Sample Earth: Machine-Learning–Ready Land-Cover Reference Dataset - Vantalon, Thibaud; Luong, Phuong Thi; Perez Escobar, Jorge Andres; Tello Dagua, Jhon Jairo; Phan, Trong Van; Nguyen, Hang; Hong Nguyen; Hoa Nguyen; Reymondin, Louis (2025)
This dataset is part of the Sample Earth initiative, a global effort to build open, high-quality reference data for improving the accuracy and inclusiveness of land-cover maps. It contains GPS-located land-cover samples that can be used to train and validate AI models that generate detailed, accurate maps, with a focus on coffee and cocoa production systems.