SSL4EO-S12: A Large-scale Multimodal Multitemporal Dataset for Self-supervised Learning in Earth Observation
收藏DataCite Commons2022-06-14 更新2024-07-13 收录
下载链接：
https://mediatum.ub.tum.de/1660427
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资源简介：
The SSL4EO-S12 dataset is a large-scale dataset for unsupervised/self-supervised 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 covering 2640mx2640m and including four seasonal time stamps. The raw dataset is provided in GeoTiff format, with each band being one single file.
提供机构：
Technical University of Munich
创建时间：
2022-06-14
