FROM-GLC Plus

• Main Authors: Le Yu (5600325), Zhenrong Du (11937011), Runmin Dong (11952389), Juepeng Zheng (11952392), Ying Tu (11952394), Xin Chen (11952395), Pengyu Hao (11952399), Bo Zhong (11952402), Jiyao Zhao (10360859), Xiyu Li (11952405), Jianyu Yang (11950241), Haohuan Fu (11950244), Guangwen Yang (11952407), Peng Gong (9932184)
• Format: Dataset
• Language: unknown
• Published: 2022
• Subjects: Land Use and Environmental Planning; remote sensing; land cover mapping; data fusion; sample migration; machine learning; super-resolution; Tundra
• Online Access: https://doi.org/10.6084/m9.figshare.18497600.v2

Building on the earlier Global Land Cover Mapping (Finer Resolution Observation and Monitoring - Global Land Cover, FROM-GLC), we developed the improved Global Land Cover Change Monitoring Platform (FROM-GLC Plus) using methods such as multi-season sample space-time migration, multi-source data time series reconstruction, and machine learning. The FROM-GLC Plus system provides a capacity for producing global land cover change data set from the 1980s with flexibility in spatio–temporal details. The preliminary results of multi-resolution land cover maps in Chicago, U. S. is given here. Values in the files: 10-cropland 20-forest 30-grassland 40-shrubland 50-wetland 60-water 70-tundra 80-impervious 90-bare land 100-ice/snow 120-clouds