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刘立志, 韩震. 基于遥感生态指数的上海市城市生态质量评价及驱动力研究[J]. 四川林业科技, 2023, 44(6): 48−54. DOI: 10.12172/202303020002
引用本文: 刘立志, 韩震. 基于遥感生态指数的上海市城市生态质量评价及驱动力研究[J]. 四川林业科技, 2023, 44(6): 48−54. DOI: 10.12172/202303020002
LIU L Z, HAN Z. Study on urban ecological quality evaluation and driving forces in Shanghai based on remote sensing ecological index[J]. Journal of Sichuan Forestry Science and Technology, 2023, 44(6): 48−54. DOI: 10.12172/202303020002
Citation: LIU L Z, HAN Z. Study on urban ecological quality evaluation and driving forces in Shanghai based on remote sensing ecological index[J]. Journal of Sichuan Forestry Science and Technology, 2023, 44(6): 48−54. DOI: 10.12172/202303020002

基于遥感生态指数的上海市城市生态质量评价及驱动力研究

Study on Urban Ecological Quality Evaluation and Driving Forces in Shanghai Based on Remote Sensing Ecological Index

  • 摘要: 定量监测生态质量变化和揭示背后驱动力对于生态环境保护和持续发展具有重要意义。以上海市为例,通过构建遥感生态指数(RSEI),分析了2013—2019年上海市生态质量,结合转移矩阵对上海市生态质量时空变化情况进行了研究,并利用地理探测器分析了影响上海市生态质量的驱动因素。结果表明: 2013—2019年上海市生态质量发生了明显变化,RSEI下降率为17.19%;社会经济、人类活动和自然环境对RSEI的影响均较强,在单因子探测中,人口密度的影响程度最大,双因子探测交互作用强于单因子探测作用,研究成果可为上海市生态环境保护提供理论支撑。

     

    Abstract: Quantitative monitoring of ecological quality changes and revealing the driving forces behind them are of great significance for ecological environmental protection and sustainable development. Taking Shanghai as an example, the ecological quality of Shanghai from 2013 to 2019 was analyzed by constructing the Remote Sensing Ecological Index (RSEI), and the spatial-temporal change of the ecological quality of Shanghai was studied by combining the transfer matrix. The driving factors affecting the ecological quality of Shanghai were analyzed by using the geographical detector. The results showed that the ecological quality of Shanghai changed significantly from 2013 to 2019, and the decline rate of RSEI is 17.19%. Socioeconomics, human activities and natural environment all had strong impacts on RSEI. In the single-factor detection, population density had the greatest impact, and the interaction of the two-factor detection was stronger than that of the single-factor detection. The research results can provide theoretical support for ecological environment protection in Shanghai.

     

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