Open-Earth-Monitor Global Workshop 2025

This work integrates optical and radar data cubes to detect forest disturbances in tropical regions.

Our method identifies initial degradation and selective logging, often precursors to deforestation, demonstrating its utility in early-warning systems. These results emphasizes the crucial role of integrating optical and radar data to improve the precision and dependability of monitoring systems, essential for sustainable forest management. These findings highlight the value of integrating multi-source data cubes to enhance precision in monitoring forest disturbances, thereby supporting more responsive and reliable environmental management.

This study explores transfer learning in the Brazilian Amazon over the period from 2015 to 2022.