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A typhoon shelter selection and evacuee allocation model: a case study of Macao (SAR), China

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posted on 2020-08-28, 13:32 authored by Xiujuan Zhao, Peng Du, Jianguo Chen, Dapeng YuDapeng Yu, Wei Xu, Shiyan Lou, Hongyong Yuan, Kuai Peng Ip
Typhoon disaster represent one of the most prominent threats to public safety in the Macao Special Administrative Region (SAR) of China and can cause severe economic losses and casualties. Prior to the landing of typhoons, affected people should be evacuated to shelters as soon as possible; this is crucial to prevent injuries and deaths. Various models aim to solve this problem, but the characteristics of disasters and evacuees are often overlooked. This study proposes a model based on the influence of a typhoon and its impact on evacuees. The model’s objective is to minimize the total evacuation distance, taking into account the distance constraint. The model is solved using the spatial analysis tools of Geographic Information Systems (GIS). It is then applied in Macao to solve the evacuation process for Typhoon Mangkhut 2018. The result is an evacuee allocation plan that can help the government organize evacuation efficiently. Furthermore, the number of evacuees allocated to shelters is compared with shelter capacities, which can inform government shelter construction in the future.

Funding

National Natural Science Foundation of China, grant number 71861167002.

Macao Science and Technology Development Fund, grant number 0049/2018/AFJ.

National Natural Science Foundation of China, grant number 71790613.

Tsinghua-Foshan Innovation Special Fund (TFISF), grant number 2018THFS0301.

History

School

  • Social Sciences and Humanities

Department

  • Geography and Environment

Published in

Sustainability

Volume

12

Issue

8

Publisher

MDPI AG

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Acceptance date

2020-04-15

Publication date

2020-04-18

Copyright date

2020

eISSN

2071-1050

Language

  • en

Depositor

Prof Dapeng Yu. Deposit date: 28 August 2020

Article number

3308

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