| 21 Aug 2020
OPERATIONAL PIPELINE FOR A GLOBAL CLOUD-FREE MOSAIC AND CLASSIFICATION OF SENTINEL-2 IMAGES
Keywords: deep learning, optical satellite images, cloud detection, U-net, classification
Abstract. Global Earth observation from satellite images is an active research topic, driven by numerous applications, such as telecommunications, defence, natural hazard monitoring and urban management. The recently launched twin Sentinel-2 satellites acquire 13-band optical data with a 2–5 day revisit time, freely available for any use, and thus very valuable for global Earth observation. In this paper, we present a completely automatic operational chain for a global cloud-free mosaic and classification of Sentinel-2 images. The proposed pipeline enables producing the world 10-m cloud-free mosaic, and a 6-class landcover classification map.