Decoding MODIS and VIIRS Quality Science Datasets using the ArcGIS MODIS-VIIRS Python Toolbox


Published: Aug. 18, 2020

All MODIS and VIIRS data products archived at the 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.

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