@inproceedings{a7eb4ab2dae04fdca795ad4ae896baf1,
title = "Impacts of Catchments Derived from Fine-Grained Mobility Data on Spatial Accessibility",
abstract = "Spatial accessibility is a powerful tool for understanding how access to important services and resources varies across space. While spatial accessibility methods traditionally rely on origin-destination matrices between centroids of administrative zones, recent work has examined creating polygonal catchments – areas within a travel-time threshold – from point-based fine-grained mobility data. In this paper, we investigate the difference between the convex hull and alpha shape algorithms for determining catchment areas and how this affects the results of spatial accessibility analyses. Our analysis shows that the choice of how we define a catchment produces differences in the measured accessibility which correlate with social vulnerability. These findings highlight the importance of evaluating and communicating minor methodological choices in spatial accessibility analyses.",
keywords = "Spatial accessibility, alpha shape, convex hull, cyberGIS, social vulnerability",
author = "Alexander Michels and Jinwoo Park and Bo Li and Kang, {Jeon Young} and Shaowen Wang",
note = "Funding This paper is based upon work supported in part by the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE) that is funded by the National Science Foundation (NSF) under award No. 2118329. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the author(s) and do not necessarily reflect the views of NSF. The work also received support from the Taylor Geospatial Institute. Our computational experiments used Virtual ROGER that is a geospatial supercomputer supported by the CyberGIS Center for Advanced Digital and Spatial Studies and the School of Earth, Society and Environment at the University of Illinois Urbana-Champaign. This paper is based upon work supported in part by the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE) that is funded by the National Science Foundation (NSF) under award No. 2118329. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the author(s) and do not necessarily reflect the views of NSF. The work also received support from the Taylor Geospatial Institute. Our computational experiments used Virtual ROGER that is a geospatial supercomputer supported by the CyberGIS Center for Advanced Digital and Spatial Studies and the School of Earth, Society and Environment at the University of Illinois Urbana-Champaign.; 12th International Conference on Geographic Information Science, GIScience 2023 ; Conference date: 12-09-2023 Through 15-09-2023",
year = "2023",
month = sep,
doi = "10.4230/LIPIcs.GIScience.2023.52",
language = "English (US)",
series = "Leibniz International Proceedings in Informatics, LIPIcs",
publisher = "Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing",
editor = "Roger Beecham and Long, {Jed A.} and Dianna Smith and Qunshan Zhao and Sarah Wise",
booktitle = "12th International Conference on Geographic Information Science, GIScience 2023",
}