A Radiometric Uncertainty Tool for the Sentinel 2 Mission

In the framework of the European Copernicus programme, the European Space Agency (ESA) has launched the Sentinel-2 (S2) Earth Observation (EO) mission which provides optical high spatial resolution imagery over land and coastal areas. As part of this mission, a tool (named S2-RUT, from Sentinel-2 Ra...

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Main Authors: Javier Gorroño, Norman Fomferra, Marco Peters, Ferran Gascon, Craig I. Underwood, Nigel P. Fox, Grit Kirches, Carsten Brockmann
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/9/2/178
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author Javier Gorroño
Norman Fomferra
Marco Peters
Ferran Gascon
Craig I. Underwood
Nigel P. Fox
Grit Kirches
Carsten Brockmann
author_facet Javier Gorroño
Norman Fomferra
Marco Peters
Ferran Gascon
Craig I. Underwood
Nigel P. Fox
Grit Kirches
Carsten Brockmann
author_sort Javier Gorroño
collection DOAJ
description In the framework of the European Copernicus programme, the European Space Agency (ESA) has launched the Sentinel-2 (S2) Earth Observation (EO) mission which provides optical high spatial resolution imagery over land and coastal areas. As part of this mission, a tool (named S2-RUT, from Sentinel-2 Radiometric Uncertainty Tool) has been developed. The tool estimates the radiometric uncertainty associated with each pixel in the top-of-atmosphere (TOA) reflectance factor images provided by ESA. This paper describes the design and development process of the initial version of the S2-RUT tool. The initial design step describes the S2 radiometric model where a set of uncertainty contributors are identified. Each of the uncertainty contributors is specified by reviewing the pre- and post-launch characterisation. The identified uncertainty contributors are combined following the guidelines in the ‘Guide to Expression of Uncertainty in Measurement’ (GUM) model and this combination model is further validated by comparing the results to a multivariate Monte Carlo Method (MCM). In addition, the correlation between the different uncertainty contributions and the impact of simplifications in the combination model have been studied. The software design of the tool prioritises an efficient strategy to read the TOA reflectance factor images, extract the auxiliary information from the metadata in the satellite products and the codification of the resulting uncertainty image. This initial version of the tool has been implemented and integrated as part of the Sentinels Application Platform (SNAP).
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spelling doaj.art-888d1cb6ae7b4d73a6d2c0ba4bdd92132022-12-22T04:05:58ZengMDPI AGRemote Sensing2072-42922017-02-019217810.3390/rs9020178rs9020178A Radiometric Uncertainty Tool for the Sentinel 2 MissionJavier Gorroño0Norman Fomferra1Marco Peters2Ferran Gascon3Craig I. Underwood4Nigel P. Fox5Grit Kirches6Carsten Brockmann7National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UKBrockmann Consult, Max-Planck-Str. 2, Geesthacht 21502, GermanyBrockmann Consult, Max-Planck-Str. 2, Geesthacht 21502, GermanyEuropean Space Agency, Via Galileo Galilei, Frascati 00044, ItalySurrey Space Centre, University of Surrey, Guildford GU2 7XH, UKNational Physical Laboratory, Hampton Road, Teddington TW11 0LW, UKBrockmann Consult, Max-Planck-Str. 2, Geesthacht 21502, GermanyBrockmann Consult, Max-Planck-Str. 2, Geesthacht 21502, GermanyIn the framework of the European Copernicus programme, the European Space Agency (ESA) has launched the Sentinel-2 (S2) Earth Observation (EO) mission which provides optical high spatial resolution imagery over land and coastal areas. As part of this mission, a tool (named S2-RUT, from Sentinel-2 Radiometric Uncertainty Tool) has been developed. The tool estimates the radiometric uncertainty associated with each pixel in the top-of-atmosphere (TOA) reflectance factor images provided by ESA. This paper describes the design and development process of the initial version of the S2-RUT tool. The initial design step describes the S2 radiometric model where a set of uncertainty contributors are identified. Each of the uncertainty contributors is specified by reviewing the pre- and post-launch characterisation. The identified uncertainty contributors are combined following the guidelines in the ‘Guide to Expression of Uncertainty in Measurement’ (GUM) model and this combination model is further validated by comparing the results to a multivariate Monte Carlo Method (MCM). In addition, the correlation between the different uncertainty contributions and the impact of simplifications in the combination model have been studied. The software design of the tool prioritises an efficient strategy to read the TOA reflectance factor images, extract the auxiliary information from the metadata in the satellite products and the codification of the resulting uncertainty image. This initial version of the tool has been implemented and integrated as part of the Sentinels Application Platform (SNAP).http://www.mdpi.com/2072-4292/9/2/178uncertaintySentinel-2RUTGUMradiometry
spellingShingle Javier Gorroño
Norman Fomferra
Marco Peters
Ferran Gascon
Craig I. Underwood
Nigel P. Fox
Grit Kirches
Carsten Brockmann
A Radiometric Uncertainty Tool for the Sentinel 2 Mission
Remote Sensing
uncertainty
Sentinel-2
RUT
GUM
radiometry
title A Radiometric Uncertainty Tool for the Sentinel 2 Mission
title_full A Radiometric Uncertainty Tool for the Sentinel 2 Mission
title_fullStr A Radiometric Uncertainty Tool for the Sentinel 2 Mission
title_full_unstemmed A Radiometric Uncertainty Tool for the Sentinel 2 Mission
title_short A Radiometric Uncertainty Tool for the Sentinel 2 Mission
title_sort radiometric uncertainty tool for the sentinel 2 mission
topic uncertainty
Sentinel-2
RUT
GUM
radiometry
url http://www.mdpi.com/2072-4292/9/2/178
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