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Spatial Optimization of Land Use Pattern toward Carbon Mitigation Targets—A Study in Guangzhou

Author

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  • Shouyi Ding

    (Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
    Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing Monitoring and Early Warning, Guangzhou 510060, China)

  • Shumi Liu

    (Department of Land Management, Huazhong Agricultural University, Wuhan 430070, China)

  • Mingxin Chang

    (Department of Land Management, Huazhong Agricultural University, Wuhan 430070, China)

  • Hanwei Lin

    (Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
    Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing Monitoring and Early Warning, Guangzhou 510060, China)

  • Tianyu Lv

    (Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China)

  • Yujing Zhang

    (Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
    Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing Monitoring and Early Warning, Guangzhou 510060, China)

  • Chen Zeng

    (Department of Land Management, Huazhong Agricultural University, Wuhan 430070, China)

Abstract

Global climate change is one of the major challenges facing the world, and the spatial optimization of land use patterns has been regarded as critical in realizing carbon mitigation. In this study, the linear programming model and the Markov Chain model are integrated in different scenarios to optimize land use structure for low-carbon development. The land use pattern is then simulated through the adjusted convolutional neural network and cellular automata model, taking Guangzhou City as the case study area. The results reveal that construction land with high economic efficiency will increase its area, and the reaming types will experience slight changes, in 2035 in the natural development scenario and the economic priority scenario. Ecological land such as forest land, grassland, and water is partly occupied by construction land in the urban–rural fringe areas. The total carbon emissions decrease by 2.32% and 1.57% in these two scenarios. In the low-carbon-oriented scenario, the expansion of construction land is restricted, and the forest land and grassland undergo great expansion. The total carbon emission decreases by 18.95%—a figure much larger than that in the natural development scenario and the economic priority scenario. Our paper embeds the needs and constraints in land spatial planning into the spatial optimization of the land use pattern, which provides valuable references for low-carbon city development in the future.

Suggested Citation

  • Shouyi Ding & Shumi Liu & Mingxin Chang & Hanwei Lin & Tianyu Lv & Yujing Zhang & Chen Zeng, 2023. "Spatial Optimization of Land Use Pattern toward Carbon Mitigation Targets—A Study in Guangzhou," Land, MDPI, vol. 12(10), pages 1-19, October.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:10:p:1903-:d:1257134
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    References listed on IDEAS

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    1. Li, Jiasheng & Guo, Xiaomin & Chuai, Xiaowei & Xie, Fangjian & Yang, Feng & Gao, Runyi & Ji, Xuepeng, 2021. "Reexamine China’s terrestrial ecosystem carbon balance under land use-type and climate change," Land Use Policy, Elsevier, vol. 102(C).
    2. Chen, Chengjing & Liu, Yihua, 2021. "Spatiotemporal changes of ecosystem services value by incorporating planning policies: A case of the Pearl River Delta, China," Ecological Modelling, Elsevier, vol. 461(C).
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    Cited by:

    1. Yahui Zhang & Jianfeng Li & Siqi Liu & Jizhe Zhou, 2024. "Spatiotemporal Effects and Optimization Strategies of Land-Use Carbon Emissions at the County Scale: A Case Study of Shaanxi Province, China," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
    2. Jinmeng Lee & Xiaojun Yin & Honghui Zhu, 2024. "Spatial Optimization of Land Use Allocation Based on the Trade-off of Carbon Mitigation and Economic Benefits: A Study in Tianshan North Slope Urban Agglomeration," Land, MDPI, vol. 13(6), pages 1-18, June.
    3. Banglong Pan & Doudou Dong & Zhuo Diao & Qi Wang & Jiayi Li & Shaoru Feng & Juan Du & Jiulin Li & Gen Wu, 2024. "The Relationship Between Three-Dimensional Spatial Structure and CO 2 Emission of Urban Agglomerations Based on CNN-RF Modeling: A Case Study in East China," Sustainability, MDPI, vol. 16(17), pages 1-16, September.

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