文献类型：会议论文

英文题名：Forest Stand Mapping with data from Hyperion, ALI and ETM

作者：Tan Bingxiang[1] Li Zengyuan[1] Chen Erxue[1] Pang Yong[1]

第一作者：谭炳香

通信作者：Tan, BX[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resources Informat Tech, WanShouShan Hou, Beijing 100091, Peoples R China

会议论文集：15th National Symposium on Remote Sensing of China - Remote Sensing of the Environment

会议日期：AUG 19-23, 2005

会议地点：CAS, Inst Remote Sensing Applicat, Gulyang, PEOPLES R CHINA

主办单位：CAS, Inst Remote Sensing Applicat

语种：英文

外文关键词：forest; EO-1; Hyperion; ALI; ETM; remote sensing

年份：2006

摘要：The EO-I spacecraft, launched November 21, 2000 into a sun synchronous orbit behind Landsat 7, hosts advanced technology demonstration instruments, whose capabilities are currently being assessed by the user community for future missions. A significant part of the EO-1 program is to perform data comparisons between Hyperion, ALI and Landsat 7 ETM+. In this paper, a comparison of forest classification results from Hyperion, ALI, and ETM+ of Landsat-7 are provided for Wangqing Forest Bureau, Jilin Province, and Northeast of China. The data have been radiometrically corrected and geometrically resampled. Feature selection and statistical transforms are used to reduce the Hyperion feature space from 129 channels to 15 features. Classes chosen for discrimination included Larch, Oak, Birch, Popular, Young tree, mixed forest, Grassland and Shrub. Classification accuracies by sensors for classes in the demonstration area were: Hyperion 88.89%, ALI 85.19%, and ETM+ 77.78%. The results shows: Hyperion classification results were the best, ALI's were much better than ETM+. Therefore, we can consider that hyper spectral remote sensing provides significant advantages and greater accuracies over ETM+ for forest discrimination. The EO-I sensors, Hyperion and ALI, provide data with better discrimination for Northeast forests of China in comparison to Landsat-7 ETM+.