SENTINEL-2 SURFACE REFLECTANCE PRODUCTS GENERATED BY CNES AND DLR: METHODS, VALIDATION AND APPLICATIONS
- 1Centre d’Etudes Spatiales de la Biosphere (CESBIO) UMR 5126 (CNES/CNRS/INRAE/IRD/Université Toulouse III), 18 avenue Edouard Belin, 31401 Toulouse Cedex 9, France
- 2Centre National d’Etudes Spatiales (CNES), 18 avenue Edouard Belin, 31401 Toulouse Cedex 9, France
- 3German Aerospace Center (DLR), Earth Observation Center, Muenchener Strasse 20, 82234 Wessling-Oberpfaffenhofen, Germany
- 4SERCO SpA c/o European Space Agency (ESA), European Space Research Institute (ESRIN), Largo Galileo Galilei, Frascati, Italia
Keywords: Sentinel-2, surface reflectance, cloud detection, atmospheric correction, monthly cloud free syntheses
Abstract. To allow for a robust and automatic exploitation of Sentinel-2 data, Analysis Ready Data (ARD) products are requested by most users. The processors of ARD products take care of the common burdens necessary for most applications, that include precise orthorectification, cloud detection and atmospheric correction steps, as well as the generation of periodic syntheses of cloud free surface reflectances. The French Theia land data center, and the German Earth Observation Center (EOC) started delivering Sentinel-2 surface reflectance products to users in 2016 in France and 2019 in Germany respectively. Both centers produce and distribute these data sets in near real time, over large regions requested by French users such as Western Europe, Maghreb, Sahel, Madagascar… Theia’s and EOC products include an instantaneous surface reflectance product (Level-2A), and a monthly cloud free synthesis of surface reflectance (Level-3A). This article shortly describes the methods used to generate the Level-2A products with the MAJA processor, and the Level-3A products with theWASP processor. The MAJA processor is based on multi-temporal methods, that use the slow variation of surface reflectance to detect clouds and estimate aerosol depth, while WASP, thanks to the quality of MAJA cloud mask, calculates a weighted average of all the cloud free observations over 45 days, every month. The article also provides validation results for Level-2A and Level-3A products, resulting from comparison with in-situ data and with other methods. A last section gives first insights from the monitoring of user uptake of the distributed products.