Sentinel-2A MSI and Landsat-8 OLI radiometric cross comparison over desert sites

Julia A. Barsi, Bahjat Alhammoud, Jeffrey Czapla-Myers, Ferran Gascon, Md Obaidul Haque, Morakot Kaewmanee, Larry Leigh, Brian L. Markham

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

The Sentinel-2A and Landsat-8 satellites carry on-board moderate resolution multispectral imagers for the purpose of documenting the Earth’s changing surface. Though they are independently built and managed, users will certainly take advantage of the opportunity to have higher temporal coverage by combining the datasets. Thus it is important for the radiometric and geometric calibration of the MultiSpectral Instrument (MSI) and the Operational Land Imager (OLI) to be compatible. Cross-calibration of MSI to OLI has been accomplished using multiple techniques involving the use of pseudo-invariant calibration sites (PICS) using direct comparisons as well as through use of PICS models predicting top-of-atmosphere reflectance. A team from the University of Arizona is acquiring field data under both instruments for vicarious calibration of the sensors. This paper shows that the work done to date by the Landsat and Sentinel-2 calibration teams has resulted in stable radiometric calibration for each instrument and consistency to ~2.5% between the instruments for all the spectral bands that the instruments have in common.

Original languageEnglish (US)
Pages (from-to)822-837
Number of pages16
JournalEuropean Journal of Remote Sensing
Volume51
Issue number1
DOIs
StatePublished - Jan 1 2018

Keywords

  • Landsat
  • MSI
  • OLI
  • Sentinel-2A
  • radiometric calibration

ASJC Scopus subject areas

  • Environmental Science(all)
  • Computers in Earth Sciences
  • Atmospheric Science
  • Applied Mathematics

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  • Cite this

    Barsi, J. A., Alhammoud, B., Czapla-Myers, J., Gascon, F., Haque, M. O., Kaewmanee, M., Leigh, L., & Markham, B. L. (2018). Sentinel-2A MSI and Landsat-8 OLI radiometric cross comparison over desert sites. European Journal of Remote Sensing, 51(1), 822-837. https://doi.org/10.1080/22797254.2018.1507613