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...