{"title":"Rural Ecosystem Health Assessment and Spatial Divergence—A Case Study of Rural Areas around Qinling Mountain, Shaanxi Province, China","authors":"Yuxia Xu, Qian Chen, Hui Zeng","doi":"10.3390/su16156323","DOIUrl":null,"url":null,"abstract":"The rapid progress of urbanization and rural revitalization in developing countries has led to dramatic changes to the rural ecological environment. Assessing the rural ecosystem health (REH) is a crucial foundation for promoting sustainable development in rural areas. This study, focusing on rural areas around the Qinling Mountains in Shaanxi Province, establishes an evaluation system based on appropriate evaluation indicators for assessing the composite ecosystem. This evaluation system comprises four rural ecosystem subsystems: resource, environment, society, and economy. By employing a comprehensive indicator evaluation model and remote sensing image data, this study examines the health status of rural ecosystems in the 40 counties and districts across the study area, as well as their spatial differentiation characteristics, using ArcGIS (10.8) spatial analysis. The REH scores of these areas range from 0.6856 to 0.8818, with a fluctuating downward trend from north to south. This suggests that the rural ecosystems around the Qinling Mountains in Shaanxi Province are relatively healthy, with the northern area being notably healthier than the southern area. Spatial Gini coefficient analysis reveals a much smaller coefficient for the overall ecosystem compared to the subsystems in the study area, indicating that the distribution of health levels is dispersed and not concentrated. After establishing REH grades and quantity metrics, the 40 counties and districts are categorized into 13 types, followed by an analysis of the influencing factors for each type. Recommendations and management strategies are then proposed to enhance the health of rural ecosystems.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"38 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/su16156323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The rapid progress of urbanization and rural revitalization in developing countries has led to dramatic changes to the rural ecological environment. Assessing the rural ecosystem health (REH) is a crucial foundation for promoting sustainable development in rural areas. This study, focusing on rural areas around the Qinling Mountains in Shaanxi Province, establishes an evaluation system based on appropriate evaluation indicators for assessing the composite ecosystem. This evaluation system comprises four rural ecosystem subsystems: resource, environment, society, and economy. By employing a comprehensive indicator evaluation model and remote sensing image data, this study examines the health status of rural ecosystems in the 40 counties and districts across the study area, as well as their spatial differentiation characteristics, using ArcGIS (10.8) spatial analysis. The REH scores of these areas range from 0.6856 to 0.8818, with a fluctuating downward trend from north to south. This suggests that the rural ecosystems around the Qinling Mountains in Shaanxi Province are relatively healthy, with the northern area being notably healthier than the southern area. Spatial Gini coefficient analysis reveals a much smaller coefficient for the overall ecosystem compared to the subsystems in the study area, indicating that the distribution of health levels is dispersed and not concentrated. After establishing REH grades and quantity metrics, the 40 counties and districts are categorized into 13 types, followed by an analysis of the influencing factors for each type. Recommendations and management strategies are then proposed to enhance the health of rural ecosystems.