Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion

• Published in: ISPRS journal of photogrammetry and remote sensing Vol. 166; pp. 333 - 346
• Main Authors: Meraner, Andrea, Ebel, Patrick, Zhu, Xiao Xiang, Schmitt, Michael
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2020; Elsevier
• Subjects: climate change; cloud cover; Cloud removal; cropland; data collection; Data fusion; Deep learning; image analysis; land use and land cover maps; monitoring; Optical imagery; remote sensing; Residual network; SAR-optical; satellites; Deep learning; Data fusion; Cloud removal; Optical imagery; SAR-optical; Residual network

Optical remote sensing imagery is at the core of many Earth observation activities. The regular, consistent and global-scale nature of the satellite data is exploited in many applications, such as cropland monitoring, climate change assessment, land-cover and land-use classification, and disaster as...