基于PLUS模型的粤港澳大湾区土地利用演变的多情景模拟研究

    Predicting Land Use Changes in the Guangdong-Hong Kong-Macao Greater Bay Area Under Alternative Scenarios Using the PLUS Model

    • 摘要: 在全球气候变化背景下,研究未来气候变化情景下的土地利用变化具有重要意义,可揭示城市发展的多模态路径,为优化土地资源再分配和可持续发展政策提供科学依据。本文基于粤港澳大湾区2010~2020年土地利用演变分析,耦合CMIP 6提供的共享社会经济路径(Shared Socioeconomic Pathways, SSPs)和代表性浓度路径(Representative Concentration Pathways, RCPs)情景框架,利用Patch-generating Land Use Simulation (PLUS) 模型模拟2030~2050年土地利用格局进行预测。结果表明: PLUS模型对2020年土地利用的模拟总体精度为87.88%,Kappa指数为0.816,满足土地利用变化模拟的要求。2030~2050年间城市建设用地将持续增加,不同情景下的增长速率依次为SSP5.85 > SSP2.45 > SSP1.19; 耕地、林地和水域面积将持续减少,其中在SSP5.85情景下耕地和林地减缩幅度最大。在SSP1.19情景维持较高水平的耕地−林地−水域系统稳定性,空间格局契合“山水林田湖草沙生命共同体”的生态理念,较好地平衡城市发展与生态保护需求。研究SSP1.19情景可为粤港澳大湾区国土空间优化和韧性发展的土地资源配置提供科学参考。

       

      Abstract: Investigating land use change under future climate change scenarios is essential for revealing multimodal trajectories of urban development, which provides a scientific foundation for optimizing land resource redistribution and formulating sustainable development policies. This study analyzes the historical land use evolution in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2020 and couples the Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) framework from CMIP6. Using the Patch-generating Land Use Simulation (PLUS) model, land use patterns in the GBA for the period 2030~2050 under multiple scenarios are simulated. The simulation results for 2020 achieve an overall accuracy of 87.88% and a Kappa coefficient of 0.816, indicating reliable performance for projecting future changes. The findings reveal a continuous expansion of built-up land between 2030 and 2050 across all scenarios, with the growth rate ranked as SSP5.85 > SSP2.45 > SSP1.19. In contrast, cultivated land, forest land, and water bodies are projected to decline, with the most substantial reductions occurring under the SSP5.85 scenario. Notably, the SSP1.19 scenario maintains relatively high stability in the structure of cultivated land, forest land, and water bodies. Its spatial configuration aligns with the concept of ‘mountains, rivers, forests, farmlands, lakes, grasslands, and deserts as a community of life’ effectively balancing urban development needs with ecological conservation. Therefore, the land resource configuration under SSP1.19 offers a scientific basis for optimizing territorial spatial planning and supporting resilient development strategies in the GBA.

       

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