Remote Sensing (Aug 2018)

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

  • Dennis Helder,
  • Brian Markham,
  • Ron Morfitt,
  • Jim Storey,
  • Julia Barsi,
  • Ferran Gascon,
  • Sebastien Clerc,
  • Bruno LaFrance,
  • Jeff Masek,
  • David P. Roy,
  • Adam Lewis,
  • Nima Pahlevan

DOI
https://doi.org/10.3390/rs10091340
Journal volume & issue
Vol. 10, no. 9
p. 1340

Abstract

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Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable.

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