The goal of this dataset is to test deep learning algorithms that predict yearly Above Ground Biomass (AGB) for Finnish forests using satellite imagery. Feature data: Satellite imagery from the European Space Agency and European Commission's joint Sentinel-1 and Sentinel-2 satellite missions, designed to collect a rich array of Earth observation data
Label data: Ground-truth AGB measurements collected using LiDAR (Light Detection and Ranging) calibrated with in-situ measurements. LiDAR is able to generate high-quality AGB maps, but is more time consuming and intensive to collect than satellite imagery.