文献类型：期刊文献

英文题名：Object-based analysis for forest inventory

作者：Wang, Lu[1,2] Chen, Erxue[1] Li, Zenyuan[1] Yao, Wanqiang[2] Li, Shiming[1]

第一作者：Wang, Lu

机构：[1] Institute of Forest Resources and Information Technology, Chinese Academy of Forestry, Beijing, China; [2] Xi'An University of Science and Technology, Xi'an, China

年份：2013

卷号：8921

外文期刊名：Proceedings of SPIE - The International Society for Optical Engineering

收录：EI(收录号：20135117111594)

语种：英文

外文关键词：Classification (of information) - Forestry - Image analysis

摘要：As widely used today, high resolution image becomes a useful data source for forest inventory because it can show detailed information of land-cover types which is so helpful in interpreting process. And in the application of high-resolution images, the toughest problem is to find the effective characteristics group to separate each class accurately. In this paper, we tried an object-based method to get the whole forest distribution of the study area. Combining segmentation and decision tree feature selection tool, we tried to find a convenient and effective way to select useful information from such many characteristics brought by - super-pixelsa€- after segmentation. Compared with the traditional pixel-based classification method, we found that object-based method was more appropriate not only for its nearly 10% higher classification accuracy but also providing with more detailed information lying in the image data that help. ? 2013 SPIE.