Study on Spatiotemporal Evolution of Flood Disaster Resilience in Urban Agglomeration Based on Random Forest Optimization Algorithm
To improve the capacity of cities to cope with disasters,the study focuses on urban flood di-saster resilience. An evaluation index system for urban flood disaster resilience was established based on the "driving force-state-response (DSR)" model. An assessment model was constructed using a ran-dom forest optimization algorithm (RF). Model performance was evaluated using the root mean square error (RMSE) and the coefficient of determination (R2). Taking the Guanzhong Plain urban agglomera-tion as an example,the spatiotemporal evolution of urban flood disaster resilience in Xi'an,Baoji,Xianyang,Shangluo,Tongchuan,Weinan,Linfen,Yuncheng,Pingliang,Tianshui,and Qingyang from 2011 to 2020 was analyzed. The results showed that driving force and state significantly impact-ed the resilience level of urban flood disaster,while response had a milder impact. Over the time se-ries,significant differences in the development of flood disaster resilience levels were observed among the cities in the Guanzhong Plain urban agglomeration,though the overall trend was rising steadily. Tongchuan exhibited the most significant improvement in flood disaster resilience. Spatially,resil-ience levels showed a declining gradient from core cities to the periphery,with an imbalance in spatial distribution of flood disaster resilience levels among the cities. The research results provide guidance for the construction of resilient cities in the Guanzhong Plain urban agglomeration.
万方数据
维普
