Datasets used in "Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management"

Data sets used to train, validate, and test machine learning models for the prediction of 10-hour dead fuel moisture content. The data sets are for 375 m and 1 km resolutions. MADIS climatography data is also included. The datasets may be processed using the code supplied at https://github.com/NCAR/...

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Hauptverfasser:	Schreck, John S, Petzke, William, Jimenez, Pedro A., Brummet, Thomas, Knievel, Jason C., James, Eric, Kosovic, Branko, Gagne, David John
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Sprache:	eng
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creator	Schreck, John S Petzke, William Jimenez, Pedro A. Brummet, Thomas Knievel, Jason C. James, Eric Kosovic, Branko Gagne, David John
description	Data sets used to train, validate, and test machine learning models for the prediction of 10-hour dead fuel moisture content. The data sets are for 375 m and 1 km resolutions. MADIS climatography data is also included. The datasets may be processed using the code supplied at https://github.com/NCAR/fmc_viirs.
doi_str_mv	10.5281/zenodo.8030682
format	Dataset
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identifier	DOI: 10.5281/zenodo.8030682
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title	Datasets used in "Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management"
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