基于 ERI-ESV 地理探测器的 "生产-生活-生态空间 "发展模式的环境效益和驱动力分析

Land Pub Date : 2024-07-15 DOI:10.3390/land13071059
Xi Zhou, Guohua Ji, Feng Wang, Xiang Ji, Cheng Hou
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引用次数: 0

摘要

本研究基于1980-2020年五期Landsat遥感数据,构建了景观生态风险-生态系统服务价值评价模型,并与地理探测模型相结合,分析了徐州规划区 "生产-生活-生态空间 "格局发展的环境效益及其驱动因素。研究结果如下(1) 在过去的 40 年中,生活空间的扩张极大地侵占了邻近的农业生产区和森林、草原等生态空间。具体而言,农业用地、森林和草地面积分别减少了 277.39 平方公里、23.8 平方公里和 12.93 平方公里;相比之下,城市和农村生活空间分别增加了 238.62 平方公里和 58.92 平方公里,同时工业生产区、水体和其他生态空间也有所增加。(2)40 年间,研究区的景观生态风险(ERI)和生态系统服务价值(ESV)均呈下降趋势。ERI中的高风险区和中高风险区的比例分别下降了5.19%和7.50%,而低、较低和中等生态风险区的比例分别上升了6.40%、3.22%和3.07%。此外,低生态风险区增加了 14.22%,而高和中高生态风险区的比例减少了 1.16%。(3) ERI 与 ESV 存在显著的空间正相关。森林、水体、草地等生态空间密集的区域,尤其是贾汪区东北部和铜山区东南部,区域生态系统服务质量较高。ERI和ESV以 "高-高 "和 "低-高 "聚集为主。相反,在研究区的西南部,由于生活空间的扩大,部分农田、林地和草地转化为风险较低的建设用地,导致区域生态系统服务质量下降。ERI与ESV的局部空间相关性由 "高-高"、"低-低"、"低-高 "集聚变为 "低-低 "集聚。(4) 影响 "生产-生活-生态空间 "空间分异的关键因素包括 GDP、人口密度、土壤类型以及与城镇和道路的距离。其中,人口密度与土壤类型的交互作用对 "生产-生活-生态空间 "格局的变化影响最为显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the Environmental Benefits and Driving Forces of the Development of the “Production–Living–Ecological Space” Pattern Based on the ERI-ESV Geodetector
Based on five periods of Landsat remote sensing data from 1980 to 2020, this study constructs a landscape ecological risk-ecosystem service value evaluation model and integrates it with a geodetector model to analyse the environmental benefits of the development of the “production–living–ecological space” pattern and its driving factors in the Xuzhou planning area. The results of the study are as follows: (1) Over the past 40 years, the expansion of living spaces has significantly encroached upon adjacent agricultural production areas and ecological spaces, such as forests and grasslands. Specifically, the areas of agricultural land, forests, and grassland have been diminished by 277.39 km2, 23.8 km2 and 12.93 km2, respectively; in contrast, urban and rural living spaces have increased by 238.62 km2 and 58.92 km2, alongside a rise in industrial production areas, water bodies, and other ecological spaces. (2) Throughout the 40-year period, both the landscape ecological risk (ERI) and ecosystem service value (ESV) in the study area have shown a decreasing trend. The proportion of high- and medium-high-risk areas of the ERI have decreased by 5.19% and 7.50%, respectively, while low, lower, and medium ecological risk areas have increased by 6.40%, 3.22% and 3.07%, respectively. In addition, low-ESV areas have increased by 14.22%, while the proportion of high- and medium-high-ESV areas have decreased by 1.16%. (3) There is a significant positive spatial correlation between the ERI and ESV. Regions with dense ecological spaces comprising forests, water bodies, and grasslands, particularly in the northeastern part of the Jiawang District and the southeastern part of the Tongshan District, demonstrate superior regional ecosystem service quality. The ERI and ESV are dominated by “high–high” and “low–high” aggregation. Conversely, in the southwestern part of the study area, the expansion of living space has led to the transformation of some agricultural land, forest land, and grassland into less risky construction land, resulting in a decline in the quality of regional ecosystem services. The local spatial correlation between the ERI and ESV changed from “high–high”, “low–low”, “low–high” agglomeration to “low–low” agglomeration. (4) Key factors influencing the spatial differentiation of the “production–living–ecological space” include the GDP, population density, soil type, and the distance to towns and roads. Among these, the interaction between population density and soil type has the most significant effect on the changes in the pattern of the “production–living–ecological space”.
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