Modeling and Spatialization of Biomass and Carbon Stock Using LiDAR Metrics in Tropical Dry Forest, Brazil

编号 010028904

推送时间 20210503

研究领域 森林生态 

年份 2021 

类型 期刊 

语种 英语

标题 Modeling and Spatialization of Biomass and Carbon Stock Using LiDAR Metrics in Tropical Dry Forest, Brazil

来源期刊 forest

期 第289期

发表时间 20210413

关键词 Caatinga vegetation;  aboveground biomass;  carbon stocks;  allometry;  statistical models; 

摘要 In recent years, with the growing environmental concern regarding climate change, there has been a search for efficient alternatives in indirect methods for the quantification of biomass and forest carbon stock. In this article, we seek to obtain pioneering results of biomass and carbon estimates from forest inventory data and LiDAR technology in a dry tropical forest in Brazil. We use forest inventory data in two areas together with data from the LiDAR flyby, generating estimates of local biomass and carbon levels obtained from local species. We approach three types of models for data analysis: Multiple linear regression with principal components (PCA), conventional multiple linear regression and stepwise multiple linear regression. The best fit total above ground biomass (TAGB) and total above ground carbon (TAGC) model was the stepwise multiple linear regression, concluding, then, that LiDAR data can be used to estimate biomass and total carbon in dry tropical forest, proven by an adjustment considered in the models employed, with a significant correlation between the LiDAR metrics. Our finding provides important information about the spatial distribution of TAGB and TAGC in the study area, which can be used to manage the reserve for optimal carbon sequestration. View Full-Text

服务人员 王璐

服务院士 蒋有绪

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