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Coupled Assessment of Land Use Changes and Ecological Benefits Using Multi-Source Remote Sensing Data

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  • Jin Guo

    (Jiangxi Key Laboratory of Watershed Ecological Process and Information, East China University of Technology, Nanchang 330013, China
    Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, East China University of Technology, Nanchang 330013, China
    School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China
    Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China)

  • Xiaojian Wei

    (Jiangxi Key Laboratory of Watershed Ecological Process and Information, East China University of Technology, Nanchang 330013, China
    Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, East China University of Technology, Nanchang 330013, China
    School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China
    Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China)

  • Fuqing Zhang

    (Jiangxi Key Laboratory of Watershed Ecological Process and Information, East China University of Technology, Nanchang 330013, China
    Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, East China University of Technology, Nanchang 330013, China
    School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China
    Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China)

  • Yubo Ding

    (Jiangxi Key Laboratory of Watershed Ecological Process and Information, East China University of Technology, Nanchang 330013, China
    Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, East China University of Technology, Nanchang 330013, China
    School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China
    Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China)

Abstract

The Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR), serving as a pivotal hub for coordinated economic and ecological development in central China, is characterized by marked ecological fragility and climate sensitivity. Investigating the land use dynamics and ecological benefit changes within this region holds critical strategic significance for balancing regional development with the construction of ecological security barriers. This study systematically analyzed the spatiotemporal variations in land use/land cover (LULC) across the UAMRYR, using multi-source remote sensing data, climatic factors, land conditions, and anthropogenic influences. By integrating the four-quadrant model and the coupling degree model, we developed a remote sensing ecological index (RSEI)–ecological service index (ESI) coupling evaluation framework to assess the spatiotemporal evolution patterns of changes in ecological benefits in the region. Furthermore, we employed Geodetector analysis to identify the key influencing factors driving the RSEI–ESI coupling relationship and their interactive mechanisms. The research findings are as follows: (1) The ecological regional pattern has changed. The area of Quadrant I (RSEI > 0.5 and ESI > 0.5) decreased by 13,800 km 2 , whereas Quadrants II (RSEI < 0.5 and ESI > 0.5) and IV (RSEI > 0.5 and ESI < 0.5) increased by 14,900 km 2 and 3500 km 2 , respectively. Quadrant III (RSEI < 0.5 and ESI < 0.5) remained relatively stable. This indicates that the imbalance in ecological functional spaces has intensified, affecting key ecological processes. (2) The quantitative analysis of the spatiotemporal evolution characteristics of the RSEI and ESI revealed contrasting trends: the RSEI decreased by 0.006, whereas the ESI showed a slight increase of 0.001. (3) The ranking of the driving factors indicated that the Normalized Difference Vegetation Index (NDVI) and the mean annual rainfall (MAP) were the primary factors driving ecological evolution, while the influence of economic driving factors was relatively weak. This study establishes a three-pillar framework (quadrant-based diagnosis, Geodetector-driven analysis, and RSEI–ESI coupled interventions) to guide precision-based ecological restoration and spatial governance.

Suggested Citation

  • Jin Guo & Xiaojian Wei & Fuqing Zhang & Yubo Ding, 2025. "Coupled Assessment of Land Use Changes and Ecological Benefits Using Multi-Source Remote Sensing Data," Agriculture, MDPI, vol. 15(13), pages 1-27, June.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:13:p:1358-:d:1687124
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    References listed on IDEAS

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    1. Weisong Li & Wanxu Chen & Jiaojiao Bian & Jun Xian & Li Zhan, 2022. "Impact of Urbanization on Ecosystem Services Balance in the Han River Ecological Economic Belt, China: A Multi-Scale Perspective," IJERPH, MDPI, vol. 19(21), pages 1-18, November.
    2. Lei Wang & Wenyi Yang & Yueyun Yuan & Chengliang Liu, 2019. "Interurban Consumption Flows of Urban Agglomeration in the Middle Reaches of the Yangtze River: A Network Approach," Sustainability, MDPI, vol. 11(1), pages 1-14, January.
    3. Linlin Zhang & Guanghui Qiao & Huiling Huang & Yang Chen & Jiaojiao Luo, 2021. "Evaluating Spatiotemporal Distribution of Residential Sprawl and Influencing Factors Based on Multi-Dimensional Measurement and GeoDetector Modelling," IJERPH, MDPI, vol. 18(16), pages 1-18, August.
    4. Ming Shi & Fei Lin & Xia Jing & Bingyu Li & Yang Shi & Yimin Hu, 2023. "Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau," Sustainability, MDPI, vol. 15(18), pages 1-25, September.
    5. Peres-Neto, Pedro R. & Jackson, Donald A. & Somers, Keith M., 2005. "How many principal components? stopping rules for determining the number of non-trivial axes revisited," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 974-997, June.
    6. Ding, Meiying & Shen, Zhi-Yang & Baležentis, Tomas & Chen, Xueli, 2025. "Climate change and marginal abatement cost: Policy insights on international treaty," Energy, Elsevier, vol. 321(C).
    7. Xiaoyan Jiang & Boyu Wang & Qinhua Fang & Peiyuan Bai & Ting Guo & Qi Wu, 2024. "Ecological Zoning Management Strategies in China: A Perspective of Ecosystem Services Supply and Demand," Land, MDPI, vol. 13(7), pages 1-20, July.
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