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This paper takes Qitaihe City as the research area, Based on Landsat 5 TM satellite image data in 2007 and 2011, and Landsat 8 OLI data in 2014, 2019, and 2023, it calculates greenness index, humidity index, dryness index, and heat index. The Remote Sensing Ecological Index (RSEI) model is constructed using principal component analysis to evaluate the spatio-temporal variation of ecological quality in this region. The study shows that the ecological environment of Qitaihe City is generally good and has shown fluctuating improvement. The ecological quality in the northwest, northeast, and central areas is relatively poor, while the RSEI index in the southwest is significantly higher than other regions. In the hierarchical evaluation, the proportions of “poor” and “relatively poor” grades have decreased, while the proportions of “good” and “excellent” grades have increased, indicating an overall positive trend. The RSEI of each district and county has shown fluctuating growth, with Boli County exhibiting outstanding RSEI performance. The spatial distribution of RSEI is characterized by agglomeration, and the concentrated distribution of “high-high” and “low-low” areas is jointly driven by natural geographical conditions, human activity intensity, and ecological policies.

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Evaluation of Ecological Environment Quality in Qitaihe City Based on RSEI

  • 会议论文

  • 发表日期：

    2026年

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  • Yanan Wu,
  • Yu Cheng,
  • Feng Xu,
  • Songyan Wang,
  • Zhuo Zhang

摘要

This paper takes Qitaihe City as the research area, Based on Landsat 5 TM satellite image data in 2007 and 2011, and Landsat 8 OLI data in 2014, 2019, and 2023, it calculates greenness index, humidity index, dryness index, and heat index. The Remote Sensing Ecological Index (RSEI) model is constructed using principal component analysis to evaluate the spatio-temporal variation of ecological quality in this region. The study shows that the ecological environment of Qitaihe City is generally good and has shown fluctuating improvement. The ecological quality in the northwest, northeast, and central areas is relatively poor, while the RSEI index in the southwest is significantly higher than other regions. In the hierarchical evaluation, the proportions of “poor” and “relatively poor” grades have decreased, while the proportions of “good” and “excellent” grades have increased, indicating an overall positive trend. The RSEI of each district and county has shown fluctuating growth, with Boli County exhibiting outstanding RSEI performance. The spatial distribution of RSEI is characterized by agglomeration, and the concentrated distribution of “high-high” and “low-low” areas is jointly driven by natural geographical conditions, human activity intensity, and ecological policies.