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

TLDR

Combining data from multiple sensors into a seamless time series—data interoperability—holds promise for advancing Earth system science, but is limited by differences in satellite design and calibration. The study aimed to tackle calibration’s impact on interoperability by convening a workshop focused on Landsat and Sentinel‑2 sensor integration. Experts met during the Pecora 20 conference to discuss and develop recommendations. The workshop produced four key recommendations: enhance agency–community communication, adopt a collections‑based processing approach, refine calibration methods, and establish a comprehensive validation process for surface reflectance products.

Abstract

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.