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Simulation of Spatiotemporal Land Use Changes for Integrated Model of Socioeconomic and Ecological Processes in China

Author

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  • Honglei Jiang

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Xia Xu

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Mengxi Guan

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Lingfei Wang

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Yongmei Huang

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Yinghui Liu

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

Land use/land cover changes (LULCC) have been affected by ecological processes as well as socioeconomic and human activities, resulting in several environmental problems. The study of the human–environment system combined with land use/land cover dynamics has received considerable attention in recent decades. We aimed to provide an integrated model that couples land use, socioeconomic influences, and ecosystem processes to explore the future dynamics of land use under two scenarios in China. Under Scenario A, the yield of grain continues to increase, and under Scenario B, the yield of grain remains constant. This study created a LULCC model by integrating a simple global socioeconomic model, a Terrestrial ecosystem simulator (TESim), and a land use allocation model. The results were analyzed by comparing spatiotemporal differences under predicted land use conditions in the two alternative scenarios. The simulation results showed patterns that varied between the two scenarios. In Scenario A, grassland will expand in the future and a large reduction in cropland will be observed. In Scenario B, the augmented expansion of cropland and a drastic shrinkage of forest area will be the main land use conversion features. Scenario A is more promising because more land is preserved for ecological restoration and urbanization, which is in line with China’s Grain for Green Program. Economic development should be based on ecological protection. The results are expected to add insight to sustainable land use development and regional natural resource management in China.

Suggested Citation

  • Honglei Jiang & Xia Xu & Mengxi Guan & Lingfei Wang & Yongmei Huang & Yinghui Liu, 2019. "Simulation of Spatiotemporal Land Use Changes for Integrated Model of Socioeconomic and Ecological Processes in China," Sustainability, MDPI, vol. 11(13), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:13:p:3627-:d:244875
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    References listed on IDEAS

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    4. Honglei Jiang & Xia Xu & Lingfei Wang & Tong Zhang, 2021. "Integrating Ecosystem Service Values and Economic Benefits for Sustainable Land Use Management in Semi-Arid Regions in Northern China," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
    5. Onggarbek Alipbeki & Gauhar Mussaif & Chaimgul Alipbekova & Aizada Kapassova & Pavel Grossul & Meirzhan Aliyev & Nursultan Mineyev, 2023. "Untangling the Integral Impact of Land Use Change, Economic, Ecological and Social Factors on the Development of Burabay District (Kazakhstan) during the Period 1999–2021," Sustainability, MDPI, vol. 15(9), pages 1-36, May.

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