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Related papers: Comparing Next-Day Wildfire Predictability of MODI…

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Monitoring the fuel moisture content (FMC) of vegetation is crucial for managing and mitigating the impact of wildland fires. The combination of in situ FMC observations with numerical weather prediction (NWP) models and satellite…

Predicting wildfire spread is critical for land management and disaster preparedness. To this end, we present `Next Day Wildfire Spread,' a curated, large-scale, multivariate data set of historical wildfires aggregating nearly a decade of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-05 Fantine Huot , R. Lily Hu , Nita Goyal , Tharun Sankar , Matthias Ihme , Yi-Fan Chen

The increasing frequency of catastrophic natural events, such as wildfires, calls for the development of rapid and automated wildfire detection systems. In this paper, we propose a wildfire identification solution to improve the accuracy of…

Image and Video Processing · Electrical Eng. & Systems 2023-08-08 Angelica Urbanelli , Luca Barco , Edoardo Arnaudo , Claudio Rossi

Increasing wildfire occurrence has spurred growing interest in wildfire spread prediction. However, even the most complex wildfire models diverge from observed progression during multi-day simulations, motivating need for data assimilation.…

Currently available satellite active fire detection products from the VIIRS and MODIS instruments on polar-orbiting satellites produce detection squares in arbitrary locations. There is no global fire/no fire map, no detection under cloud…

Data Analysis, Statistics and Probability · Physics 2014-11-18 Jan Mandel , Adam K. Kochanski , Martin Vejmelka , Jonathan D. Beezley

Data likelihood of fire detection is the probability of the observed detection outcome given the state of the fire spread model. We derive fire detection likelihood of satellite data as a function of the fire arrival time on the model grid.…

Applications · Statistics 2022-02-16 James Haley , Angel Farguell Caus , Adam K. Kochanski , Sher Schranz , Jan Mandel

Recent research has demonstrated the potential of deep neural networks (DNNs) to accurately predict wildfire spread on a given day based upon high-dimensional explanatory data from a single preceding day, or from a time series of T…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Saad Lahrichi , Jake Bova , Jesse Johnson , Jordan Malof

Climate change has intensified extreme weather and wildfire conditions globally. Canada experienced record-breaking wildfires in 2023 and 2025, burning millions of hectares and severely impacting the Prairie provinces, with Manitoba facing…

Computers and Society · Computer Science 2026-04-17 Xiang Shi , Peng Hu

Due to severe societal and environmental impacts, wildfire prediction using multi-modal sensing data has become a highly sought-after data-analytical tool by various stakeholders (such as state governments and power utility companies) to…

Applications · Statistics 2023-10-12 Chen Xu , Yao Xie , Daniel A. Zuniga Vazquez , Rui Yao , Feng Qiu

Wildland fires pose an increasingly serious problem in our society. The number and severity of these fires has been rising for many years. Wildfires pose direct threats to life and property as well as threats through ancillary effects like…

Machine Learning · Computer Science 2022-04-05 James D. Haley

Accurate next-day active fire forecasts can support early warning, disaster response, forest risk assessment, and downstream estimation of fire-related carbon emissions. Existing machine learning approaches to wildfire forecasting typically…

Machine Learning · Computer Science 2026-05-12 Yuchen Bai , Georgios Athanasiou , Xin Yu , Diogenis Antonopoulos , Ioannis Papoutsis , Stijn Hantson , Nuno Carvalhais

Wildfires are becoming increasingly frequent, with potentially devastating consequences, including loss of life, infrastructure destruction, and severe environmental damage. Low Earth orbit satellites equipped with onboard sensors can…

Systems and Control · Electrical Eng. & Systems 2026-05-11 Brycen D. Pearl , Joshua G. Warner , Hang Woon Lee

Quantitative estimate of observational uncertainty is an essential ingredient to correctly interpret changes in climatic and environmental variables such as wildfires. In this work we compare four state-of-the-art satellite fire products…

Atmospheric and Oceanic Physics · Physics 2019-06-17 Marco Turco , Sixto Herrera , Etienne Tourigny , Emilio Chuvieco , Antonello Provenzale

The increasing frequency and severity of wildfires necessitates advanced methods for effective surveillance and management, as traditional ground-based techniques often struggle to adapt to rapidly changing fire behavior and environmental…

Image and Video Processing · Electrical Eng. & Systems 2026-05-11 Afonso Oliveira , João P. Matos-Carvalho , Filipe Moutinho , Nuno Fachada

The Visible Infrared Imaging Radiometer Suite (VIIRS) active fire product is widely used for global fire monitoring, yet its confidence classification scheme exhibits an undocumented systematic pattern. Through analysis of 21,540,921 fire…

Applications · Statistics 2025-11-03 Rohit Rajendra Dhage

Wildfires pose significant threats to ecosystems, economies, and communities worldwide, necessitating advanced predictive methods for effective mitigation. This study introduces a novel and comprehensive dataset specifically designed for…

Machine Learning · Computer Science 2025-01-22 Ayoub Jadouli , Chaker El Amrani

Wildfires pose a serious threat to the environment of the world. The global wildfire season length has increased by 19% and severe wildfires have besieged nations around the world. Every year, forests are burned by wildfires, causing vast…

Artificial Intelligence · Computer Science 2023-12-13 Prisha Shroff

Frequent and severe wildfires have been observed lately on a global scale. Wildfires not only threaten lives and properties, but also pose negative environmental impacts that transcend national boundaries (e.g., greenhouse gas emission and…

Signal Processing · Electrical Eng. & Systems 2021-09-23 How-Hang Liu , Ronald Y. Chang , Yi-Ying Chen , I-Kang Fu

Due to climate change, the extreme wildfire has become one of the most dangerous natural hazards to human civilization. Even though, some wildfires may be initially caused by human activity, but the spread of wildfires is mainly determined…

Machine Learning · Computer Science 2025-03-13 Qijun Chen , Shaofan Li

This work demonstrates the possibilities for improving wildfire and air quality management in the western United States by leveraging the unprecedented hourly data from NASA's TEMPO satellite mission and advances in self-supervised deep…

Machine Learning · Computer Science 2025-10-14 Nicholas LaHaye , Thilanka Munashinge , Hugo Lee , Xiaohua Pan , Gonzalo Gonzalez Abad , Hazem Mahmoud , Jennifer Wei
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