Spatiotemporal Evolution and Influencing Factors for Urban Resilience in China: A Provincial Analysis
Auteur(s): |
Beibei Zhang
Yizhi Liu Yan Liu Sainan Lyu |
---|---|
Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 1 février 2024, n. 2, v. 14 |
Page(s): | 502 |
DOI: | 10.3390/buildings14020502 |
Abstrait: |
In the current era, as modern cities increasingly face environmental disasters and inherent challenges, the creation and enhancement of resilient cities have become critical. China’s urban resilience exhibits significant imbalances and inadequacies at the provincial level. This study delves into the evolution of urban resilience in various Chinese provinces, offering valuable insights for building and nurturing resilient cities. Initially, a comprehensive evaluation system for China’s urban resilience was established, incorporating 24 indicators across three key resilience aspects: resistance, adaptability, and recovery. The entropy weight method was used to develop an urban resilience evaluation model, and the Moran index and spatial cold–hot-spot analysis were applied to examine the spatiotemporal dynamics of urban resilience across China’s 31 provinces from 2012 to 2021. Moreover, the geographically and temporally weighted regression model was employed to analyze the spatial distribution of factors affecting urban resilience. The results show a general upward trend in urban resilience across Chinese provinces, with notable regional differences and concentrations. A significant decrease in urban resilience is observed from southeastern coastal cities to inland regions. The regression model highlights spatial variations in the impact of different factors, with the same factor having varying effects in different provinces. This research provides a thorough understanding of the factors influencing urban resilience in China, contributing to both theoretical and practical discussions on the topic. It lays a strong scientific groundwork for the development and advancement of resilient cities in China. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
6.9 MB
- Informations
sur cette fiche - Reference-ID
10773722 - Publié(e) le:
29.04.2024 - Modifié(e) le:
05.06.2024