As part of the Copernicus program of the European Commission, the European Space Agency (ESA) developed and operated the Sentinel-2 constellation (S2A, S2B); and in cooperation with the EUMETSAT, they are operating the Sentinel-3 constellation (S3A, S3B). Both are Earth Observation optical missions, where the MultiSpectral Instruments (MSI) is carried on board Sentinel-2 mission and the Ocean and Land Colour Instrument (OLCI) and Sea Land Surface Temperature Radiometer (SLSTR) are on board Sentinel-3 mission. In the framework of the Copernicus Optical Mission Performance Cluster (OPT-MPC), we use the Database for Imaging Multispectral Instruments and Tools for Radiometric Inter-comparison (DIMITRI) to perform the radiometry intercomparison of the Level-1 products. The aims of this presentation are 1) to assess the quality of the data product; 2) to monitor the temporal evolution of the radiometry of the instruments MSI, OLCI and SLSTR for both unites A and B.The results of the intercomparison show a good stability of the sensors, although SLSTR-A & B show slight positive trend. MSI and SLST pairs A & B show good agreement better than 1% while OLCI constellation displays slight discrepancy up to 2-3%. While MSI-A, MSI-B, OLCI-B gain coefficients are within the missions’ requirements, OLCI-A, SLSTR-A and SLSTR-B ones are slightly higher of the mission requirements.

The Copernicus Sentinel-2 Global Reference Image (GRI) was originally designed with the main goal of being used by the Ground Segment Level-1 processor to geometrically refine the Sentinel-2 data. The usage of the GRI has enabled a real improvement of the Sentinel-2 data geometric performance. Indeed, both absolute geolocation and relative (multi-temporal) performances have significantly improved and meet the requirements.It is expected that the use of the GRI could be then beneficial to other missions than Sentinel-2. In this framework and driven by user’s needs, ESA decided to freely give access to the scientific community to the entire GRI. Moreover, in order to facilitate the use of the GRI, a set of Level-1C images and a database of Ground Control Points (Level-1B and Level-1C geometries) have been derived from the Level-1B Sentinel-2 GRI. This paper recalls the characteristics of this Calibration/Validation GRI databases as well as the validations performed.

The Copernicus Sentinel-2 satellite mission, with its Sentinel-2A and Sentinel-2B units, offers since several years now a massive quantitative and qualitative resource for the Earth Observation community. Since the launch of Sentinel-2A in 2015, and Sentinel-2B in 2017, many lessons have been learnt leading to continuous improvements of the radiometric and the geometric performances. However, the current archive is composed of heterogenous processing baselines with inconsistent product formats and uneven data quality, which limits its use for multi-temporal monitoring applications.To overcome this limitation, the Copernicus program has undertaken a complete reprocessing with the latest processing baseline (05.00). It concerns the L1C (Top-Of-Atmosphere reflectance) and L2A (Surface Reflectance) products. This paper recalls the features of Collection-1 products and gives an overview of the first validation results.

The amount of remote sensing data available from different satellite platforms is increasing freely and openly every day. Thus, raising multiple issues which require innovative approaches to organize, manage, and analyze remote-sensing imagery. Discrete Global Grid Systems (DGGS) currently under study by the OGC DGGS SWG, can in principle act as a unified framework for EO data integration, multisource data fusion and cloud computing on a global scale. This study assesses different DGGS candidates: H3, rHEALpix, ISEA7H, ISEA4T/D, etc., analyzing their main features with the perspective of potentially using them for Copernicus Sentinel-2 mission. We then discuss the first outcomes for the different use cases considered and their applicability regarding the benefits and limitations of the DGGS, with a view to setting up a dedicated demonstrator.

The domain of high-resolution and very high-resolution optical sensors and Synthetic Aperture Radars (SAR) has dramatically increased. Dependable satellites providing accurate and reliable measurements are key to essential urgent activities such as climate change monitoring. As Earth Observation (EO) system architect in Europe, the European Space Agency (ESA) needs to assess the quality and the suitability of the EO data provided by its own satellites and to promote awareness about the importance of assessing EO data quality provided by other missions, e.g. in the commercial and New Space sector. Also, this would allow establishing a dialog with the EO data mission providers in order to improve the overall coherence of the EO system and data interoperability. Furthermore, some of these missions are potential candidates to become ESA Third Party Missions (TPM), pending ESA selection. Calibration/Validation (Cal/Val) activities are fundamental to assess the quality of EO satellite data, requiring dedicated measurements taken from established reference Cal/Val sites and networks. However, Cal/Val sites are often customized to the operator's needs, with little to no flexibility. Therefore, ESA is currently willing to explore the new idea of an open and pioneering reference site, named as Cal/Val Park. The concept is currently under investigation and is meant to be a multi-Agency cooperation.

The Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) will provide high-quality, global, operational hyperspectral observations in support of European Union and related policies for the management of natural resources, assets and benefits. In this contribution, the main outcomes of the activities carried out in Phase A/B1 and B2, as well as the planned activities for Phase C/D/E will be presented, covering the scientific support studies, the technical developments and the user community preparatory activities. The ongoing international collaboration towards increasing synergies of current and future Imaging Spectroscopy missions in space will be reported as well.

This work was conceived to analyze the impact of the different instances of the Copernicus DEM (CopDEM) dataset (named: EEA-10, GLO-30, GLO-90) on the orthorectification of Very High Resolution (VHR) optical data (spatial resolution: 2–4 m). Indeed, the CopDEM instances are characterized by different pixel sizes/spatial coverages/licenses (EEA-10: 10&12 m/European/restricted; GLO-30: 30 m/global/public; GLO-90: 90 m/global/public). Findings showed that all the CopDEM instances provided valuable topographic information that allows reaching similar values of geolocation accuracy. The latter is only slightly influenced by the different pixel sizes of the data. Moreover, this research provided valuable insights related to the existing relationships between the geolocation accuracy and: i) the spatial resolution of the VHR input products; ii) the orography and land cover of the target areas. The analysis also highlighted the importance of the GLO-30 instance for orthorectification purposes, as it is freely and globally available.

The recent surge in interest towards hyperspectral imagery has the potential to unlock a new range of applications for the scientific community. However, compared to traditional multi-spectral images, the workload required to process such high-dimensional data is dramatically increased, to the point that new and more flexible strategies must be developed in order to properly monitor the quality of this type of products. In the particular case of sharpness assessment, traditional procedures based on the edge method tend to be extremely time-consuming due to their reliance on visual analysis performed by human operators, and would make proper processing of all bands a daunting task to perform on a large scale. In this paper we propose a flexible and fully automatic approach to edge method-based sharpness assessment that can be applied inde-pendently from the number of spectral bands. We then present the results of the application of the methodology on the visible and near-infrared and shortwave infrared spectral cubes of a selection of PRISMA L2D images, which confirm the relia-bility of the methodology and suggest further improvements.

In the recent years, the Earth observation (EO) capacity from space has grown with the multiplication of both institutional and commercial missions; in particular the domain of high-resolution optical sensors and SAR (Synthetic Aperture Radar) has dramatically increased. The “NewSpace players” are considered in full in the evolution of the EO international strategy. In this context, ESA and NASA put in place several activities that aim at assessing the data coming from these new missions, like the ESA’ s Earthnet Data Assessment Pilot (EDAP) project and the NASA's Commercial Smallsat Data Acquisition (CSDA) Program. Given the initial success of both of these activities and the multiplication of new missions in the context of the NewSpace, ESA and NASA are proposing to extend these activities with a coordinated approach and the definition of joint guidelines for data quality assessment.

The Sentinel-2 constellation consists on two unites MSI-A & MSI-B, which are an Earth Observation optical mission developed and operated by the European Space Agency (ESA) in the framework of the Copernicus programme of the European Commission. The Sentinel-2 Mission Performance Centre (MPC) is responsible of the calibration, validation, and image quality of the user product. The inter-unit consistency of the radiometry measurements is critical for the mission as more sentinel-2 platforms are planned in the future. In order to assess the validity and temporal stability of the radiometry measurements, two independent vicarious calibration (Desert PICS and Angular-Matchups) methods for EO optical sensors have been applied over land targets. We use DIMITRI (Database for Imaging Multispectral Instruments and Tools for Radiometric Intercomparison) toolbox. The results of the validation show an excellent image quality and stable radiometric performance, which meets the mission requirements target. Nonetheless systematic radiometric biases of 1.1 % across the VNIR spectrum are found with high confidence.

The more high-quality Earth Observation (EO) data are available to users, the more their potential applications increase in number. This is boosting the request for EO data already processed to a minimum set of requirements and needing limited pre-processing steps in order to be used, also when distributed by different EO data providers. The Analysis Ready Data (ARD) concept has been conceived, and a large effort is being made at international levels in order to converge towards a common definition. In this context, the Committee on Earth Observation Satellites (CEOS), with its member Agencies and institution, has worked to define the CEOS ARD for Land (CARD4L) specifications. The Copernicus Sentinel-2 Level-2A product has undergone a self-assessment process performed by the European Space Agency (ESA) aimed at preliminary assessing its compliance status with respect to the CARD4L specifications for optical surface reflectance.

The Sentinel-2 mission is a key element of the Copernicus Earth monitoring program of the European Union. The mission is currently composed of two satellites and provides a continuous observation of land and coastal areas at high spatial resolution and with a revisit time of 5 days at the equator. The geometric uncertainty of the Sentinel-2 product is a critical contributor to the performance of the mission. We present the approach used to calibrate the geometric performance of Sentinel-2 data and latest activities, especially related to the co-registration with the Global Reference Image (GRI). Generation of the GRI, coregistration algorithm, called geometric refinement, and preliminary results are presented.

Presented is a new quality assurance (QA) framework for Earth Observation missions that has been developed as a joint initiative between ESA and NASA. It aims ensure the rigorous assessment of all aspects of relevant aspects of mission quality, verifying claimed mission performance and, where applicable, reviewing the extent to which the mission follows community best practice in a manner that is “fit for purpose”. The QA framework has potential for more general use in both institutional and commercial Earth Observation – helping mission providers to understand the information their users' needs and empowering users to make informed decisions about which data is fit for their purpose.

Reliable cloud screening remains a critical issue for the analysis of optical imagery. In this work we present the recent evolutions of the Cloud Screening and Scene Classification module of Sen2Cor processor for the Copernicus Sentinel-2 mission. In addition to a Level-2A surface reflectance product, Sen2Cor provides a Scene Classification (SCL) map divided into 11 classes. The information provided by this map is of great interest for automated processing chains. It can be used to mask out clouds, cloud shadow, water, snow/ice from the Sentinel-2 imagery, so that downstream processing can be performed on clear land pixels, suitable for time-series analysis and quantitative remote sensing. The performance and limitations of the current algorithm are recalled. The updates aimed at improving the overall accuracy of the cloud screening are described (efficient topographic shadows computation, mitigation of false snow detection in clouds and mitigation of false clouds detection on bright targets). Preliminary results based on a Sen2Cor prototype are discussed.

There are growing and evolving expectations from the Earth Observation (EO) Community for merging an increasing number of input data streams recorded with the various space based Multi-Spectral (MS) High Resolution (HR) EO mission instruments. The various agencies and industries are now delivering Analysis Ready Data (ARD) aiming at stacking together multi source data. One critical objective of ARD is to enable the monitoring of rapid and subtle changes. This category of applications sets some strong requirements regarding the quality of the surface reflectance harmonization in the time series. In the context of Sentinel-2 / Landsat 8, this paper proposes a comprehensive analysis of the Sen2Like processing. It shows that it is possible to increase significantly the geometric coregistration accuracy and to ensure an appropriate cross calibration. However, some issues persist and are due to directional effects. These are partially corrected with the current approach but remain a major source of noise in time series.

The metrics traditionally used for assessing the sharpness level of optical imagery acquired by spaceborne sensors (e.g., relative edge response, point spread function, full width at half maximum of the line spread function, modulation transfer function) are usually measured before launch using a set of standard simulated inputs. However, vibrations occurring during launch and satellite deployment, as well as sensor degradation through time, may alter the nominal characteristics significantly. Therefore, post-launch assessment analyses are necessary for monitoring data quality. To this end, on-orbit measurement techniques for sharpness assessment - e.g., the edge method (EM) - were developed. Selection of suitable targets to be used for such techniques is a crucial step for carrying out the assessment successfully. The objective of this paper is to describe an automatic method for identification of suitable edges to be used for on-orbit sharpness assessment via the EM by taking into account the widespread presence of natural targets - like agricultural fields - on Earth. The presented approach is expected to ease the continuous monitoring of the sharpness level of optical data acquired by spaceborne sensors.

Sen2Cor is a Level-2A processor designed to correct Sentinel-2 Level-1C products from the effects of the atmosphere in order to deliver a Level-2A surface reflectance product. ESA has been using Sen2Cor for systematic Level-2A processing of Sentinel-2 acquisitions over Europe since June 2017. It has since then been successfully integrated into Sentinel-2 ground segment (PDGS) with a global production over the World started in December 2018. In this manuscript, the Level-2A product and algorithm are presented. The performance of this operational Level-2A product is described in terms of cloud screening accuracy and atmospheric correction accuracy. Finally, the on-going parallel developments aimed at improving the product quality at global scale in terms of cloud screening and atmospheric correction are discussed.

Sen2Like is a processor designed to produce harmonized Level 2 surface reflectance dataset considering as reference Sentinel-2 data. Sen2Like fits with the on-going and growing expectations of the Earth Observation (EO) Community for the merging of an increasing number of input data streams from the various Multi-Spectral (MS) High Resolution (HR) EO mission instruments. The harmonization is an essential processing stage in order to fully exploit all the potential of physical data in the context of land use /land change classification/detection. However, because harmonization addresses several issues in the field of atmospheric/geometric/directional effects/spectral difference corrections, there is not a standard way to achieve this objective. To initiate this project, the Landsat 8 (LS8) mission has been considered as the most appropriate. The Sen2Like processor is now delivering S2/LS8 Analysis Ready Data (ARD) on S2 tiling system at a map resolution of 30 m and 10 m. After a description of the algorithms involved in Sen2Like, this paper discusses testing and validation results.

The present paper reports on some insights in the use of Synthetic Aperture Radars (SAR) for bathymetric data retrieval by exploiting variation in swell wave parameters approaching the shoreline. Since SAR signals are unable to penetrate sea surface and to reach seabed, echoed signals from sea surface are used to investigate underwater bathymetry in coastal area. A suitable data processing methodology is proposed to properly detect swell shoaling and refraction phenomena, and to accurately measure swell parameters. The described methodology is tested by using ALOS L-band SAR images over the Gulf of Naples, Italy. A Digital Elevation Model (DEM) of the investigated area is thus obtained. Results are consistent with the values reported in the Official Nautical Chart provided by the Italian Navy Hydrographic Institute.