首页    期刊浏览 2024年07月08日 星期一
登录注册

文章基本信息

  • 标题:A Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York
  • 本地全文:下载
  • 作者:Chengbin Deng ; Xiaoyu Dong ; Huihai Wang
  • 期刊名称:ISPRS International Journal of Geo-Information
  • 电子版ISSN:2220-9964
  • 出版年度:2020
  • 卷号:9
  • 期号:1
  • 页码:36
  • DOI:10.3390/ijgi9010036
  • 语种:English
  • 出版社:MDPI AG
  • 摘要: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.
国家哲学社会科学文献中心版权所有