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

United States Geological Survey Earth Resources Observation and Science Center, 47914 252nd Street, Sioux Falls, SD 57198, USA
NASA Goddard Space Flight Center, Code 618, Greenbelt, MD 20771, USA
Stinger Ghaffarian Technologies Inc., 47914 252nd Street, Sioux Falls, SD 57198, USA
SSAI, 10210 Greenbelt Rd, Lanham, MD 20706, USA
ESA/ESRIN, Largo Galileo Galilei 1, 00044 Frascati, Italy
ACRI-ST, 260 Route du Pin Montard, BP 234, 06904 Sophia-Antipolis, France
CS-SI, Parc de la Plaine, Rue de Brindejonc des Moulinais, BP 5872, 31506 Toulouse CEDEX 5, France
South Dakota State University, Brookings, South Dakota, 57007, USA
Geoscience Australia, G.P.O. Box 378, Canberra, ACT 2601, Australia
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(9), 1340;
Received: 26 June 2018 / Revised: 31 July 2018 / Accepted: 8 August 2018 / Published: 22 August 2018
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. View Full-Text
Keywords: calibration; geometric; radiometric; Landsat; Sentinel; interoperability calibration; geometric; radiometric; Landsat; Sentinel; interoperability
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Helder, D.; Markham, B.; Morfitt, R.; Storey, J.; Barsi, J.; Gascon, F.; Clerc, S.; LaFrance, B.; Masek, J.; Roy, D.P.; Lewis, A.; Pahlevan, N. Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability. Remote Sens. 2018, 10, 1340.

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