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Change of the spatial and temporal pattern of ecological vulnerability: A case study on Cheng-Yu urban agglomeration, Southwest China

城市群 地理 脆弱性(计算) 人口 中国 城市化 分布(数学) 生态学 经济地理学 生物 数学分析 社会学 人口学 计算机科学 考古 计算机安全 数学
作者
Bohan Jiang,Wei Chen,Xiaoai Dai,Min Xu,Lanfa Liu,Tetsuro Sakai,Si‐Liang Li
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:149: 110161-110161 被引量:29
标识
DOI:10.1016/j.ecolind.2023.110161
摘要

China's urban economy has developed rapidly over the decades, and the Cheng-Yu urban agglomeration has become one of China's four typical urban agglomerations, with a large population and a high level of economic development. However, the conflict between humans and the environment is becoming increasingly prominent together with economic development. In order to protect the ecological environment in urban areas, thus scientific understanding and assessment of ecological vulnerability are beneficial to establishing regional conservation measures, and serve as a key means to maintain environmental health. Based on the “Sensitivity-Resilience-Pressure” (SRP) model, this study considered remote sensing, geographic and statistical data to construct an evaluation system for regional ecological vulnerability. In addition, the coupled AHP (Analytic hierarchy process)-Entropy weighting model was proposed to obtain the weight of each evaluation indicator and analyze the spatio-temporal distribution characteristics of the ecological vulnerability of the study area during 2000–2020. The changes and the divergence pattern were depicted by the transfer matrix, dynamic degree and spatial auto-correlation. The results indicated that the ecological vulnerability of Cheng-Yu urban agglomeration is mainly mild and moderate, with an overall high distribution in Chongqing and Chengdu, while low in the central and north zone (e.g., Ziyang, Mianyang). It is consistent with the distribution of HH (High-High) and L-L (Low-Low) clusters, respectively, having a significant positive spatial correlation. In particular, the severely vulnerable area increased from 7059 km2 in 2000 to 23553 km2 in 2020, with an increased rate of 233.66 %. Combining the transfer matrix and dynamic degree, it was found that the ecological environment underwent a rapid deterioration followed by a slow recovery. This study provides a scientific reference for the ecological policy making which serves sustainable urban development.
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