Sentinel-2 Level 1 Products and Image Processing Performances

Abstract

ABSTRACT:In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES) program, the European Space Agency (ESA) is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. While ensuring data continuity of former SPOT and LANDSAT multi-spectral missions, Sentinel-2 will also offer wide improvements such as a unique combination of global coverage with a wide field of view (290km), a high revisit (5 days with two satellites), a high resolution (10m, 20m and 60m) and multi-spectral imagery (13 spectral bands in visible and shortwave infra-red domains). In this context, the Centre National d'Etudes Spatiales (CNES) supports ESA to define the system image products and to prototype the relevant image processing techniques. This paper offers, first, an overview of the Sentinel-2 system and then, introduces the image products delivered by the ground processing: the Level-0 and Level-1A are system products which correspond to respectively raw compressed and uncompressed data (limited to internal calibration purposes), the Level-1B is the first public product: it comprises radiometric corrections (dark signal, pixels response non uniformity, crosstalk, defective pixels, restoration, and binning for 60m bands); and an enhanced physical geometric model appended to the product but not applied, the Level-1C provides ortho-rectified top of atmosphere reflectance with a sub-pixel multi-spectral and multi-date registration; a cloud and land/water mask is associated to the product. Note that the cloud mask also provides an indication about cirrus. The ground sampling distance of Level-1C product will be 10m, 20m or 60m according to the band. The final Level-1C product is tiled following a pre-defined grid of 100x100km², based on UTM/WGS84 reference frame. The stringent image quality requirements are also described, in particular the geo-location accuracy for both absolute (better than 12.5m) and multi-temporal (better than 0.3 pixels) cases.Then, the prototyped image processing techniques (both radiometric and geometric) will be addressed. The radiometric corrections will be first introduced. They consist mainly in dark signal and detector relative sensitivity correction, crosstalk correction and MTF restoration. Then, a special focus will be done on the geometric corrections. In particular the innovative method of automatic enhancement of the geometric physical model will be detailed. This method takes advantage of a Global Reference Image database, perfectly geo-referenced, to correct the physical geometric model of each image taken. The processing is based on an automatic image matching process which provides accurate ground control points between a given band of the image to refine and a reference image, allowing to dynamically calibrate the viewing model. The generation of the Global Reference Image database...

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