College of Landscape Architecture, Nanjing Forestry University, No. 159 Longpan Road, Nanjing 210037, Jiangsu, China.
Comput Intell Neurosci. 2022 Aug 25;2022:3013620. doi: 10.1155/2022/3013620. eCollection 2022.
Improving carbon reserves is considered to be an important way to alleviate global warming. However, there is a lack of research work based on the perspective of metropolitan area, and there is also a lack of analysis on the leading influencing factors of spatial distribution of carbon storage in subregions of metropolitan area. In this study, Nanjing metropolitan area (NMA) is taken as the research area, and the InVEST model is used to calculate the spatial distribution of regional carbon reserves, and the evolution of carbon reserves distribution in recent 20 years is analyzed. Then, based on the random forest (RF) model, taking the whole study area and subareas as the research scope, a regression model of each selected impact factor and carbon reserves is established, and the leading factors of spatial distribution of carbon reserves in NMA are obtained. The results show that the overall carbon reserves level in the study area is in a downward trend. Through the application of the RF model, the leading factors of the spatial distribution of carbon reserves in NMA and its subareas are derived. The research proves that the application of the RF model in the analysis is helpful for city planners and governments to make plans and improve regional carbon storage more effectively.
提高碳储量被认为是缓解全球变暖的重要途径。然而，基于大都市区视角的研究工作还比较缺乏，对大都市区内部次区域碳储量空间分布的主导影响因素的分析也比较缺乏。本研究以南京都市圈（NMA）为研究区域，利用 InVEST 模型计算了区域碳储量的空间分布，并分析了近 20 年来碳储量分布的演变。然后，基于随机森林（RF）模型，以整个研究区和次区域为研究范围，建立了每个选定影响因素与碳储量的回归模型，得出了 NMA 碳储量空间分布的主导因素。结果表明，研究区域的整体碳储量水平呈下降趋势。通过 RF 模型的应用，得出了 NMA 及其次区域碳储量空间分布的主导因素。研究证明，RF 模型在分析中的应用有助于城市规划者和政府更有效地制定计划和提高区域碳储存。
