Copernicus Sentinel-2A Calibration and Products Validation Status

By F. Gascon, C. Bouzinac, O. Thépaut, Mathieu Jung, B. Francesconi, J. Louis, Vincent Lonjou, B. Lafrance, S. Massera, A. Gaudel-Vacaresse and 13 more. Remote Sensing, 2017

534 citations recorded by the source corpus.

As part of the Copernicus programme of the European Commission (EC), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This article provides a description of the calibration activities and the status of the mission products validation activities after one year in orbit. Measured performances, from the validation activities, cover both Top-Of-Atmosphere (TOA) and Bottom-Of-Atmosphere (BOA) products. The presented results show the good quality of the mission products both in terms of radiometry and geometry and provide an overview on next mission steps related to data quality aspects.

Subfields: Aerospace Engineering, Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/e0548ed0816a7a1be58c0cf7b7af753d85f4131a

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Citations in the corpus

Current status of Landsat program, science, and applications (2019, methodology): “In addition, the processing system baselines and Level-2 (surface reflectance) approach for both data sets, in particular the more recent Sentinel-2 data (Gascon et al., 2017), have changed quite frequently.”
Land cover 2.0 (2018, methodology): “In narrow ﬁ eld of view data, such as Landsat or Sentinel-2 (Gascon et al. 2017), these e ﬀ ects have been minimized using statistical correction methods (Toivonen et al. 2006; Hansen et al. 2008) and more recently using more physically-based methods (Roy et al. 2016b, 2017).”
Sentinel-2A and 2B absolute calibration monitoring (2019, methodology): “A detailed description of the instruments together with an S2A performance review is available in Gascon et al. (2017).”
Analysis Ready Data: Enabling Analysis of the Landsat Archive (2018, methodology): “The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image [49] with completion expected in 2019 and then the Collection 1 data will be reprocessed as Collection 2.”
Machine learning for digital soil mapping: Applications, challenges and suggested solutions (2020, methodology): “Further potential covariates are provided by remote sensing such as by the MODIS (Mira et al., 2015) satellite or Sentinel-2A hyperspectral sensor (Gascon et al., 2017).”
A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring (2017, background): “Similarly, the Sentinel-2 satellites will systematically acquire observations over land and coastal areas from −56◦ to 84◦ latitude including islands larger 100 km2, all the European Union islands, the Mediterranean Sea, and all inland water bodies and closed seas [28].”
Sen2Cor for Sentinel-2 (2017, methodology): “This map is used internally in Sen2Cor in the AC module to distinguish between cloudy, clear and water pixels, but it does not perform a land cover classification map in a strict sense [9].”