fbc005c9-9168-47af-beb2-0862e8325622 Gregory Giuliani University of Geneva Lecturer +41 (0) 22 3790709 Telephone number of a facsimile machine for the responsible organization or individual 66 Boulevard Carl-Vogt Geneva 1205 Switzerland gregory.giuliani@unige.ch http://www.unige.ch/envirospace 2022-10-03T08:57:41 ISO 19115:2003/19139 1.0 EPSG:4326 Sentinel-2 Analysis Ready Data 2020-03-10T00:00:00 s2_l2a_10m_swiss This dataset is the Sentinel-2 Analysis Ready Data (ARD) - Level 2 (surface reflectance) archive for Switzerland. Detailed description about the Sentinel-2 missions can be found in the CEOS Earth Observation Handbook: Sentinel-2 A http://database.eohandbook.com/database/missionsummary.aspx?missionID=552 and Sentinel-2 B http://database.eohandbook.com/database/missionsummary.aspx?missionID=553. Switzerland is covered by twelve Sentinel-2 scenes (ID: 31TGM, 31TGN, 32TLR, 32TLS, 32TLT, 32TMR, 32TMS, 32TMT, 32TNS, 32TNT, 32TPS, 32TPT). This corresponds to a spatial extent of latitude 45.0 to 47.9N, longitude 5.5 to 11.8E. Data are downloaded as L1C products corresponding to 100x100km2 geometrically corrected Top Of the Atmosphere (TOA) tiles. Atmospheric corrections are applied to generate normalized surface reflectance that correspond to the ARD level (i.e., Level 2A). For that, we use the ESA Sen2Cor algorithm (http://step.esa.int/main/third-party-plugins-2/sen2cor/)38 version 2.5.5 (2.8.0 version is not used as it is not able to process products before 2017). The algorithm follows two steps to pre-process data: first, it executes an image classification to identify and generate masks of clouds, cloud shadows, snow and water. Second, it applies an atmospheric correction model to convert TOA values into surface reflectance. Sen2Cor provides additional outputs on Aerosol Optical Thickness (AOT) and Water Vapour (WV). In the S2 ARD workflow, all bands are pre-processed and ingested except the band 10 that is only used for atmospheric corrections and consequently not relevant for users. It is important to mention that topographic correction is not applied as it creates strong artefacts. Sentinel-2 processed to level 2A with Sen2Cor comes with a scene classification (similar to the pixel_qa band provided by USGS for Landsat data) with 12 classes as described at: https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-2a/algorithm. It helps identifying pixels that are saturated or defective as well as cloud and cloud shadows that may affect the quality of the images. In addition, ESA provides a monthly status of the quality of Sentinel-2 data through Data Quality Reports (DQR). These reports document geometric and radiometric performances against initial sensor specifications together with observed anomalies and issues. DQR are available at: https://sentinels.copernicus.eu/web/sentinel/data-product-quality-reports. Sentinel-2 (S2) is a constellation of two sun-synchronous satellites operated by ESA respectively from 2015 to 2022 (Sentinel-2A) and 2017-2024 (Sentinel-2B). It supports land monitoring related services, including generation of generic land cover maps, risk mapping and fast images for disaster relief, generation of leaf coverage leaf chlorophyll content and leaf water content. Bruno Chatenoux UNEP/GRID-Geneva bruno.chatenoux@unepgrid.ch https://geonetwork.swissdatacube.org/geonetwork/srv/api/records/fbc005c9-9168-47af-beb2-0862e8325622/attachments/Sentinel-2_logo.jpg Swiss Data Cube Earth Observations Sentinel-2 Analysis Ready Data Switzerland 10 environment geoscientificInformation imageryBaseMapsEarthCover 5.95661377423453 10.4934735095497 45.8191539516188 47.8098679329775 2015 2024 OGC NetCDF 1.0 Bruno Chatenoux UNEP/GRID-Geneva bruno.chatenoux@unepgrid.ch https://sdc.unepgrid.ch:8080 WWW:LINK-1.0-http--link Jupyter Notebook http://sdc.unepgrid.ch null SDC Web UI https://doi.org/10.26037/yareta:zeg4u3pa5bcrfbph7mcsehorfm DOI Yareta Repository downloaded from the Copernicus Open Access Hub and pre-processed with Sen2Cor