Active Fire Mapping on Brazilian Pantanal Based on Deep Learning and CBERS 04A Imagery

Fire in Brazilian Pantanal represents a serious threat to biodiversity. The Brazilian National Institute of Spatial Research (INPE) has a program named Queimadas, which estimated from January 2020 to October 2020, a burned area in Pantanal of approximately 40,606 km2. This program also provides dail...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 14; H. 3; S. 688
Hauptverfasser:	Higa, Leandro, Marcato Junior, José, Rodrigues, Thiago, Zamboni, Pedro, Silva, Rodrigo, Almeida, Laisa, Liesenberg, Veraldo, Roque, Fábio, Libonati, Renata, Gonçalves, Wesley Nunes, Silva, Jonathan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.02.2022
Schlagworte:	Accuracy Artificial neural networks Biodiversity Brazil Cameras China convolutional neural network data collection Datasets Deep learning Drought Earth resources Environmental conditions Environmental impact Fire detection Fire fighting Forest & brush fires Image acquisition Neural networks object detection Object recognition Pantanal Remote sensing Satellites Sensors Spatial data Spatial discrimination Spatial resolution Surveillance Unmanned aerial vehicles wildfire Wildfires Brazil Pantanal China
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
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