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.
Descriptioneid_2-s2.0-85077981915
Persistent Identifierhttp://hdl.handle.net/10722/280401
ISSN
2023 Impact Factor: 2.8
2023 SCImago Journal Rankings: 0.712
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDeng, C-
dc.contributor.authorDong, X-
dc.contributor.authorWang, H-
dc.contributor.authorLin, W-
dc.contributor.authorWen, H-
dc.contributor.authorFrazier, J-
dc.contributor.authorHo, HC-
dc.contributor.authorHolmes, L-
dc.date.accessioned2020-02-07T07:40:28Z-
dc.date.available2020-02-07T07:40:28Z-
dc.date.issued2020-
dc.identifier.citationISPRS International Journal of Geo-Information, 2020, v. 9 n. 1, p. article no. 36-
dc.identifier.issn2220-9964-
dc.identifier.urihttp://hdl.handle.net/10722/280401-
dc.descriptioneid_2-s2.0-85077981915-
dc.description.abstractWalking 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.-
dc.languageeng-
dc.publisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/ijgi-
dc.relation.ispartofISPRS International Journal of Geo-Information-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectwalkability-
dc.subjectGIS-
dc.subjectdata-driven method-
dc.subjectopen data-
dc.subjectshrinking small cities-
dc.titleA Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York-
dc.typeArticle-
dc.identifier.emailHo, HC: hcho21@hku.hk-
dc.identifier.authorityHo, HC=rp02482-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/ijgi9010036-
dc.identifier.scopuseid_2-s2.0-85077981915-
dc.identifier.hkuros309098-
dc.identifier.volume9-
dc.identifier.issue1-
dc.identifier.spagearticle no. 36-
dc.identifier.epagearticle no. 36-
dc.identifier.isiWOS:000514631100008-
dc.publisher.placeSwitzerland-
dc.identifier.issnl2220-9964-

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