All Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) data products archived at NASA's Land Processes Distributed Active Archive Center (LP DAAC) contain quality assurance information which should be considered when determining the usability and usefulness of a dataset for a particular science application. This information, however, has been notoriously difficult for users to access.
Quality information is often stored as an integer value that requires the user to decode into binary strings. In order to interpret the binary string users must map the unique combinations of bits found in separate subsets of the binary string (i.e. bit-fields) to quality tables that characterize the particular quality attribute associated with each bit-field. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding MODIS and VIIRS quality data layers while also producing thematic quality raster files for each quality attribute.
Relevant Tools
Name | Description |
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Data Prep Scripts | This collection of R and Python scripts can be used to download data and perform basic data processing functions such as georeferencing, reprojecting, converting, and reformatting data. |
ArcGIS MODIS-VIIRS Python Toolbox | This Python Toolbox for ArcGIS shows how to interact with MODIS and VIIRS science datasets. |