[基于SRP模型的中原城市群生态脆弱性分析与预测]。

Q2 Environmental Science
Zong-Ze Zhao, Qian Ma, Yi Wang, Chao Ma, Hong-Tao Wang
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引用次数: 0

摘要

作为绿色生态发展规划示范区的中原城市群生态脆弱性分析与预测,对于了解该区域生态环境现状及未来发展趋势具有重要意义。本文以“敏感性-恢复力-压力”(sensitivity-resilience-pressure, SRP)模型为基础,选取多源遥感空间统计数据,采用熵权法确定各指标权重,构建了中原城市群生态脆弱性评价指标体系。分析了2005 - 2020年研究区生态脆弱性的时空变化特征。利用地理探测器模型,探索研究区生态脆弱性驱动因素,并结合CA-Markov模型预测2025年研究区生态脆弱性状况。结果表明:①中原城市群以轻度脆弱性为主,呈现出西北高、东南低的空间趋势;随着时间的推移,它呈现出先增加后减少的演化趋势。②无论生态脆弱性等级是升高还是降低,各等级都有向最近等级大规模过渡的趋势,其中以严重脆弱性等级变化最为显著。③建筑面积百分比、生物丰度、植被覆盖度、人口密度和国内生产总值(GDP)是影响中原城市群生态脆弱性的显著因子,且各指标之间的交互作用显著增强。④2025年的预测结果显示生态脆弱性呈下降趋势,生态环境有所改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Analysis and Prediction of Ecological Vulnerability of the Central Plains Urban Agglomeration Based on the SRP Model].

The analysis and prediction of ecological vulnerability of the Central Plains Urban Agglomeration, as a demonstration area for green ecological development planning, is important for understanding the current status and future development trends of the ecological environment in this region. This article is based on the "sensitivity-resilience-pressure" (SRP) model, selecting multi-source remote sensing spatial statistical data, using the entropy weight method to determine the weights of each index, and constructing an evaluation index system for the ecological vulnerability of the Central Plains Urban Agglomeration. This study analyzed the spatial distribution and temporal changes of ecological vulnerability in the study area from 2005 to 2020. With the help of the geographical detector model, the driving factors of ecological vulnerability in the study area were explored and combined with the CA-Markov model to predict the ecological vulnerability status in 2025. The results showed that: ① The Central Plains urban agglomeration was primarily characterized by mild vulnerability, exhibiting a spatial trend of higher vulnerability in the northwest and lower in the southeast. Over time, it displayed an evolutionary trend of first increasing and then decreasing. ② Regardless of whether the level of ecological vulnerability increased or decreased, each level tended to undergo large-scale transitions toward the nearest level, with the most important changes occurring in the severe vulnerability level. ③ Building area percentage, biological abundance, fractional vegetation cover, population density, and gross domestic product (GDP) were notable influencing factors that contributed to the ecological vulnerability of the Central Plains urban agglomeration, and the interaction between all these indicators had significantly increased. ④ The predictive results for 2025 showed a downward trend in ecological vulnerability, indicating an improvement in the ecological environment.

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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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