Impact of extreme weather events on urban human flow: A perspective from location-based service data

Research output: Contribution to journalArticlepeer-review

Authors

Colleges, School and Institutes

External organisations

  • Ohio State University
  • Tsinghua University
  • Baidu Online Technology

Abstract

This study investigates the impact of extreme weather events on urban human flow disruptions using location-based service data obtained from Baidu Map. Utilizing the 2018 Typhoon Mangkhut as an example, the spatial and temporal variations of urban human flow patterns in Shenzhen are examined using GIS and spatial flow analysis. In addition, the variation of human flow by different urban functions (e.g. transport, recreational, institutional, commercial and residential related facilities) is also examined through an integration of flow data and point-of-interest (POI) data. The study reveals that urban flow patterns varied substantially before, during, and after the typhoon. Specifically, urban flows were found to have reduced by 39% during the disruption. Conversely, 56% of flows increased immediately after the disruption. In terms of functional variation, the assessment reveals that fundamental urban functions, such as industrial (work) and institutional - (education) related trips experienced less disruption, whereas the typhoon event appears to have a relatively larger negative influence on recreational related trips. Overall, the study provides implications for planners and policy makers to enhance urban resilience to disasters through a better understanding of the urban vulnerability to disruptive events.

Bibliographic note

Publisher Copyright: © 2020 Elsevier Ltd Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

Details

Original languageEnglish
Article number101520
JournalComputers, Environment and Urban Systems
Volume83
Publication statusPublished - Sep 2020

Keywords

  • AMOEBA, Baidu map, Disaster analysis, Location-based service data, Urban human flow