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Improving Sentinel-5P Imagery Usability Through Machine Learning Gap-Filling
Abstract. Satellite-based air quality monitoring, particularly using Sentinel-5P (S5P) TROPOMI observations of NO2 and SO2, provides high-resolution global coverage but is substantially affected by spatio-temporal data gaps. These discontinuities, caused by cloud cover, surface reflectance, viewing geometry constraints...
From Foundation Embeddings to Cropland Maps: Label Efficiency, Temporal Transferability and Independent Human Validation
The results support frozen geospatial embeddings as a low-compute candidate for regional cropland mapping, subject to the limits of a single-state study, a 30 m-derived training reference, and a one-block human validation.