European Journal of Remote Sensing · 2018 · 20 citations · 23 references
Natural SciencesEarth SciencesAtmospheric ScienceRemote SensingUncertainty QuantificationAtmospheric Sounding From SatellitesReflectance ModelingSatellite Data ValidationSatellite InstrumentationSatellite SensorsMonte Carlo IntegrationRadiometric ValidationReflectanceRemote Sensing UncertaintyRetrieval Uncertainty EstimationSatellite Retrievals Of Surface RadiationTemporal CorrelationTop-of-atmosphere Reflectance
As part of the Sentinel-2 mission, a Radiometric Uncertainty Tool (RUT) has been recently released to the community. This tool estimates the Sentinel-2 radiometric uncertainty associated with each pixel in the top-of-atmosphere (TOA) reflectance factor images provided by the European Space Agency (ESA). The use of such information enables users to assess the “fitness for purpose” of the data to their specific application. The work described here summarises the efforts and results of integrating the RUT for radiometric validation activities \nfor the Sentinel-2 mission. Starting from the results provided by the RUT, the focus will be on providing a methodology to calculate the uncertainty associated with the mean TOA reflectance factor in a Region of Interest (ROI). Two different methods – one simple method directly using the RUT and a more rigorous one based on Monte Carlo method (MCM) propagation – are proposed and compared. These two methods focus on the effect of the spectral, spatial and temporal correlation of the errors in different ROI pixels and the impact of correlation on the uncertainty associated with the mean TOA reflectance factor. The study has also considered the impact of uncertainty contributions not included in the first version of the RUT.
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