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Land Use and Carbon Storage Evolution Under Multiple Scenarios: A Spatiotemporal Analysis of Beijing Using the PLUS-InVEST Model

Author

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  • Jiaqi Kang

    (School of Life & Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China
    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Linlin Zhang

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China)

  • Qingyan Meng

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China)

  • Hantian Wu

    (China Institute for Geo-Environmental Monitoring, Beijing 100081, China)

  • Junyan Hou

    (Beijing Institute of Remote Sensing Information, Beijing 100011, China)

  • Jing Pan

    (Institute of Remote Sensing Satellite, China Academy of Space Technology, Beijing 100094, China)

  • Jiahao Wu

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    State Key Laboratory of Internet of Things for Smart City and Department of Ocean Science and Technology, University of Macau, Macao 999078, China)

Abstract

The carbon stock in terrestrial ecosystems is closely linked to changes in land use. Understanding how land use alterations affect regional carbon stocks is essential for maintaining the carbon balance of ecosystems. This research leverages land use and driving factor data spanning from 2000 to 2020, utilizing the Patch-generating Land Use Simulation (PLUS) model alongside the InVEST ecosystem services model to examine the temporal and spatial changes in carbon storage across Beijing. Additionally, four future scenes for 2030—urban development, natural development, cropland protection, as well as eco-protection—are explored, with the PLUS and InVEST models employed to emulate dynamic land use changes and the corresponding carbon stock variations. The results show that the following: (1) Between 2000 and 2020, changes in land use resulted in a significant decline in carbon storage, with a total reduction of 1.04 × 10 7 tons. (2) From 2000 to 2020, agricultural, forest, and grassland areas in Beijing all declined to varying extents, while built-up land expanded by 1292.04 km 2 (7.88%), with minimal changes observed in water bodies or barren lands. (3) Compared to the carbon storage distribution in 2020, carbon storage in the 2030 urban development scenario decreased by 6.99 × 10 6 tons, highlighting the impact of rapid urbanization and the expansion of built-up areas on the decline in carbon storage. (4) In the ecological protection scenario, the optimization of land use structure resulted in an increase of 6.01 × 10 5 tons in carbon storage, indicating that the land use allocation in this scenario contributes to the restoration of carbon storage and enhances the carbon sink capacity of the urban ecosystem. This study provides valuable insights for policymakers in optimizing ecosystem carbon storage from a land use perspective and offers essential guidance for the achievement of the “dual carbon” strategic objectives.

Suggested Citation

  • Jiaqi Kang & Linlin Zhang & Qingyan Meng & Hantian Wu & Junyan Hou & Jing Pan & Jiahao Wu, 2025. "Land Use and Carbon Storage Evolution Under Multiple Scenarios: A Spatiotemporal Analysis of Beijing Using the PLUS-InVEST Model," Sustainability, MDPI, vol. 17(4), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1589-:d:1591472
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    References listed on IDEAS

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    Cited by:

    1. Zeyu Li & Haichen Zhang & Linxing Zhao & Maqiang Xu & Changxian Qi & Qiang Gu & Yanhe Wang, 2025. "Spatiotemporal Simulation Prediction and Driving Force Analysis of Carbon Storage in the Sanjiangyuan Region Based on SSP-RCP Scenarios," Sustainability, MDPI, vol. 17(16), pages 1-26, August.
    2. Tian Bai & Junming Yang & Xinyu Wang & Rui Su & Samuel A. Cushman & Gillian Lawson & Manshu Liu & Guifang Wang & Donghui Li & Jiaxin Wang & Jingli Zhang & Yawen Wu, 2025. "Multi-Source Data-Driven Spatiotemporal Study on Integrated Ecosystem Service Value for Sustainable Ecosystem Management in Lake Dianchi Basin," Sustainability, MDPI, vol. 17(9), pages 1-22, April.

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