Providing uncertainty estimates of the Sentinel-2 top-of-atmosphere measurements for radiometric validation activities

Abstract

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 for 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 methodsone simple method directly using the RUT and a more rigorous one based on Monte Carlo method (MCM) propagationare 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.

Comparison of the Sentinel-3A and B SLSTR Tandem Phase Data Using Metrological Principles

“…Generally, the outcomes of such comparisons are to compute inter-sensor differences or "biases" in given conditions, but, without uncertainty information, it is difficult to form any definitive quantitative conclusion whether these observed differences indicate the sensors are achieving their specified performance. Efforts are therefore on-going to develop the techniques to facilitate the evaluation and dissemination of satellite sensor uncertainty information [5], with some missions now able to provide this (e.g., Sentinel-2 [6,7]). Sensor uncertainty information is also available for both SLSTR L1 and L2 SST products [3,8].…”

Fiducial Reference Measurements for Vegetation Bio-Geophysical Variables: An End-to-End Uncertainty Evaluation Framework

“…However, mean value downsampling cannot be used to correctly propagate the per-pixel uncertainties provided by the RUT through the aggregation procedure, since several uncertainty components (marked with * above) are considered to be correlated in space. Instead, the 'select/deselect' approach described by Gorroño et al [48] was adopted. This involved running the RUT twice, enabling the uncertainty components that are uncorrelated in space to be separated from those that are correlated in space.…”

“…This involved running the RUT twice, enabling the uncertainty components that are uncorrelated in space to be separated from those that are correlated in space. The standard uncertainty in the aggregated pixel values was then taken as the mean of the two RUT outputs [48].…”

Copernicus Sentinel-2 Calibration and Validation

“…The Mission Performance Centre (MPC) as part of the European Space Agency's S2 ground segment carries out the routine S2 calibration and validation activities operationally. In order to guarantee the required data quality as established in the S2 Mission Requirements Document (Drusch, Gascon, & Berger, 2010) (Table 1), the quality of the mission data is monitored by the S2 Quality Working Group (QWG) where Copernicus Services are represented.…”

“…S2VT work presented here mainly focused on Level-1C product type. However, certain authors (Gorroño et al, 2018;Ariza, Irizar, & Bayer, 2018;Keukelaere et al, 2018;Ressl & Pfeifer, 2018) also worked on other product levels (−1B, −2A). For the sake of clarity, a brief outline of these levels is as follows:…”