热带亚热带植物学报2025，Vol.33Issue(4)：417-427,11.DOI:10.11926/jtsb.4899
基于遥感的漓江流域喀斯特森林碳储量建模估测
Estimation and Modeling of Carbon Stocks in Karst Forests of Lijiang River Basin Using Remote Sensing
摘要
Abstract
To explore methods for quantifying the carbon sequestration capabilities of karst forests in the Lijiang River Basin and clarify the spatial distribution characteristics of forest carbon stocks within the basin,taking the karst forests in the Lijiang River Basin as the research object,a multiple linear regression model and a random forest model based on machine learning were established to predict the relationship between forest carbon stocks and remote sensing parameters with the help of field survey data and texture characteristics of remote sensing images.Additionally,the InVEST model and land use data were employed to simulate carbon stock scenarios for the years 2005,2010,2015,and 2020.The results showed that the random forest model outperformed the multiple linear regression model in simulating actual carbon stocks,exhibiting a higher coefficient of determination(0.726)and a lower root mean square error(8.742),indicating that there was a complex nonlinear relationship between carbon stocks and various remote sensing parameters.The average forest carbon density in the Lijiang River Basin was 27.48 t/hm2,with a minimum of 2.43 t/hm2 and a maximum of 94.35 t/hm2.The high carbon density areas were mainly distributed in the northern,northwestern,and eastern contour regions of the basin,while medium-density areas were primarily located in the midstream and southern tourist regions.Low-density areas were mainly distributed in urban built-up areas.The high carbon stock regions are predominantly covered by subtropical evergreen broad-leaved forests,while medium-density regions mostly consist of subtropical coni-ferous forests,evergreen orchards,and subtropical economic forests.This indicated that vegetation type and forest type significantly influence the spatial distribution of forest carbon stocks in the Lijiang River Basin.Over the past decade,due to the conversion of cropland and forestland to construction land,the change from high-value carbon storage area to low-value carbon storage area has gradually intensified.Therefore,it was verified the advantages and feasibility of combining remote sensing technology with field surveys in estimating carbon storage.For the karst forests in the Li River Basin,the multivariate regression model could effectively capture the quantitative relationship between carbon storage and vegetation index,as well as texture features,while the random forest model demonstrates had even higher fitting accuracy.关键词
碳储量/喀斯特森林/遥感技术/随机森林模型/多元回归分析Key words
Carbon stock/Karst forest/Remote sensing technology/Random forest model/Multiple regression analysis引用本文复制引用
康佳琦,李林,储小雪,赵毅,刘佳润,谭一波..基于遥感的漓江流域喀斯特森林碳储量建模估测[J].热带亚热带植物学报,2025,33(4):417-427,11.基金项目
广西自然科学基金青年项目(2021GXNSFBA196052) （2021GXNSFBA196052）
广西优良用材林资源培育重点实验室课题(23-B-04-02) （23-B-04-02）
桂林兴安漓江源森林生态系统广西野外科学观测研究站科研能力建设项目(桂科22-035-130-02)资助 This work was supported by the Youth Project for Natural Science in Guangxi(Grant No.2021GXNSFBA196052),the Project for Key Laboratory of Superior Timber Trees Resource Cultivation in Guangxi(Grant No.23-B-04-02),and the Project for Science Research Capacity Building of Lijiangyuan Forest Ecosystem Observation and Research Station in Xing'an Guilin of Guangxi(Grant No.GXSTP 22-035-130-02). （桂科22-035-130-02）
