文献类型：会议论文

英文题名：Forest land type precise classification based on SPOT5 and GF-1 images

作者：Ren, Chong[1] Ju, Hongbo[1] Zhang, Huaiqing[1] Huang, Jianwen[1]

第一作者：Ren, Chong

通信作者：Ju, Hongbo

机构：[1] Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, China

会议论文集：2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings

会议日期：July 10, 2016 - July 15, 2016

会议地点：Beijing, China

语种：英文

外文关键词：Forest Land Type; GF-1 Image; Hierarchical Information Extraction; Multi-Source Data; Multiple Classifier Combination; Precise Classification

年份：2016

摘要：The objective of this paper is to develop a hierarchical classification scheme and propose forest land type precise classification method based on SPOT5, GF-1 images, and other multi-source data, focusing on fine classification of forest land using high resolution remote sensing image in complex mountainous terrain conditions. The experiments were carried out by multi-source data integration, multiple features analysis and multiple classifier combination. The proposed method in this paper have advantages in fine identification of forest land types with high accuracy and high reliability, and the detail degree of fine identification reaches dominant tree species, which could fully meet the needs of forestry applications such as forest resources investigation, forest land change monitoring and thematic map digital update. ? 2016 IEEE.