Preprint Brief Report Version 1 Preserved in Portico This version is not peer-reviewed

Predicting Large Wildfires in the Contiguous United States Using Deep Neural Networks

Sambandh Bhusan Dhal
* ORCID logo ,
Shubham Jain
ORCID logo ,
Krishna Chaitanya Gadepally
,
Prathik Vijaykumar
,
Bhavesh Hariom Sharma
,
Bharat Sharma Acharya
,
Kevin Nowka
,
Stavros Kalafatis
*
Version 1 : Received: 10 May 2023 / Approved: 10 May 2023 / Online: 10 May 2023 (14:46:12 CEST)

How to cite: Dhal, S.B.; Jain, S.; Gadepally, K.C.; Vijaykumar, P.; Sharma, B.H.; Acharya, B.S.; Nowka, K.; Kalafatis, S. Predicting Large Wildfires in the Contiguous United States Using Deep Neural Networks. Preprints 2023, 2023050768. https://doi.org/10.20944/preprints202305.0768.v1 Dhal, S.B.; Jain, S.; Gadepally, K.C.; Vijaykumar, P.; Sharma, B.H.; Acharya, B.S.; Nowka, K.; Kalafatis, S. Predicting Large Wildfires in the Contiguous United States Using Deep Neural Networks. Preprints 2023, 2023050768. https://doi.org/10.20944/preprints202305.0768.v1

Abstract

Over the last several decades, large wildfires are increasingly common across the United States causing disproportionate impact on forest health and function, human well-being, and economy. Here, we examine the severity of large wildfires across the Contiguous United States over the past decade (2011-2020) using a wide array of meteorological, vegetational, and topographical features in the Deep Neural Network model. A total of 4,538 wildfire incidents were used in the analysis covering 87,305 square miles of burned area. We observed the highest number of large wildfires in California, Texas, and Idaho, with lightning causing 43 % of these incidents. Importantly, results indicate that the severity of wildfire occurrences is highly correlated with the climatological forcings, land cover, location, and elevation of the ecosystem. Overall, results may serve useful guide in managing landscapes under changing climate and disturbance regimes.

Keywords

Climate; Contiguous United States; Deep Neural Network; Land Cover; Large Wildfire

Subject

Environmental and Earth Sciences, Environmental Science

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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