Research on the Spatial Differentiation Pattern of High-Temperature Disaster Resilience and Strategies for Enhancing Resilience: A Case Study of Hangzhou, China

Shanfeng Zhang (), Yilin Xu, Hao Wu, Wenting Wu and Yuhao Lou
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Shanfeng Zhang: School of Design and Architecture, Zhejiang University of Technology, Hangzhou 310023, China
Yilin Xu: School of Design and Architecture, Zhejiang University of Technology, Hangzhou 310023, China
Hao Wu: Hangzhou Urban Planning and Design Institute, Hangzhou 310012, China
Wenting Wu: School of Design and Architecture, Zhejiang University of Technology, Hangzhou 310023, China
Yuhao Lou: Hangzhou Zhituo Space Planning and Design Co., Ltd., Hangzhou 310014, China

Sustainability, 2025, vol. 17, issue 6, 1-25

Abstract: With the intensification of climate change and urbanization, the impact of high-temperature disasters on urban resilience has become increasingly significant. Based on the “Pressure-State-Response” (PSR) model, this study proposes a novel assessment method for urban high-temperature disaster resilience. Through 15 evaluation indicators across 3 categories, we quantified the high-temperature disaster resilience level in Hangzhou and constructed a SOM-K-means second-order clustering algorithm to classify the study area into different resilience zones, exploring the spatial differentiation characteristics of high-temperature disaster resilience. The research results indicate the following: (1) Hangzhou exhibits a relatively low level of high-temperature disaster resilience, with a spatial distribution pattern showing a radial decrease from the main city area at the center, followed by a slight increase in the far periphery of the main city area. (2) The study area was divided into four distinct high-temperature disaster resilience zones, demonstrating significant spatial differentiation characteristics. This study innovatively integrates the PSR model with the SOM-K-means clustering method, providing a new perspective for the quantitative assessment and spatial zoning of urban high-temperature disaster resilience. The findings offer valuable decision-making support for enhancing urban resilience.

Keywords: high-temperature disaster; resilience evaluation; PSR model; SOM-K-means; enhancement strategies (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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