A Radiometric Uncertainty Tool for the Sentinel 2 Mission
| Autor: | Carsten Brockmann, Nigel Fox, Ferran Gascon, Grit Kirches, Craig Underwood, Marco Peters, Norman Fomferra, Javier Gorroño |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Multivariate statistics
Earth observation 010504 meteorology & atmospheric sciences Computer science Science Monte Carlo method radiometry uncertainty Sentinel-2 RUT GUM 01 natural sciences 010309 optics 0103 physical sciences General Earth and Planetary Sciences Measurement uncertainty Radiometry Satellite Radiometric dating 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Remote Sensing, Vol 9, Iss 2, p 178 (2017) Remote Sensing; Volume 9; Issue 2; Pages: 178 |
| ISSN: | 2072-4292 |
| Popis: | 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). |
| Databáze: | OpenAIRE |
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