SSL4EO-S12: A Large-scale Multimodal Multitemporal Dataset for Self-supervised Learning in Earth Observation (8-bit)

The SSL4EO-S12 dataset is a large-scale dataset for unsupervised pre-training in Earth observation. The dataset consists of unlabeled patch triplets (Sentinel-1 dual-pol SAR, Sentinel-2 top-of-atmosphere multispectral, Sentinel-2 surface reflectance multispectral) from 251079 locations across the globe. Each patch covers an area of 2640mx2640m and includes four seasonal time stamps. The compressed dataset is provided in normalized 8-bit GeoTiff format, with each band being one single file. Details see <a href=" https://github.com/zhu-xlab/SSL4EO-S12" target="_blank"> https://github.com/zhu-xlab/SSL4EO-S12</a>