H2020 Copernicus CalVal Solution CCVS

Kurzfassung

The objective of the Copernicus H2020 Cal/Val Solution (CCVS) project is to define a holistic solution for all Copernicus Sentinel missions to overcome current limitations for both current and upcoming Sentinel-missions. This includes improved calibration of currently operational or planned Copernicus Sentinel sensors and the validation of Copernicus core products generated by the payload ground segment. While high-resolution optical missions are out of scope of the project, most of the recommendations coming from the project could be applicable or beneficial to these missions. This presentation will focus on those aspects and highlight possible synergies between Copernicus missions and high-resolution missions. The first aspect concerns R&D on models. Models of natural targets (PICS, Moon, Deep Convective Clouds) need to be further improved in terms of spectral coverage, SI traceability and uncertainty estimates. Validation methodologies using models of complex scenes (e.g. urban or vegetated scenes) with 3D Radiative Transfer should be developed. Progress on atmospheric Radiative Transfer Models is critical to improve uncertainty of surface reflectance measurements. Development of open-source models and cross-comparison activities should be encouraged, and community-agreed guidelines on best practices for modelling should be issued. Validation of surface reflectance is currently limited by the lack of suitable reference measurements (FRM). The CCVS project supports the development of an operational network of automatic hyperspectral radiometers on a set of representative and fully characterized sites (including BRDF and spatial homogeneity). The measurements should be SI traceable and provided with uncertainties. These sites should be regularly compared with a well characterised travelling standard that is controlled by across network body. Such network could be of interest for VHR-missions for the radiometry CalVal activities. Regarding geometry CalVal, in addition to the project support of a public reference grid such as the Sentinel-2 GRI at Level-1C, the project identified a lack of suitable geometric reference for nigh-time thermal infra-red imaging. R&D activities should explore the possible use of reference features such as gas flares or contrasted scenes (water/land interfaces). Finally, the reliability of cloud and cloud shadow masks is an important factor for the quality of optical surface measurements. Therefore, any improvement on the masking algorithms would be an asset to the VHR-missions products. To achieve this objective, it could be useful to develop a public cloud mask reference database and to harmonize validation methodologies.