| 基于PLUS-InVEST-Geodector模型的苏州市碳储量时空变化及驱动力分析 |
| 摘要点击 294 全文点击 19 投稿时间：2024-05-09 修订日期：2024-07-11 |
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| 中文关键词 土地利用变化 碳储量 多情景模拟 PLUS模型 InVEST模型 Geodector模型 |
| 英文关键词 land use change carbon storage multi-scenario simulation PLUS model InVEST model Geodector model |
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| 中文摘要 |
| 城市的土地利用和土地覆被变化会对碳储量产生深远影响,直接关系到城市的碳平衡和气候适应能力.以苏州市为研究区,首先对2000~2020年土地利用数据进行转移矩阵分析,再基于修正后的碳密度系数耦合PLUS模型和InVEST模型,对2030年苏州市土地利用格局进行4种情景（惯性发展、防止城市扩张、耕地保护和生态保护）下的预测,核算2000~2020年间及2030年苏州市4种情景下生态系统的碳储量并分析土地利用转换对碳储量的影响,最后使用地理探测器模型分析碳储量的空间分异驱动力,探索了城市化程度较高地区的土地利用变化以及人为与自然活动对碳储量的影响机制.结果表明：①2000~2020年,苏州市的土地利用格局发生显著转变,耕地与林地面积不断缩减,耕地尤为突出,主要转变为建设用地.②2000~2020年,苏州市碳储量损失3 750 195.27 t.耕地和水域为主要碳汇区域,其碳储量分别占总碳储量的39.93%和33.65%.此外,苏州市碳储量呈“由北向南逐渐递增”的空间分布特征.③苏州市土地利用转换对碳储量的影响存在差异.2000~2020年,耕地共转出1 632.758 km2,累计流失碳储量3 916 241.609 t,占总损失的96.9%.水域、建设用地和未利用土地转换分别增加了131 184.929、140 024.741和18 641.031 t碳储量.④从固碳角度来看,生态保护情景相较于其他3种情景优势显著,为苏州市后续的碳减排政策制定提供了有力的依据和指导.⑤苏州市碳储量的空间分异受到多种因素的共同影响,高程、气温、人口密度以及归一化植被指数（NDVI）是主要的影响因子,其中NDVI解释力最强,为0.29. |
| 英文摘要 |
| The changes in urban land use and land cover have profound impacts on carbon storage, directly affecting urban carbon balance and climate adaptation capacity. Taking Suzhou City as the study area, this study first conducts a transition matrix analysis of land use data from 2000 to 2020. Then, based on the modified carbon density coefficient coupled with the PLUS and InVEST models, predictions are made for the land use pattern of Suzhou City in 2030 under four scenarios （business-as-usual development, urban sprawl prevention, farmland protection, and ecological conservation）. The ecosystem carbon storage from 2000 to 2020 and in 2030 under the four scenarios in Suzhou City are accounted for and the impact of land cover changes on carbon storage is analyzed. Finally, the Geodetector model is used to analyze the spatial differentiation driving forces of carbon storage. This study explores the mechanisms of land use change on carbon storage in regions with high urbanization levels. The results are as follows： ① From 2000 to 2020, Suzhou City's land use pattern underwent significant changes, with a continuous reduction in farmland and woodland, and the conversion of farmland to construction land was especially prominent. ② From 2000 to 2020, Suzhou City lost 3 750 195.27 t of carbon storage. Farmland and water bodies were the main carbon sink areas in the study area, accounting for 39.93% and 33.65% of the total carbon storage, respectively. Additionally, Suzhou City's carbon storage exhibited a spatial distribution characteristic of “gradual increase from north to south.” ③ The impact of land use conversion on carbon storage in Suzhou City varied. From 2000 to 2020, farmland was converted out of 1 632.758 km2, resulting in a cumulative loss of carbon storage of 3 916 241.609 t, accounting for 96.9% of the total loss. Conversions from water bodies, construction land, and unused land to other land types increased the total carbon storage by 131 184.929, 140 024.741, and 18 641.031 t, respectively. ④ From the perspective of carbon sequestration, the ecological conservation scenario was significantly advantageous compared to the other three scenarios, providing strong evidence and guidance for the formulation of Suzhou City's subsequent carbon reduction policies. ⑤ The spatial differentiation of carbon storage in Suzhou City was jointly influenced by various factors, with elevation, temperature, population density, and Normalized Difference Vegetation Index （NDVI） being the main influencing factors, among which NDVI had the strongest explanatory power, reaching 0.29. |
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