Open access
Aug 2026
Improving Sentinel-5P Imagery Usability Through Machine Learning Gap-Filling
This study investigates missing data patterns and develops a robust gap-filling framework for the Po Valley (Northern Italy) over 2019–2023, a region characterized by complex basin topography and frequent winter inversions that exacerbate both pollution accumulation and data loss.
Zhanbing Wu, V. Yordanov, M. Brovelli
· The International Archives o... · 0 citations