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October 28, 2024

Tutorials are now available to provide guidance and help users access, query, and use Landsat data directly from the USGS cloud storage location. 

The release of Landsat Collection 2 in 2020 introduced the ability to access Landsat data more efficiently within a commercial cloud environment. Landsat Collection 2 data are stored in and distributed from the Amazon Web Services (AWS) commercial cloud. Cloud storage allows researchers and data scientists to analyze and process Landsat data directly, eliminating time-consuming downloads of full scene bundles, the need for users to apply pre-processing algorithms, and eliminates the need to store large amounts of data.
 

A suite of helpful tutorials is now available from the EROS User Services code repository.

The tutorials are created in Python Jupyter notebooks and are a valuable resource to help users become familiar with the Spatiotemporal Asset Catalog (STAC) family of specifications—a metadata standard that expedites large-collection searches and enables interoperability between data from different sensors using common machine-readable language. Specific subjects include an introduction to cloud data access, metadata filtering, band selection, and how to use the Quality Assessment (QA) band to filter clouds, snow, and cloud shadows from Landsat imagery. 

The image below displays an example query that was created using information from the Querying the Landsat SpatioTemporal Asset Catalog with PySTAC tutorial. 

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Landsat SpatioTemporal Asset Catalog with PySTAC Query Example

In addition to STAC-specific instructions, tutorials for accessing Landsat data in the USGS EROS archives via the ‘Machine-to-Machine’ (M2M) and quick guides are also available in the repository.  

Please contact EROS User Services with any questions about STAC, or visit the Landsat Commercial Cloud Data Access webpage to learn more about accessing data in the cloud. 

 

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