文献类型：会议论文

英文题名：FOREST CANOPY CLOSURE ESTIMATION IN GREATER KHINGAN FOREST BASED ON GF-2 DATA

作者：Sun, Shanshan[1] Li, Zengyuan[1] Tian, Xin[1] Gao, Zhihai[1] Wang, Chongyang[1] Gu, Chengyan[2]

第一作者：Sun, Shanshan

通信作者：Li, ZY[1];Tian, X[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Forestry Planning & Design Acad Forest Prod Ind, 130 Chaoyangmennei St, Beijing 100010, Peoples R China

会议论文集：IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 28-AUG 02, 2019

会议地点：Yokohama, JAPAN

语种：英文

外文关键词：Forest canopy closure (FCC); support vector machine (SVM); Chinese high-resolution satellite-2 (GF-2)

年份：2019

摘要：Forest canopy closure (FCC) is an important factor to assess the quality of forest resources, and to understand the characteristics of forest change, which supports forest ecosystem management. The Chinese high-resolution satellite-2 (Gaofen-2, GF-2) image covering the Genhe Forest Reserve located at the Great Khingan of Inner Mongolia was firstly segmented by object-oriented technology and then the local FCC was estimated by the support vector machine (SVM) based on the GF-2's spectral, normalized vegetation index (NDVI), texture and other auxiliary information. The FCC estimates from the airborne LiDAR point cloud data with high density were used for the cross-validation. The result showed that the coefficient of determination (R-2) between LiDAR and GF-2 results was up to 0.65 and the root mean square error (RMSE) is 0.12. It indicated that it is feasible to estimate FCC by using the GF-2 images based on the object-oriented classification method.