The Landsat Burned Area algorithm and products for the conterminous United States

Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Esse...

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Veröffentlicht in:	Remote sensing of environment Jg. 244; S. 111801
Hauptverfasser:	Hawbaker, Todd J., Vanderhoof, Melanie K., Schmidt, Gail L., Beal, Yen-Ju, Picotte, Joshua J., Takacs, Joshua D., Falgout, Jeff T., Dwyer, John L.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Inc 01.07.2020 Elsevier BV
Schlagworte:	Algorithms artificial intelligence burn severity Burned area climate Climate change crops data collection Errors Fire hay Image processing Image resolution Image segmentation Land cover Landsat Landsat satellites Learning algorithms Machine learning moderate resolution imaging spectroradiometer monitoring Pasture pastures Regression analysis Remote sensing Satellite imagery Sensors Spectroradiometers time series analysis Trends United States vegetation types wildfires United States > US United States Burned area United States Landsat Fire Machine learning
ISSN:	0034-4257, 1879-0704
Online-Zugang:	Volltext
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