UNIVERSITAT POLITÈCNICA DE VALÈNCIA (ES)
Living Planet Fellowship research project carried out by Javier Gorroño.
In the last decade, some missions started to offer operational Level-1 (L1) uncertainty estimates for top-of-atmosphere (TOA) radiance/reflectance factor.
Among them, the Sentinel-2 (S2) mission delivers uncertainty products associated to the L1C products using the Radiometric Uncertainty Tool (RUT). The delivery of uncertainty products represents an important milestone that requires consecutive efforts so that further processing levels can also offer these uncertainty estimates.
Consequently, the following phase of study involves the development of uncertainty estimates associated to the S2 L2A products (i.e. surface reflectance). The uncertainty analysis involves the propagation of the L1C TOA reflectance factor through the atmosphere as well as the uncertainty over the atmospheric correction itself.
The study focuses on a mathematical expression of the atmospheric correction of the operational S2 L2A products using the Sen2Cor processor. From this mathematical expression, an analytical expression of the uncertainty can be defined consisting of: a Jacobian of sensitivity coefficients, a correlation matrix and an uncertainty contribution matrix. In order to derive robust uncertainty estimates, the analytical expression of the uncertainty will be validated against a Monte-Carlo approach.
Special attention will be given to the auxiliary retrievals such as Aerosol Optical Thickness (AOT) and Water Vapour (WV) in Sen2Cor processor. In parallel to the uncertainty analysis, its software implementation will be developed to improve the current RUT tool in order to deliver both S2 L1C and L2A uncertainty estimates. The implementation will explore memory/processing time optimisation approaches such as the integration of the RUT as part of Sen2Cor processor.
Among other applications, the delivery of S2 L2A operational uncertainty products can be helpful to provide better quality metrics for end applications such as agricultural monitoring, a better definition of prior conditions in retrieval processes or the support of Earth Observation (EO) products conformance tests.