An Improved DPSIR-DEA Assessment Model for Urban Resilience: A Case Study of 105 Large Cities in China

Land Pub Date : 2024-07-25 DOI:10.3390/land13081133
Liudan Jiao, Bowei Han, Qilin Tan, Yu Zhang, X. Huo, Liu Wu, Ya Wu
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Abstract

Urban development is facing increasingly complex disturbances. Assessing large cities’ urban resilience is important for improving their ability to withstand disturbances and promoting sustainable development. Therefore, this paper establishes an improved assessment model for urban resilience based on the driving force–pressure–state–impact–response (DPSIR) and data envelopment analysis (DEA) model. The Malmquist index, Dagum Gini coefficient, and Markov chain were sequentially used for spatiotemporal evolution and differential resilience analysis. Then, 105 large Chinese cities were selected as case studies. The results indicate their overall resilience is relatively high; each year’s average resilience efficiency can achieve DEA effectiveness. The distribution pattern of resilience level presents a healthy olive-shaped structure. However, there is also a significant difference between the two poles. During the research period, the combined effect of technological efficiency improvement and technological progress resulted in the overall resilience slowly improving, and this process was more driven by technological innovation. At the same time, the overall regional difference in resilience also shows a narrowing trend, and the current spatial differences mainly come from the difference within subregions and super-density. In future transfer predictions, the resilience of large cities will show good stability with a higher probability of maintaining stability; if the resilience undergoes a transition, the probability of an increase will be higher than a decrease. Based on the life cycle process of resilience, this study selects indicators that can characterize the level of resilience according to the DPSIR model, which comprehensively reflects the characteristics of urban resilience. This study’s results can provide particular reference values for urban disaster response emergency planning and sustainable development construction, and it also provides new ideas for the assessment research of urban resilience.
改进的城市抗灾能力 DPSIR-DEA 评估模型:中国 105 个大城市案例研究
城市发展正面临着日益复杂的干扰。评估大城市的城市恢复力对于提高其抵御干扰的能力、促进可持续发展具有重要意义。因此,本文在动力-压力-状态-影响-反应(DPSIR)和数据包络分析(DEA)模型的基础上,建立了一个改进的城市弹性评估模型。先后使用马尔奎斯特指数、达古姆基尼系数和马尔科夫链进行时空演化和差异韧性分析。然后,选择中国 105 个大城市作为案例进行研究。结果表明,这些城市的整体恢复力相对较高,每年的平均恢复力效率可以达到 DEA 的有效性。复原力水平的分布格局呈现出健康的橄榄型结构。但两极之间也存在明显差异。研究期间,在技术效率提升和技术进步的共同作用下,整体恢复力缓慢提升,而这一过程更多地受到技术创新的推动。与此同时,区域整体恢复力差异也呈现缩小趋势,目前的空间差异主要来自于次区域内部差异和超密度差异。在未来转移预测中,大城市的恢复力将呈现良好的稳定性,保持稳定的概率较高;如果恢复力发生转变,上升的概率将高于下降的概率。基于韧性的生命周期过程,本研究根据 DPSIR 模型选取了能够表征韧性水平的指标,全面反映了城市韧性的特征。该研究成果可为城市救灾应急规划和可持续发展建设提供特定的参考价值,也为城市抗灾能力的评估研究提供了新思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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