Wen Haijia, Huang Junhao, Qian Long, Li Zhuohang, Zhang Yalan, Zhang Jialan
Key Laboratory of New Technology for Construction of Cities in Mountain Area of the Ministry of Education, National Joint Engineering Research Center for Prevention and Control of Environmental GeoHazards in the TGR Area, School of Civil Engineering, Chongqing University, Chongqing, 400045, China.
J Environ Manage. 2024 Nov;370:122963. doi: 10.1016/j.jenvman.2024.122963. Epub 2024 Oct 21.
Cities, as complex systems with multi-interconnected subsystems, face significant challenges from both rapid urbanization and climate change. Ensuring high resilience in urban areas is essential for managing these dynamic risks effectively. This study introduces an innovative, data-driven approach to quantitatively analyze the spatial-temporal evolution patterns of urban resilience, validated through a case study of Chongqing, a representative mountainous city in China. Based on historical landslide data from Chongqing (2010-2020), which includes 4464 events, along with indicator data from the Chongqing Statistical Yearbook, we developed a comprehensive assessment framework. This framework incorporates 33 variables, covering indicators of physical-environmental resilience (PER) and socio-economic resilience (SER). The model integrates the Random Forest (RF) algorithm, Analytic Hierarchy Process (AHP), and Coupling Coordination Degree (CCD) model. Key findings include: (1) Social development in mountainous cities like Chongqing follows a point-to-area pattern. Although there is an overall increase in SER, the CCD in more developed areas (Chongqing urban circle) was generally higher than in less developed areas (northeastern and southeastern Chongqing) (2) The PER model demonstrated exceptional performance (AUC values consistently above 0.95). Spatiotemporal evolution models reveal that Chongqing maintains a high overall PER. Notably, from 2019 to 2020, the proportion of administrative units classified as highly resilient peaked at 24.5%, marking a historical high. (3) Multi-year average rainfall primarily impacts PER (ranked first), while Gross Domestic Product (GDP) significantly affect SER. The development of multi-dimensional recovery indicators provides a robust framework for assessing resilience against landslides in mountainous cities. The CCD model illustrates the importance of regional dynamic coordinated development in resilience trajectories. This study provides a detailed blueprint for the scientific development of resilient mountainous cities, emphasizing the need for a spatial-temporal perspective on resilience and the benefits of coordinated regional development.
城市作为具有多个相互关联子系统的复杂系统，面临着快速城市化和气候变化带来的重大挑战。确保城市地区的高韧性对于有效管理这些动态风险至关重要。本研究引入了一种创新的、数据驱动的方法来定量分析城市韧性的时空演变模式，并通过对中国典型山地城市重庆的案例研究进行了验证。基于重庆2010 - 2020年的历史滑坡数据（共4464起事件）以及《重庆统计年鉴》的指标数据，我们构建了一个综合评估框架。该框架纳入了33个变量，涵盖物理环境韧性（PER）和社会经济韧性（SER）指标。该模型整合了随机森林（RF）算法、层次分析法（AHP）和耦合协调度（CCD）模型。主要研究结果包括：（1）像重庆这样的山地城市社会发展呈点到面模式。虽然SER总体呈上升趋势，但较发达地区（重庆都市圈）的耦合协调度普遍高于欠发达地区（重庆东北部和东南部）。（2）PER模型表现优异（AUC值始终高于0.95）。时空演变模型显示重庆整体PER保持较高水平。值得注意的是，2019年至2020年，高韧性行政单位占比达到峰值24.5%，创历史新高。（3）多年平均降雨量主要影响PER（排名第一），而国内生产总值（GDP）对SER有显著影响。多维恢复指标的发展为评估山地城市抗滑坡韧性提供了一个有力框架。CCD模型说明了区域动态协调发展在韧性轨迹中的重要性。本研究为韧性山地城市的科学发展提供了详细蓝图，强调了从时空角度看待韧性的必要性以及区域协调发展的益处。
