Landsat Collections ensure that all Landsat Level-1 products contain known data quality.
In 2016, the USGS reorganized the Landsat archive into a tiered collection management structure titled Landsat Collection 1. This structure ensures that all Landsat Level-1 products provide a consistent archive of known data quality while controlling continuous improvement of the archive and access to all data as they are acquired. The implementation of collections represents a substantial change in the management of the Landsat archive by ensuring consistent quality through time and across all instruments. Collection 1 contains all Level-1 data acquired since 1972 to present from Landsat 1-8. Landsat 9 is only available in Collection 2.
NOTE: Landsat Collection 1 data and products are no longer available to download from the USGS as of December 30, 2022. Landsat Collection 2 remains available. Please access the Landsat Collection 2 webpage for information about Collection 2 data and science products.
Landsat Collection 2 marks the second major reprocessing event of the USGS Landsat Level-1 archive, resulting in several product improvements that harness recent advancements in data processing, algorithm development, and data access and distribution capabilities. A primary characteristic of Collection 2 is the substantial improvement in the absolute geolocation accuracy of the global ground reference dataset used in the Landsat Level-1 processing flow. Additionally, Collection 2 includes updated global digital elevation modeling sources, calibration and validation updates, as well as global Level-2 surface reflectance and surface temperature scene-based products from 1982 to present. Collection 2 contains all Landsat sensors Landsat 1-9.
Visit the Landsat Data Access page to discover how to search and download all Landsat products from USGS data portals.
Wulder, M.A., Loveland, T.R., Roy, D.P., Crawford, C.J., Masek, J.G., Woodcock, C.E., Allen, R.G., Anderson, M.C., Belward, A.S., et al., 2019, Current status of Landsat program, science, and applications: Remote Sensing of Environment, v. 225, p. 127–147, at https://doi.org/10.1016/j.rse.2019.02.015.