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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #406422

Research Project: From Field to Watershed: Enhancing Water Quality and Management in Agroecosystems through Remote Sensing, Ground Measurements, and Integrative Modeling

Location: Hydrology and Remote Sensing Laboratory

Title: The 50-year Landsat collection 2 archive

Author
item CRAWFORD, C - Us Geological Survey (USGS)
item ROY, D - Michigan State University
item ARAB, S - Us Geological Survey (USGS)
item BARNES, C - Us Geological Survey (USGS)
item VERMOTE, E - Goddard Space Flight Center
item HULLEY, G - Jet Propulsion Laboratory
item GERACE, A - Rochester Institute Of Technology
item CHOATE, M - Us Geological Survey (USGS)
item ENGEBRETSON, C - Us Geological Survey (USGS)
item SCHMIDT, GAIL - Us Geological Survey (USGS)
item ANDERSON, C - Us Geological Survey (USGS)
item Anderson, Martha
item BOUCHARD, M - Us Geological Survey (USGS)
item SKAKUN, S - University Of Maryland
item YAN, L - Michigan State University
item ZHANG, H - South Dakota State University
item ZHU, Z - University Of Connecticut
item ZAHN, S - Us Geological Survey (USGS)

Submitted to: Science of Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/13/2023
Publication Date: 9/18/2023
Citation: Crawford, C., Roy, D., Arab, S., Barnes, C., Vermote, E., Hulley, G., Gerace, A., Choate, M., Engebretson, C., Schmidt, G., Anderson, C., Anderson, M.C., Bouchard, M., Skakun, S., Yan, L., Zhang, H., Zhu, Z., Zahn, S. 2023. The 50-year Landsat collection 2 archive. Science of Remote Sensing. 8. Article e100103. https://doi.org/10.1016/j.srs.2023.100103.
DOI: https://doi.org/10.1016/j.srs.2023.100103

Interpretive Summary: For 50 years, the Landsat suite of satellites have been collecting Earth remote sensing imagery in multiple wavebands, documenting changes in the Earth surface conditions occurring at scales of human management (30-100 m). The United States Geological Survey (USGS) converts the raw imagery collected by Landsat into higher level products, including the geolocation and radiometric corrections needed to make the imagery useable for science and applications. These products are delivered as “Collections” – consistently processed(or reprocessed) over the full 50-year archive to enable robust investigations of change. This manuscript describes the products and processing stream involved in generating Landsat Collection 2, describing improvements to Collection 1 and new products distributed with this collection, including surface reflectance and surface temperature. This paper provides a valuable resource for users of Landsat imagery, and also looks forward to new products and improvements that will be part of Collection 3.

Technical Abstract: The Landsat global consolidated data archive now exceeds 50 years. In recognition of the need for consistently processed data, the United States Geological Survey (USGS) initiated collection-based Landsat processing with the entire archive processed as Collection 1 in 2016. In preparation for the data from the, now successfully launched, Landsat 9 satellite, the USGS reprocessed the archive as Collection 2 in 2020. This paper describes the contents and advancements provided by Landsat Collection 2, highlights the differences between Collection 1 and Collection 2, and concludes with a discussion on envisioned Landsat Collection 3 improvements in preparation for the Landsat Next mission planned for launch in the early 2030s. Notably, the Landsat Collection 2 products have improved geolocation and, for the first time in the Landsat mission history, the USGS now provides a standard global inventory of Level 2 surface reflectance and surface temperature products. The USGS used a commercial cloud compute architecture via Amazon Web Services (AWS) to efficiently process over 9 million images totaling more than 9 petabytes in a timely and cost-effective manner and to enable direct user access of Landsat data in the cloud.