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Long-Term Ecological Environment Quality Evaluation and Its Driving Mechanism in Luoyang City

Author

Listed:
  • Hui Li

    (College Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China)

  • Haitao Jing

    (College Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China)

  • Geding Yan

    (College Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China)

  • Huanchao Guo

    (College Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China)

  • Wenfei Luan

    (College Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China)

Abstract

The quality of the ecological environment determines human well-being, and the degree of ecological environment quality has a significant impact on regional sustainable development. Currently, the assessment content of ecological environment quality in Luoyang is relatively single-indicator-based and is insufficient to comprehensively reflect the changes in the ecological environment quality of Luoyang city. Therefore, the study aims to use the Remote Sensing Ecological Index (RSEI), a comprehensive evaluation model, with Landsat remote sensing images and statistical yearbooks as the data sources, to evaluate the spatiotemporal dynamic changes in the ecological environment quality of Luoyang city from 2002 to 2022 through trend analysis and mutation testing; the study employs geographical detectors to analyze the driving factors about the changes in ecological environment quality. The study found that: (1) the average RSEI value in Luoyang city has increased by 0.102 in the past 20 years, indicating an overall improvement in the ecological environment quality of Luoyang city. (2) The northern region of the study area has lower RSEI values, while the southern region has better ecological environment quality, which corresponds to the fact that the northern part of Luoyang city has intensive human activities, while the southern part is characterized by higher vegetation coverage in mountainous areas. (3) The proportion of areas with medium and above ecological environment quality grades have increased from 47.2% to 67.5%, indicating a positive trend in future ecological environment quality changes. (4) The population change was the strongest single factor influencing the ecological environment quality change in Luoyang city. The interaction between temperature and GDP was relatively the strongest. The current ecological environment status in the study area is the result of the combined effects of natural and anthropogenic factors. The research conclusions contribute to improving regional ecological environment quality and are of great significance for the regional ecological environment planning and the achievement of sustainable development goals.

Suggested Citation

  • Hui Li & Haitao Jing & Geding Yan & Huanchao Guo & Wenfei Luan, 2023. "Long-Term Ecological Environment Quality Evaluation and Its Driving Mechanism in Luoyang City," Sustainability, MDPI, vol. 15(15), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11866-:d:1208743
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    References listed on IDEAS

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    1. Pariha Helili & Mei Zan, 2023. "Coupling Coordination Development of Urbanization and Ecological Environment in the Urban Agglomeration on the Northern Slope of the Tianshan Mountains, China," Sustainability, MDPI, vol. 15(5), pages 1-16, February.
    2. Na Chen & Gang Cheng & Jie Yang & Huan Ding & Shi He, 2023. "Evaluation of Urban Ecological Environment Quality Based on Improved RSEI and Driving Factors Analysis," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    3. Enjun Gong & Fangxin Shi & Zhihui Wang & Qingfeng Hu & Jing Zhang & Hongxin Hai, 2022. "Evaluating Environmental Quality and Its Driving Force in Northeastern China Using the Remote Sensing Ecological Index," Sustainability, MDPI, vol. 14(23), pages 1-18, December.
    4. Chaoran Gao & Jinxin Wang & Manman Wang & Yan Zhang, 2023. "Simulating Urban Agglomeration Expansion in Henan Province, China: An Analysis of Driving Mechanisms Using the FLUS Model with Considerations for Urban Interactions and Ecological Constraints," Land, MDPI, vol. 12(6), pages 1-23, June.
    5. Yossi Hadad & Baruch Keren & Gregory Gurevich, 2017. "Improving demand forecasting using change point analysis," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 3(2), pages 130-151.
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    Cited by:

    1. Anya Zhong & Chunming Hu & Li You, 2023. "Evaluation and Prediction of Ecological Restoration Effect of Beijing Wangping Coal Mine Based on Modified Remote Sensing Ecological Index," Land, MDPI, vol. 12(11), pages 1-19, November.

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