You Xiaotong, Sun Yanan, Liu Jiawei
School of Economics and Management, Nantong University, No. 9 Seyuan Road, Nantong, 226019 Jiangsu People's Republic of China.
Nat Hazards (Dordr). 2022;113(3):1751-1782. doi: 10.1007/s11069-022-05368-x. Epub 2022 May 4.
This research uses panel data of cities in Jiangsu from 2009 to 2018 to construct a resilience framework that measures the level of urban resilience. A combination of the entropy method, Theil index, , and the Spatial Durbin Model (SDM) is used to explore regional resilience development differences, the spatial correlation characteristics of urban resilience, and its influencing factors. The study finds that: (1) The spatial heterogeneity of regional resilience development is significant, as the overall level of resilience presents a spatial distribution pattern of descending from southern Jiangsu to central Jiangsu and to northern Jiangsu. (2) The total Theil index shows a wave-like downward trend during the study period. The differences between southern Jiangsu, central Jiangsu, and northern Jiangsu make up the main reason for the overall difference of urban resilience in Jiangsu Province. Among the three regions, the gap in resilience development level within southern Jiangsu is the largest. (3) There is a clear positive spatial correlation between urban resilience in the province and an obvious agglomeration trend of urban resilience levels. Among all subsystems, urban ecological resilience is the weakest and needs to be further improved. (4) Lastly, among the five factors affecting urban resilience, general public fiscal expenditure/GDP, which characterizes government factors, has the largest positive impact on urban resilience, while foreign trade has a negative impact. In the following studies, the theme of urban resilience should be constantly deepened, and more extensive data monitoring should be carried out for the urban system to improve the diversity of data sources, so as to assess urban resilience more accurately.
The online version contains supplementary material available at 10.1007/s11069-022-05368-x.
本研究使用2009年至2018年江苏省城市的面板数据构建了一个衡量城市韧性水平的韧性框架。采用熵值法、泰尔指数和空间杜宾模型（SDM）相结合的方法，探讨区域韧性发展差异、城市韧性的空间关联特征及其影响因素。研究发现：（1）区域韧性发展的空间异质性显著，韧性总体水平呈现出从苏南向苏中再到苏北递减的空间分布格局。（2）研究期间泰尔指数总体呈波浪式下降趋势。苏南、苏中、苏北之间的差异是江苏省城市韧性总体差异的主要原因。在这三个区域中，苏南内部韧性发展水平差距最大。（3）省内城市韧性之间存在明显的正空间相关性，城市韧性水平呈现出明显的集聚趋势。在所有子系统中，城市生态韧性最弱，需要进一步提升。（4）最后，在影响城市韧性的五个因素中，表征政府因素的一般公共财政支出/国内生产总值对城市韧性的正向影响最大，而对外贸易则有负面影响。在后续研究中，应不断深化城市韧性主题，对城市系统开展更广泛的数据监测，以提高数据来源的多样性，从而更准确地评估城市韧性。
网络版包含可在10.1007/s11069-022-05368-x获取的补充材料。
