2022
DOI: 10.1155/2022/3013620
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Deducing Leading Factors of Spatial Distribution of Carbon Reserves in Nanjing Metropolitan Area Based on Random Forest Model

Abstract: 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 ev… Show more

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Cited by 2 publications
(2 citation statements)
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“…A random forest is an approach for machine learning that uses many trees to train and predict sample data. It builds many models by merging several weak classifiers, assesses the contribution of each variable under various models, and determines the relevance ranking of variables (Xue and Yan, 2022).…”
Section: Random Forest Modelmentioning
confidence: 99%
“…A random forest is an approach for machine learning that uses many trees to train and predict sample data. It builds many models by merging several weak classifiers, assesses the contribution of each variable under various models, and determines the relevance ranking of variables (Xue and Yan, 2022).…”
Section: Random Forest Modelmentioning
confidence: 99%
“…Plant-based carbon removal, or carbon sequestration, reduces greenhouse gas concentrations, especially CO2 [14]. Biogeophysical and economic limits exist for plant-based negative carbon removal [15]. Biomass, the living vegetation mass, has a direct correlation with carbon absorption potential [16].…”
Section: Introductionmentioning
confidence: 99%