The SEN12TS dataset contains Sentinel-1, Sentinel-2, and labeled land cover image triplets over six agro-ecologically diverse areas of interest: California, Iowa, Catalonia, Ethiopia, Uganda, and Sumatra. Using the Descartes Labs geospatial analytics platform, 246,400 triplets are produced at 10m resolution over 31,398 256-by-256-pixel unique spatial tiles for a total size of 1.69 TB. The image triplets include radiometric terrain corrected synthetic aperture radar (SAR) backscatter measurements; interferometric synthetic aperture radar (InSAR) coherence and phase layers; local incidence angle and ground slope values; multispectral optical imagery; and decameter-resolution land cover data. Moreover, sensed imagery is available in timeseries: Within an image triplet, radar-derived imagery is collected at four timesteps 12 days apart. For the same spatial extent, up to 16 image triplets are available across the calendar year of 2020.
The SEN12TS documentation demonstrates two initial use cases for the dataset. The first transforms radar imagery into enhanced vegetation indices by means of a generative adversarial network, and the second tests combinations of input imagery for cropland classification.
Conlon, T. & Rustowicz, R. (2022), SEN12TS, Version 1.0, Radiant MLHub. [Date Accessed] https://doi.org/10.34911/rdnt.9qh1mb