Sentinel-2 Level-2 processing Sen2Cor status and outlook of 2022

The Sentinel-2 mission is fully operating since June 2017 with a constellation of two polar orbiting satellite units. Both Sentinel-2A and Sentinel-2B are equipped with an optical imaging sensor MSI (MultiSpectral Instrument) which acquires high spatial resolution optical data products. The Sentinel-2 mission is dedicated to land monitoring, emergency management and security. It serves for monitoring of land-cover change and biophysical variables related to agriculture and forestry, monitors coastal and inland waters and is useful for risk and disaster mapping. Accurate atmospheric correction of satellite observations is a precondition for the development and delivery of high quality applications. Therefore the atmospheric correction processor Sen2Cor was developed with the objective of delivering land surface reflectance products. Sen2Cor is designed to process single tile Level-1C products, providing Level-2A surface (Bottom-of-Atmosphere) reflectance product together with Aerosol Optical Thickness (AOT), Water Vapour (WV) estimation maps and a Scene Classification (SCL) map including cloud / cloud shadow classes for further processing. Sen2Cor processor can be downloaded from ESA website as a standalone tool for individual Level-2A processing by the users. It can be run either from command line or as a plugin of the Sentinel-2 Toolbox (SNAPS2TBX). In parallel, ESA started in June 2017 to use Sen2Cor for systematic Level-2A processing of Sentinel-2 acquisitions over Europe. Since March 2018, Level-2A products are generated by the official Sentinel-2 ground segment (PDGS) and are available on the Copernicus Open Access Hub. The objective of this presentation is to provide users with an overview of the Level-2A product contents and up-to-date information about the data quality of the Level-2A products (processing baseline PB.04.00 onwards) generated by Sentinel-2 PDGS since end of January 2022, in terms of Cloud Screening and Atmospheric Correction. In addition, the presentation will give an outlook on the recent updates of Sen2Cor, which improve L2A Data Quality: updated L2A metadata, updated scene classification, updated fall-back method using meteorological information from the Copernicus Atmosphere Monitoring Service, updated Copernicus DEM

Sen2Cor version 2.10: Last evolutions and Focus on the update of Cloud Screening and Scene Classification algorithm

Sen2Cor is a Level-2A processor with the main purpose to correct single-date Sentinel-2 Level 1C products from the effects of the atmosphere in order to deliver a Level-2A surface reflectance product. Side products are Cloud Screening and Scene Classification (SCL), Aerosol Optical Thickness (AOT) and Water Vapour (WV) maps. The Sen2Cor version 2.10 has been developed with the aim to improve the quality of both the surface reflectance products and the Cloud Screening and Scene Classification (SCL) maps in order to facilitate their use in downstream applications like the Sentinel-2 Global Mosaic (S2GM) service. This version is planned to be used operationally within Sentinel-2 Ground Segment and for the Sentinel-2 Collection 1 reprocessing. The Cloud Screening and Scene Classification module is performed prior to the atmospheric correction and provides a Scene Classification map divided into 11 classes. This map does not constitute a land cover classification map in a strict sense. Its main purpose is to be used internally in Sen2Cor’s atmospheric correction module to distinguish between cloudy -, clear - and water pixels. Two quality indicators are also provided: a Cloud - and a Snow confidence map with values ranging from 0 to 100 (%). The presentation provides an overview of the last evolutions of Sen2Cor including the support of new L1C products with processing baseline >= 04.00 and the provision of additional L2A quality indicators. The different steps of the Cloud Screening and Scene Classification algorithm are recalled: cloud/snow -, cirrus -, cloud shadow detection, pixel recovery and post-processing with DEM information. It will also detail the latest updates of version 2.10 that makes use of the parallax properties of the Sentinel-2 MSI instrument to limit the false detection of clouds above urban and bright targets. Finally, SCL validation results with Sen2Cor 2.10 are included in the presentation. The recent improvements as well as the current limitations of the SCL-algorithm are presented. Some advices are given on the configuration choices and on the use of external auxiliary data files

Uncertainty of Sentinel-2 AOT, WV and SR retrieval with Sen2Cor

Sen2Cor is a Level-2A (L2A) processor whose main purpose is to correct mono-temporal Copernicus Sentinel-2 (S2) mission Level-1C (L1C) products from the effects of the atmosphere in order to deliver radiometrically corrected Bottom-of-Atmosphere (BOA) data. Byproducts are Aerosol Optical Thickness (AOT), Water Vapor (WV) and Scene Classification (SCL) maps. Sen2Cor is used for systematic processing of Sentinel-2 L1C data thus generating the S2 L2A products distributed to users by the Copernicus SciHub. In parallel, a Sen2Cor Toolbox can be downloaded from the ESA website for autonomous processing of S2 L1C data by the users. Several important evolutions had been realized from Sen2Cor version 2.8 to 2.10. Version 2.9 runs with Copernicus DEM if correctly formatted. Significant improvements were realized on scene classification module from Sen2Cor 2.8 to 2.10. Whereas atmospheric correction core modules and the AOT estimation based on dense dark vegetation (DDV)-pixels remain unchanged, a new AOT estimation fallback solution was implemented in the recent version. This new fallback solution takes AOT from Copernicus Atmospheric Monitoring Service (CAMS) data in snowy and arid landscapes in case the Sentinel-2 granule does not contain enough DDV-pixel required for AOT estimation. Sen2Cor 2.10 is designed to work with next generation product format which includes this external AOT information in the metadata. Sentinel-2 products processed with Sen2Cor are almost compliant with the Analysis Ready Data (ARD) specifications. Knowledge of uncertainty of products is one major key to foster interoperability both through time and with other datasets. This presentation will provide a status update on the Sentinel-2 product uncertainties. Both AOT and WV retrievals are validated by comparing with reference data provided by AERONET sun photometers at 80 locations distributed over the globe, all continents and climate zones. Spatial average of retrieval from Sentinel-2 over 9x9 km2 region around AERONET station is compared to ±15 min time average of AERONET data around satellite overpass time. Quality of SR retrieval is assessed by comparison with pseudo reference data. These are generated by running Sen2Cor with fixed aerosol optical thickness as input which is set equal to the value provided by the AERONET. The presentation will compare uncertainty of AOT, WV and SR per band for different geographical regions and climate zones. The presentation will also analyze the sensitivity of Sen2Cor processing to parameters which can be configured by the user with running Sen2Cor Toolbox. The difference between processing with rural or maritime aerosol type and between summer or winter atmospheric profile will be discussed

Comparison of DDV-algorithm for AOT estimation in Sen2Cor and use of AOT from CAMS data

The Copernicus Sentinel-2 mission provides data since the launch of the Sentinel-2A unit in 2015. The launch of the Sentinel-2B in 2017 created a constellation of two polar orbiting satellite units. Both Sentinel-2A and Sentinel-2B are equipped with an optical imaging sensor MSI (Multi-Spectral Instrument) which acquires decametric spatial resolution optical data products. The Sentinel-2 mission serves for observation of land-cover change and deriving biophysical variables related to agriculture and forestry, monitors coastal and inland waters and is useful for risk and disaster mapping. Atmospheric correction processor Sen2Cor was developed to remove the effect of the atmosphere from Sentinel-2 data. Sen2Cor is designed for mono-temporal processing of Sentinel-2 L1C data products providing Level-2A Bottom-of-Atmosphere (BOA) surface reflectance product together with Aerosol Optical Thickness (AOT), Integrated Water Vapour (WV) and Scene Classification (SCL) maps. The processor relies on Dense Dark Vegetation (DDV) pixels for estimation of AOT and uses AOT from Copernicus Atmospheric Monitoring Service (CAMS) as fall-back option in case there are not enough DDV-pixels in the image. The data set for validation was split into two subsets so far investigating the performance of the DDValgorithm and the CAMS-fall-back option. CAMS fall-back option performs better than the DDV-algorithm in some cases and worse in others. However, this is no comparison of DDV-algorithm and CAMS fall-back option because it is based on different images in each subset. The presentation will compare both AOT-options of Sen2Cor on the same images. The analysis will start as before reporting results for the two subsets. Then, Sen2Cor will be forced using CAMS data for reprocessing the subset of images with enough DDV-pixels in the image allowing a direct comparison of DDV-algorithm and CAMS data use. The comparison is done with reference data from AERONET on a dataset of more than 1000 Sentinel-2 images distributed around the globe

Time series noise of Copernicus Sentinel-2 operational L2A-Products of year 2022

Copernicus Sentinel-2 is the main European land surface observing mission. It serves for observation of land-cover change and deriving biophysical variables related to agriculture and forestry, monitors coastal and inland waters and is useful for risk and disaster mapping. Data quality of the provided data products is a critical point for all these applications. The Sentinel-2 mission consists of a constellation of two polar orbiting satellite units. Both Sentinel-2A and Sentinel-2B are equipped with an identical optical imaging sensor MSI (Multi-Spectral Instrument) which samples 13 spectral bands: four bands at 10 m in the Visible Near Infrared (VNIR) region, six bands at 20 m and three bands at 60 m spatial resolution in the VNIR to Shortwave Infrared (SWIR) region. Sentinel-2 Level-2A (L2A) data contain Bottom-of-Atmosphere (BOA) surface reflectance products together with Aerosol Optical Thickness (AOT), Integrated Water Vapour (WV) and Scene Classification (SCL) maps. They are generated with Sen2Cor which is the operational atmospheric correction processor that removes the effect of the atmosphere from Top-of-Atmosphere Level-1C data. ESA started the complete reprocessing of the Sentinel-2 data archive named Collection-1 which is tagged with the processing baseline (PB) 5.00. The previous processing baseline PB 4.00 has equivalent evolutions and is very close to the PB 5.00 of Collection-1. Operational L2A products with PB 4.00 were generated from end of January 2022 to beginning of December 2022. In this presentation we propose to study surface reflectance time series smoothness, for several test sites, using L2A products from year 2022. The smoothness of that time series is used as an indicator of data quality of the reprocessed products. Test sites are selected representing different climate zones with different AOT retrieval performance 0.03 ≤ RMSDAOT ≤ 0.20 and different WV retrieval performance 0.12 g/cm2 ≤ RMSDWV ≤ 0.40 g/cm2

Initial Validation of Sentinel-2 Collection-1 L2A-Products

The Copernicus Sentinel-2 mission provides data since the launch of the Sentinle-2A unit in 2015. With the launch of the Sentinel-2B in 2017 it is a constellation of two polar orbiting satellite units. Both Sentinel-2A and Sentinel-2B are equipped with an optical imaging sensor MSI (Multi-Spectral Instrument) which acquires high spatial resolution optical data products. The Sentinel-2 mission serves for observation of land-cover change and deriving biophysical variables related to agriculture and forestry, monitors coastal and inland waters and is useful for risk and disaster mapping. Atmospheric correction processor Sen2Cor was developed to remove the effect of the atmosphere from Sentinel-2 data. Sen2Cor is designed for mono-temporal processing of Sentinel-2 L1C data products providing Level-2A Bottom-of-Atmosphere (BOA) surface reflectance product together with Aerosol Optical Thickness (AOT), Integrated Water Vapour (WV) and Scene Classification (SCL) maps. Since June 2017, ESA uses Sen2Cor for systematic, operational Level-2A processing of Sentinel-2 acquisitions. Products are available on the Copernicus Open Access Hub. However, several evolutions of Sen2Cor and L2A-products since 2017 resulted in a quite inhomogeneous time series. Therefore, ESA started a reprocessing campaign of the complete Sentinel-2 data archive. The resulting Collection-1 of Sentinel data archive provides a real homogeneous time series based on the recent Sen2Cor processor version. The presentation provides initial validation results for AOT, WV and (BOA) surface reflectance retrieval together with quality assessment of cloud screening. Accuracy and uncertainty of AOT and WV retrieval is assessed with reference measurements from AERONET stations. BOA reflectance retrieval can be estimated on a limited number of reference data only from RadCalNet-sites and in-situ campaigns. Reference data for cloud screening are generated by manual labelling of test images

Sentinel-2 Level-2 processing: Regional distribution of Sen2Cor version 2.8 performance for AOT and SR retrieval over Europe

Sen2Cor is the atmospheric correction processor selected by ESA for operational, systematic processing of Copernicus Sentinel-2 mission data. It is used for generating the Level-2A products distributed to users by the Copernicus SciHub. In addition, it can be downloaded from ESA website as standalone tool for individual processing by the users. The main purpose of Sen2Cor is to correct mono-temporal Sentinel-2 (S2) Level-1C (L1C) products from the effects of the atmosphere in order to deliver atmospherically corrected Bottom-of-Atmosphere (BOA) respectively surface reflectance (SR) data. Part of the atmospheric correction process is estimation of aerosol optical thickness and integrated water vapor of the atmosphere. Provided SR data are used in a wide field of downstream applications on land surface related to agriculture, forestry and land-cover change and are also used to monitor coastal and inland water. Downstream applications need information on quality of atmospheric correction products. This presentation will show performance of AOT and WV retrievals estimated by comparing with reference data provided by AERONET sun photometers at different locations distributed over Europe. Spatial average of retrievals from Sentinel-2 over 9x9 km2 region around AERONET station is compared to ±15 min time average of AERONET data around satellite overpass time. Performance of SR retrieval is assessed by comparison with pseudo reference data. These are generated by running Sen2Cor with fixed aerosol optical thickness as input which is set equal to the value provided by the AERONET

Sen2Cor Version 3.0 Processor Applied to Landsat-8 Data: Implementation and Preliminary Results

Sen2Cor (latest version 2.10) is the official ESA Sentinel-2 processor for the generation of the Level-2A Bottom-Of-Atmosphere reflectance products starting from Level-1C Top-Of-Atmosphere reflectance. In this work, we introduce Sen2Cor 3.0, an evolution of Sen2Cor 2.10 able to perform the processing of Landsat-8 Level-1 products in addition to Sentinel-2 Level-1C products. In this study, we test the resulting capability of the Sen2Cor 3.0 algorithms (also updated to work in a Python 3 environment) such as the scene classification and the atmospheric correction, to process Landsat-8 Level-1 input data. This work is part of the Sen2Like framework that aims to support Landsat-8-9 observations and to prepare the basis for future processing of large set of data from other satellites and missions. Testing and measuring the capacity of Sen2Cor 3.0 to adapt to different input and reliably produce the expected results is, thus, crucial. Sentinel-2 and Landsat-8 have seven overlapping spectral bands and their measurements are often complimentary used for studying and monitoring, for example, the status and variability of the Earth’s vegetation and land conditions. However, there are also important differences between these two sensors, such as the spectral-band response, spatial resolution, viewing geometries and calibrations. These differences and quantities are all reflected in their resulting L1 products. A dedicated handling process for those differences is, thus, needed. Moreover, contrary to Sentinel-2, Landsat-8 does not have the water-vapour band that is used by Sen2Cor to perform the atmospheric correction of Sentinel-2 products. Therefore, important information is missing and further implementation is required in order to retrieve the necessary data from external sources to prepare the scene for the Landsat-8 processing. Moreover, new set of Look-Up Tables had to be prepared. In this work, we address the modifications applied to Sen2Cor and the uncertainty due to the Level 1 to Level 2 processing methodology. Further, we present a qualitative comparison between Sen2Cor 3.0 generated Sentinel-2 and Landsat-8 L2 products and Sen2Cor 2.10 generated Sentinel-2 L2A products. Finally, we list foreseen optimizations for future development

Sentinel-2 Level-2 processing: Sen2Cor version 2.10 and L2A processing baseline >=04.00

The Copernicus Sentinel-2 mission is fully operating since June 2017 with a constellation of two polar orbiting satellite units. Both Sentinel-2A and Sentinel-2B are equipped with an optical imaging sensor MSI (Multi-Spectral Instrument) which acquires high spatial resolution optical data products. The Sentinel-2 mission is dedicated to land monitoring, emergency management and security. It serves for monitoring of land-cover change and biophysical variables related to agriculture and forestry, monitors coastal and inland waters and is useful for risk and disaster mapping. Accurate atmospheric correction of satellite observations is a precondition for the development and delivery of high-quality applications. Therefore, the atmospheric correction processor Sen2Cor was developed with the objective of delivering land surface reflectance products. Sen2Cor is designed to process single tile Level-1C products, providing Level-2A surface (Bottom-of-Atmosphere) reflectance product together with Aerosol Optical Thickness (AOT), Water Vapour (WV) estimation maps and a Scene Classification (SCL) map including cloud / cloud shadow classes for further processing. Sen2Cor processor can be downloaded from ESA website as a standalone tool for individual Level-2A processing by the users. It can be run either from command line or as a plugin of the Sentinel-2 Toolbox (SNAP-S2TBX). In parallel, ESA started in June 2017 to use Sen2Cor for systematic Level-2A processing of Sentinel-2 acquisitions over Europe. Since March 2018, Level-2A products are generated by the official Sentinel-2 ground segment (PDGS) and are available on the Copernicus Open Access Hub. The objective of this presentation is to provide users with up-to-date information on the Level-2A products with processing baseline >= PB.04.00 generated by PDGS since 25th of January 2022. The presentation will focus on the product format updates, the updates on Cloud Screening and Atmospheric Correction algorithms as well as on the auxiliary data used in the processing, like the Copernicus DEM90 and the Atmospheric data from Copernicus Atmosphere Monitoring Service (CAMS)