Software
An official USGS software project is code reviewed and approved at the bureau-level for distribution.
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Decoding and using the Landsat Pixel Quality Assessment Band for Masking Decoding and using the Landsat Pixel Quality Assessment Band for Masking
This work demonstrates how to utilize the Pixel QA band in Landsat data to mask out pixels affected by clouds and snow specifically in the Vancouver, Canada area. This process involves decoding the QA bit flag, creating a mask for cloud- or snow-affected pixels, and applying it to the imported data.
Querying the Landsat SpatioTemporal Asset Catalog through Metadata Filtering Querying the Landsat SpatioTemporal Asset Catalog through Metadata Filtering
The Landsat STAC catalog provides a versatile and user-friendly interface for accessing and exploring the USGS Landsat Archive. Understanding the characteristics and differences between the various Landsat data products is helpful for choosing suitable data for your research and applications. This tutorial focuses on filtering the Landsat STAC catalog for products based on various...
Landsat STAC Direct Requester Pays Download Landsat STAC Direct Requester Pays Download
In this tutorial, we demonstrate the process of accessing Landsat data files through the STAC API and the AWS command-line tools, specifically the requester-pays functionality. Users can define their spatial and temporal parameters to query and download multiple Landsat data band files.
Using the Landsat SpatioTemporal Asset Catalog (STAC) for Band Selection and Retrieval Using the Landsat SpatioTemporal Asset Catalog (STAC) for Band Selection and Retrieval
This tutorial will introduces the basics of selecting a subset of bands over a set area of interest (AOI) and time span, loading the desired cloud optimized geotiffs (COGs) into a Jupyter Notebook directly from the cloud, cropping the bands and creating a natural composite.
Machine to Machine (M2M) Querying MetadataFilters Machine to Machine (M2M) Querying MetadataFilters
This tutorial demonstrates how to query using metadata specific to the various collections of Landsat data. We use the following Machine-to-Machine API filters: metadataValue, metadataBetween, metadataAnd, and metadataOr. Users can view queryable metadata after following one of these steps (1) Submitting a dataset-filters query and listing the results (2) Submitting a search on Earth...
Machine-to-Machine (M2M) Landsat-9 Search and Download Machine-to-Machine (M2M) Landsat-9 Search and Download
This tutorial is designed to guide users through metadata filtering for Landsat-9 satellite data within the Landsat 8-9 Operational Land Imager and Thermal Infrared Sensor Collection 2 Level-2 dataset. The chosen location for use is Albemarle Sound, a large estuarine body of water in northeastern North Carolina, United States. The emphasis on metadata filtering is crucial, especially...