BigEarthNet is a large-scale benchmark dataset for multi-label classification, derived from Sentinel-1 (radar) and Sentinel-2 (optical) satellite imagery.
We have pre-processed the dataset by upsampling all sentinel-2 channels to 120x120 pixels and concatenated them together. Please see Torchgeo/bigearthnet for more information about pre-processing. In addition, we map the original 43 land cover classes to 19 broader categories using a predefined conversion scheme.… See the full description on the dataset page:
https://huggingface.co/datasets/GFM-Bench/BigEarthNet.
