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Analysis of Ecological Environmental Quality Change in the Yellow River Basin Using the Remote-Sensing-Based Ecological Index

Author

Listed:
  • Zekang Yang

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

  • Jia Tian

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

  • Wenrui Su

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

  • Jingjing Wu

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

  • Jie Liu

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

  • Wenjuan Liu

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

  • Ruiyan Guo

    (School of Agriculture, Ningxia University, Yinchuan 750021, China)

Abstract

Establishing a method for characterizing spatiotemporal changes in the quality of the ecological environment in a timely and accurate manner is of great significance for the protection and sustainable development of the ecological environment in the Yellow River Basin (YRB). In this study, the Google Earth Engine (GEE) platform was used as a basis for constructing the remote-sensing-based ecological index (RSEI), and the RSEI was used to evaluate the quality of the ecological environment in the YRB. The results indicated that the mean of the RSEI values showed two stages of rapid improvement and slow improvement during 1990–2020. From 1990 to 2000, the average growth trend was 0.005/a with a growth rate of 21.15%, with the main contributions of bad to poor (101,800 km 2 ), poor to medium (56,900 km 2 ), and medium to good (70,800 km 2 ) ecological environmental quality levels. From 2000 to 2020, the average growth trend was 0.002/a with a growth rate of 2.13%, with main contributions of poor to bad (65,100 km 2 ) and good to medium (35,200 km 2 ) ecological environmental quality levels. From 1990 to 2020, there was a 76.38% improvement in the ecological environmental quality of the entire YRB, in which significant improvement accounted for 26.14%. The reductions in the ecological environmental quality accounted for 23.62%, of which significant reductions accounted for just 1.46%. The improvement in the ecological environmental quality of the YRB showed a trend of increasing sustainability, which is expected to continue. The distribution of the ecological environmental quality in the YRB showed obvious regional aggregation, whereby cold spots were concentrated in the northern and central regions of the YRB, which are the sandy and hilly ravine areas of the Loess Plateau. However, the areas corresponding to hot spot clusters decreased with time, and their significance also decreased. Thus, our study demonstrates that the GEE platform can be used to determine the spatiotemporal changes in the ecological environmental quality of the YRB in a timely and accurate manner.

Suggested Citation

  • Zekang Yang & Jia Tian & Wenrui Su & Jingjing Wu & Jie Liu & Wenjuan Liu & Ruiyan Guo, 2022. "Analysis of Ecological Environmental Quality Change in the Yellow River Basin Using the Remote-Sensing-Based Ecological Index," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10726-:d:900388
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    References listed on IDEAS

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    1. Guo, Beibei & Fang, Yelin & Jin, Xiaobin & zhou, Yinkang, 2020. "Monitoring the effects of land consolidation on the ecological environmental quality based on remote sensing: A case study of Chaohu Lake Basin, China," Land Use Policy, Elsevier, vol. 95(C).
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    1. Lina Tang & Alimujiang Kasimu & Haitao Ma & Mamattursun Eziz, 2023. "Monitoring Multi-Scale Ecological Change and Its Potential Drivers in the Economic Zone of the Tianshan Mountains’ Northern Slopes, Xinjiang, China," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    2. Zhiyun Chen & Renrong Chen & Quan Guo & Yinglong Hu, 2022. "Spatiotemporal Change of Urban Ecologic Environment Quality Based on RSEI—Taking Meizhou City, China as an Example," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
    3. Xin Dai & Jianping Chen & Chenli Xue, 2023. "Spatiotemporal Patterns and Driving Factors of the Ecological Environmental Quality along the Jakarta–Bandung High-Speed Railway in Indonesia," Sustainability, MDPI, vol. 15(16), pages 1-24, August.

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