An Accessibility Analysis of Emergency Shelters in Shenzhen Using the Gaussian-Based Two-Step Floating Catchment Area Method and Clustering

Qing Yang, Yang Liu, Zhaolin Duan () and Xingxing Liu
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Qing Yang: School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China
Yang Liu: School of Management, Wuhan University of Technology, Wuhan 430070, China
Zhaolin Duan: School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China
Xingxing Liu: School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China

Sustainability, 2025, vol. 17, issue 12, 1-22

Abstract: The strategic planning of emergency shelters is vital for enhancing urban resilience against natural disasters, ensuring timely and equitable support for vulnerable populations. However, the existing studies often overlook the effects of fixed search radii and spatial heterogeneity in supply–demand matching. This study evaluated the spatial accessibility of emergency shelters in Shenzhen, a megacity in China, using a Gaussian two-step floating catchment area (G2SFCA) method integrated with K-means clustering. The analysis incorporated three service radii (1 km, 2.5 km, and 5 km) to assess accessibility levels across spatial scales. The results indicate the following: (1) The supply–demand balance of emergency shelters in Shenzhen varies significantly across service radii. A notable mismatch exists within 1000 m; at 2500 m, the demand in high-density areas is better met with reduced regional disparities, while at 5000 m, the spatial correlation between the supply and demand weakens considerably. (2) The cluster analysis revealed the distinct spatial clustering of supply–demand imbalances, primarily driven by population density. (3) The proposed method offers empirical support for optimized shelter allocation and improving the equity and efficiency of emergency resource distribution.

Keywords: emergency shelter accessibility; supply–demand matching; Gaussian two-step floating catchment area (G2FCA); K-means clustering (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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