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Wildfire forecasting is of paramount importance for disaster risk reduction and environmental sustainability.
Hands-on Bayesian Neural Networks – a Tutorial for Deep Learning Users
Laurent Valentin Jospin, Wray Buntine, Farid Boussaid, Hamid Laga, and Mohammed Bennamoun · 2007
Earlier work this paper cites.
Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data
Fantine Huot, R. Lily Hu, Matthias Ihme, Qing Wang, John Burge, Tianjian Lu, Jason Hickey, Yi-Fan Chen, and John Anderson · 2010
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The european forest fire information system in the context of environmental policies of the european union
Jesús San-Miguel-Ayanz, Ernst Schulte, Guido Schmuck, and Andrea Camia · 2011
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Continent-wide DEM creation for the european union
A. Bashfield and A. Keim · 2011
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Corine land cover and land cover change products
György Büttner · 2014
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Wildfire risk estimation in the mediterranean area
A. A. Ager, H. K. Preisler, B. Arca, D. Spano, and M. Salis · 2014
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Convolutional LSTM network: A machine learning approach for precipitation nowcasting
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo · 2015
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The status and challenge of global fire modelling
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Doug I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, and Paulo Artaxo · 2016
Cited alongside, same era.
The collection 6 MODIS active fire detection algorithm and fire products
Louis Giglio, Wilfrid Schroeder, and Christopher O. Justice · 2016
Cited alongside, same era.
Exacerbated fires in Mediterranean Europe due to anthropogenic warming projected with non-stationary climate-fire models
Marco Turco, Juan José Rosa-Cánovas, Joaquín Bedia, Sonia Jerez, Juan Pedro Montávez, Maria Carmen Llasat, and Antonello Provenzale · 2018
Cited alongside, same era.
Deep learning and process understanding for data-driven Earth system science
Markus Reichstein, Gustau Camps-Valls, Bjorn Stevens, Martin Jung, Joachim Denzler, and Nuno Carvalhais · 2019
Cited alongside, same era.
Fire Danger Observed from Space
M. Lucrecia Pettinari and Emilio Chuvieco · 2020
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A review of machine learning applications in wildfire science and management
Piyush Jain, Sean C.P. Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, and Mike D. Flannigan · 2020
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Evaluation procedures for forecasting with spatiotemporal data
Mariana Oliveira, Luís Torgo, and Vítor Santos Costa · 2021
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A datacube for the analysis of wildfires in greece, June 2021
Ioannis Prapas, Spyros Kondylatos, and Ioannis Papoutsis · 2021
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Era5-land: A state-of-the-art global reanalysis dataset for land applications
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, et al · 2021
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Explaining deep neural networks and beyond: A review of methods and applications
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Forest fire susceptibility modeling using a convolutional neural network for yunnan province of china
Guoli Zhang, Ming Wang, and Kai Liu · 2019
Cited alongside, same era.
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J Anders, and Klaus-Robert Müller · 2021
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