| 基于SRP模型的中原城市群生态脆弱性分析与预测 |
| 摘要点击 823 全文点击 125 投稿时间：2024-03-03 修订日期：2024-05-13 |
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| 中文关键词 生态脆弱性 SRP评价 地理探测器 动态度 CA-Markov模型 |
| 英文关键词 ecological vulnerability SRP evaluation geographical detector dynamics CA-Markov model |
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| 中文摘要 |
| 中原城市群作为绿色生态发展示范规划区,研究其生态脆弱性对于了解该地区生态环境的现状和未来发展趋势具有重要意义. 基于“敏感性-恢复力-压力”模型,选取多源遥感空间统计数据,采用熵权法求取各指标的权重,构建中原城市群生态脆弱性评价指标体系；分析研究区2005~2020年的生态脆弱性的空间分布和时间变化特征；借助地理探测器模型,探究研究区生态脆弱性的驱动因素；并结合CA-Markov模型预测2025年的生态脆弱性状况. 结果表明：①中原城市群以轻度脆弱性为主,在空间上呈现西北高、东南低的趋势,在时间上,呈现先增加后下降的演变趋势. ②无论生态脆弱性的等级是上升还是下降,各等级都倾向于向最近的等级方向大规模转变,且重度脆弱性等级变化最为剧烈. ③建成区占比、生物丰度、植被覆盖度、人口密度和国内生产总值是造成中原城市群生态脆弱性的主要影响因素,且所有指标之间的交互作用明显增强. ④2025年的预测结果表明生态脆弱性呈下降趋势,生态环境有所改善. |
| 英文摘要 |
| 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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