集成Landsat和GOSAT卫星数据的森林碳储量估测研究  

Research on Estimation of Forest Carbon Stock by Integrating Landsat and GOSAT Satellite Data

作　　者：王飞平 张加龙 曹军 杨正道 肖庆琳 杨坤 殷唐燕 程滔[3] Wang Feiping;Zhang Jialong;Cao Jun;Yang Zhengdao;Xiao Qinglin;Yang Kun;Yin Tangyan;Cheng Tao(College of Forestry,Southwest Forestry University,Kunming Yunnan 650233,China;Guangxi State-owned Gaofeng Forest Farm,Nanning Guangxi 530001,China;Investigation and Monitoring Department,National Geomatics Center of China,Beijing 100830,China)

机构地区：[1]西南林业大学林学院,云南昆明650233 [2]广西壮族自治区国有高峰林场,广西南宁530001 [3]国家基础地理信息中心调查监测部,北京100830

出　　处：《西南林业大学学报(自然科学)》2025年第2期151-158,共8页Journal of Southwest Forestry University:Natural Sciences

基　　金：云南省教育厅科学研究基金项目(2023Y0740)资助;2020年云南省高层次人才培养支持计划“青年拔尖人才”专项(YNWR–QNBJ–2020–164)资助;国家自然科学基金项目(32260390,31860207)资助。

摘　　要：以云南省普洱市森林为研究对象,用GOSAT卫星B2、B3、B4波段通道反演其森林碳浓度,与LandsatOLI多光谱影像和DEM上提取和筛选出的森林碳储量强相关因子,构建GEOS–Chem模型,进行碳通量的反演,再通过碳通量与碳储量之间的换算,实现森林碳储量的估测。结果表明:森林碳储量相关因子分别为DEM和Landsat数据中的Elevation、 NDVI、R9Mean和GOSAT反演出的碳浓度。森林碳储量最优估测模型为GEOS–Chem^(2),其R^(2)为0.978,P为94.89%,相比单独使用GOSAT数据构建的模型GEOS–Chem1(R^(2)为0.847,P为85.32%),R^(2)和P分别提高了0.131和9.57%。用GEOS–Chem^(2)模型估测后的普洱市森林碳储量为4.253×10^(7) t,平均碳储量为19.356 t/hm^(2),总体估测误差为4.69%。综合Landsat和GOSAT卫星数据构建GEOS–Chem模型,能有效降低普洱市森林碳储量的估测误差,研究结果可为高精度森林碳储量遥感估测方法的探索提供参考。Using the forests in Pu'er City,Yunnan Province as the research subject,the forest carbon concentration was inversely inferred using the GOSAT satellite's B2,B3,and B4 spectral channels.Highly correlated factors for forest carbon stock were extracted and selected from Landsat OLI multispectral images and DEM,and a GEOS-Chem model was constructed.Carbon flux was then inversely inferred,and through the conversion between carbon flux and carbon stock,the estimation of forest carbon stock was achieved.The results showed that the highly correlated factors for forest carbon stock were the Elevation,NDVI,R9Mean from the Landsat data,and the carbon concentration inverted by GOSAT.The optimal model for estimating forest carbon stock was GEOS-Chem2, with an R^(2) of 0.978 and P of 94.89%. Compared to the model GEOS-Chem1 constructed solely using GOSAT data(R^(2) of 0.847, P of 85.32%), the R^(2) and P were increased by 0.131 and 9.57% respectively. The estimated forest carbon stock in Pu'er City using the GEOS-Chem2 model was 4.253 × 10^(7) t, with an average car-bon stock of 19.356 t/hm2, and an overall estimation error of 4.69%. By integrating Landsat and GOSAT satellite data to construct the GEOS-Chem model, the estimation error of forest carbon stock in Pu'er City can be effect-ively reduced. The research results can provide reference for the exploration of high-precision remote sensing es-timation methods for forest carbon stock.

关 键 词：森林 碳储量 碳卫星 碳通量 GEOS–Chem GOSAT 

分 类 号：S758.4[农业科学—森林经理学]