MTSCFNet: a novel framework for improving tree species classification in a subtropical forest using RGB, LiDAR-derived, and GF-2 data
Year: 2025
Type: article
Language: en
Topic: Remote Sensing and LiDAR Applications
Authors and affiliations:
raw_author_name: Linlong Wang
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
Research Institute of Forest Policy and Information, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
Research Institute of Forest Policy and Information, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
raw_author_name: Huaiqing Zhang
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
raw_author_name: Rurao Fu
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
raw_author_name: Kexin Lei
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
raw_author_name: Yang Liu
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
raw_author_name: Tingdong Yang
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
raw_author_name: Jing Zhang
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China
raw_author_name: Xiaoning Ge
raw_affiliation_strings: Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People’s Republic of China
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China
National Forestry and Grassland Science Data Center (NFGSDC), Beijing, 100091, People's Republic of China