文献类型：会议论文

英文题名：Object-based classification of IKONOS data for endemic Torreya mapping

作者：Wang, Xiaoming[1] Wang, Ke[2] Zhou, Benzhi[1]

第一作者：王小明

通信作者：Wang, XM[1]

机构：[1]Chinese Acad Forestry, Res Inst Subtrop Forestry, Fuyang 311400, Zhejiang, Peoples R China;[2]Zhejiang Univ, Inst Remote Sensing Informat Technol Applica, Hangzhou 310029, Zhejiang, Peoples R China

会议论文集：3rd International Conference on Environmental Science and Information Application Technology (ESIAT)

会议日期：AUG 20-21, 2011

会议地点：Xian, PEOPLES R CHINA

语种：英文

外文关键词：Vegetation mapping; Object-based classification; Texture; IKONOS

年份：2011

摘要：Torreya (T. grandis 'Merrillii') is a rare cash crop tree endemic to Kuaiji mountains of southern China. The present research demonstrated the use of spatial information in object-based classification for improving the identification of Torreya from IKONOS images. Pixel-based and object-based classifications on a combination of spectral and textural features were implemented and their accuracies were compared. The object-based classification proved more accurate than the pixel-based classification. The overall classification accuracy and Kappa coefficients were 75.7% and 0.676 for the pixel-based classification; 81.7% and 0.746 for the object-based classification. The overall results demonstrate that object-based classification of very high resolution satellite images using additional features is a practical tool for vegetation mapping in the study area. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Conference ESIAT2011 Organization Committee.