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. The mission is also used to monitor coastal and inland waters and is useful for risk and disaster mapping. 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 (Multi-Spectral Instrument) which acquires optical data products with spatial resolution up to 10 m.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 monotemporal 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 for further processing.The paper will give an overview of the Level-2A product content and up-to-date information about the data quality of the Level-2A products generated with Sen2Cor 2.8 in terms of Cloud Screening and Atmospheric Correction. In addition the paper gives an outlook on the next updates of Sen2Cor and their impact on Level-2A Data Quality.
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. Accurate atmospheric correction of Sentinel-2 data and knowledge of its uncertainties are preconditions for high quality downstream applications. In this work we present the comparison of Sentinel-2 Bottom-of-Atmosphere products with measurements of surface reflectance on ground. Source of reference measurements are both surface reflectance data from RadCalNet and from dedicated field campaigns. The analysis shows, that the uncertainty of SR-retrieval with Sen2Cor is better than about 7% for bright surfaces and about 17% for darker. In addition to this performance evaluation, the data are also applied to compare the use of reference data coming from permanent operating bright RadCalNet sites and from ad-hoc field campaigns at darker sites.
Airborne infrared limb-viewing sensors may be used as surveillance devices in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. Consequently, the knowledge of the radiance small-scale angular fluctuations and their statistical properties is required to assess the sensors' detection capacity. In the stratosphere and in clear-sky conditions, the structured background is mainly due to inertia-gravity-wave and turbulence-induced temperature and density spatial fluctuations. Moreover, in the particular case of water vapor absorption bands, the mass fraction fluctuations play a non negligible role on the radiative field. Thereby, considering as a first approximation the temperature field and the water vapor field as stationary stochastic processes, the radiance autocorrelation function (ACF) can be expressed as a function of the temperature ACF and the water vapor mass fraction ACF. This paper presents the model developed to compute the two-dimensional radiance angular ACF. This model requires the absorption coefficients and their temperature derivatives, which were calculated by a line-by-line code dedicated to water vapor absorption bands. An analytical model was also developed for a simple homogeneous case, in order to validate the average values and the radiance fluctuation variance. The numerical model variance and variance distribution are also compared to SAMM2 outputs, the AFRL radiance structure computation code. The influence of water vapor fluctuations on radiance fluctuations is also discussed.
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