Research on the location model of emergency rescue facilities based on disaster risk-A Case study of earthquake disaster.

Authors

Qian Li, Xing Ju, Tuo Meng, Mengchu Xiao, Yi Xu, Tengjian Li, Xiaoqing Zhao

Published in

PloS one. Volume 21. Issue 6. Pages e0350148. Epub Jun 24, 2026.

Abstract

Rational site selection for disaster relief supply reserve depots is crucial for mitigating natural disaster risks. This study constructs a site selection model for relief supply reserve depots based on an analysis of natural disaster risks. It identifies four disaster risk elements: hazard, exposure, vulnerability, and capacity by examining the definition of natural disaster risk and applying principles of disaster system theory. The relationships between these four elements and the selection of relief supply reserve depot locations are analyzed to develop the proposed site selection model. The model applies the entropy weight method and the geometric mean model to calculate comprehensive indicators across multiple regions, and the results for pre-disaster comprehensive regional factors are obtained. The model performs a targeted analysis of post-disaster regional losses by considering the relationships among hazard, exposure, vulnerability, and capacity and by distinguishing the risk characteristics of different disaster types. The study applies responsive technical methods to determine functional criteria for relief supply reserve depots using data sources such as regional GIS and satellite remote sensing data. Through multilevel constraint relationships, the model establishes a regional layout of multi-tiered relief supply reserve depots and ultimately integrates urban planning and other factors to determine candidate areas. The study is demonstrated through an extreme disaster scenario, specifically an earthquake of magnitude 7 or higher, in the western region of Yunnan, China. The resulting layout plan is relatively optimal, validating the effectiveness of the proposed model.

PMID:
42341011
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.