Citation

Chen Z, Gong Z, Yang S, Ma Q, Kan C. Comput. Environ. Urban Syst. 2020; 83: e101520.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.compenvurbsys.2020.101520

PMID

32834303 PMCID

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.

Language: en

Keywords

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