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Assessment and Simulation of Urban Ecological Environment Quality Based on Geographic Information System Ecological Index

Author

Listed:
  • Lusheng Che

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

  • Shuyan Yin

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

  • Junfang Jin

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

  • Weijian Wu

    (Sichuan Institute of Metal Geologic Survey, Chengdu 611730, China)

Abstract

The urban ecological environment is crucial to the quality of life of residents and the sustainable development of the region, and the assessment and prediction of the ecological environment quality can provide a scientific guidance for ecological environment management and improvement. We proposed a novel approach to assess and simulate the urban ecological environment quality using the Geographic Information System Ecological Index (GISEI). First, we calculated the remote sensing ecological index (RSEI) for Xi’an in 2020. Second, we selected land use data, mean annual temperature, and mean annual relative humidity as ecological indicators. We regressed these indicators on the RSEI to obtain the GISEI of Xi’an in 2020. Finally, we simulated the GISEI of Xi’an in 2030 by predicting the ecological indicators and analyzed the changes in the ecological environment quality. The results of the study show that the ecological environment quality in Xi’an in 2020 is better overall. By 2030, most of the ecological environment quality in Xi’an will be worse, and the proportion of the excellent area will decrease from 42.8% to 3.8%. The more serious ecological degradation is mainly located in the regions bordering the Qinling Mountains and the Guanzhong Plain, and the ecological environment quality in most areas of the Qinling Mountains will deteriorate from excellent to good.

Suggested Citation

  • Lusheng Che & Shuyan Yin & Junfang Jin & Weijian Wu, 2024. "Assessment and Simulation of Urban Ecological Environment Quality Based on Geographic Information System Ecological Index," Land, MDPI, vol. 13(5), pages 1-20, May.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:5:p:687-:d:1394417
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    References listed on IDEAS

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    1. Li, Yi & Zou, Changfu & Berecibar, Maitane & Nanini-Maury, Elise & Chan, Jonathan C.-W. & van den Bossche, Peter & Van Mierlo, Joeri & Omar, Noshin, 2018. "Random forest regression for online capacity estimation of lithium-ion batteries," Applied Energy, Elsevier, vol. 232(C), pages 197-210.
    2. Li Li & Zhichao Chen & Shidong Wang, 2022. "Optimization of Spatial Land Use Patterns with Low Carbon Target: A Case Study of Sanmenxia, China," IJERPH, MDPI, vol. 19(21), pages 1-22, October.
    3. Shangxiao Wang & Ming Zhang & Xi Xi, 2022. "Ecological Environment Evaluation Based on Remote Sensing Ecological Index: A Case Study in East China over the Past 20 Years," Sustainability, MDPI, vol. 14(23), pages 1-15, November.
    4. Graham Simpkins, 2017. "Progress in climate modelling," Nature Climate Change, Nature, vol. 7(10), pages 684-685, October.
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