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Ecological vulnerability assessment and spatial pattern optimization of resource-based cities: A case study of Huaibei City, China
Human and Ecological Risk Assessment ( IF 3.0 ) Pub Date : 2020-03-26 , DOI: 10.1080/10807039.2020.1744426
Haifeng Yang 1 , Guofang Zhai 1 , Yan Zhang 1
Affiliation  

Abstract

The continuous, intense exploitation of resources under rapid industrialization has made the ecological environment of resource-based cities increasingly vulnerability. Negative impacts of over-exploitation include soil erosion, declines in soil fertility, water pollution, and ground collapse—seriously threatening the survival and development of cities. We used Huaibei City, one of the representative coal resource-based cities, as a case study for measuring ecological vulnerability. We considered the interference effects of human mining activities, based on a typical Pressure-Sensitivity-Resilience (PSR) conceptual framework and constructed an ecological vulnerability index (EVI) system that couples natural and human factors. We then evaluated the EVI using the comprehensive index method. Finally, we combined a Bayesian network model with an entropy difference method, to optimize land use to minimize ecological vulnerability. We found that EVI ranged from 0.25 to 077, with highly vulnerable areas mainly concentrated in the southwest and north of the study area. The subset of {Soi = 1, MSA = 1} was selected as the optimal state subset of key variables for spatial pattern optimization, and primary and secondary optimization areas were mainly concentrated in Xiangshan and Duji Districts. This research will help protect the key ecological functional zones in the region, and provide a reference for policy-making in order to improve the comprehensive carrying capacity of resource-based cities.



中文翻译:

资源型城市生态脆弱性评估与空间格局优化-以淮北市为例

抽象的

在快速工业化进程中对资源的持续,密集开发,使得资源型城市的生态环境日益脆弱。过度开发的负面影响包括土壤侵蚀,土壤肥力下降,水污染和地面塌陷,严重威胁着城市的生存和发展。我们以具有代表性的煤炭资源型城市之一淮北市为例,对生态脆弱性进行了评估。我们基于典型的压力-敏感性-复原力(PSR)概念框架,考虑了人类采矿活动的干扰效应,并构建了将自然因素与人为因素相结合的生态脆弱性指数(EVI)系统。然后,我们使用综合指标法评估了EVI。最后,我们将贝叶斯网络模型与熵差法相结合,以优化土地利用,从而最大程度地降低生态脆弱性。我们发现EVI的范围从0.25到077,高度脆弱的地区主要集中在研究区域的西南和北部。{Soi = 1,MSA = 1}的子集被选为空间格局优化的关键变量的最佳状态子集,主要和次要优化区域主要集中在象山和杜集地区。这项研究将有助于保护该地区的关键生态功能区,并为提高资源型城市的综合承载力提供决策参考。高度脆弱地区主要集中在研究区域的西南和北部。{Soi = 1,MSA = 1}的子集被选为空间格局优化的关键变量的最佳状态子集,主要和次要优化区域主要集中在象山和杜集地区。这项研究将有助于保护该地区的关键生态功能区,并为提高资源型城市的综合承载力提供决策参考。高度脆弱地区主要集中在研究区域的西南和北部。{Soi = 1,MSA = 1}的子集被选为空间格局优化的关键变量的最佳状态子集,主要和次要优化区域主要集中在象山和杜集地区。这项研究将有助于保护该地区的关键生态功能区,并为提高资源型城市的综合承载力提供决策参考。

更新日期:2020-03-26
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