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Identification and analysis of forest loss drivers in Africa based on multisource time-series remote sensing products
- “Nearly 86.73% of forest damage in Africa is caused by human factors, and this proportion continues to rise. The research team has constructed a forest damage driving factor classification framework based on decision tree rules, providing solutions for forest conservation policy formulation.”
- Vol. 29, Issue 9, Pages: 2714-2727(2025)
DOI:10.11834/jrs.20254590
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LIU Wendi 中国科学院空天信息创新研究院 数字地球重点实验室;可持续发展大数据国际研究中心;中国科学院大学
LIU Liangyun 中国科学院空天信息创新研究院 数字地球重点实验室;可持续发展大数据国际研究中心;中国科学院大学
CHEN Rui 西南交通大学 地球科学与工程学院
XIE Jiangliu 西南交通大学 地球科学与工程学院
YANG Yajie 西南交通大学 地球科学与工程学院
MA Dujuan 西南交通大学 地球科学与工程学院
ZHANG Guodong 西南交通大学 地球科学与工程学院
WANG Meilian 西南交通大学 地球科学与工程学院
Related Institution
Faculty of Geosciences and Engineering, Southwest Jiaotong University
Advanced Interdisciplinary Institute of Satellite Applications/State Key Laboratory of Earth Surface Process and Disaster Risk Reduction, Beijing Normal University
Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment
Key Laboratory of Satellite Remote Sensing,Ministry of Ecology and Environment
State Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences


