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A near real-time web-system for predicting fire spread across the Cerrado biome

Wildfires are aggravating due to climate change. Public policies need territorial intelligence to prevent and promptly fight fires, especially in vast regions like Brazil. To this end, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires i...

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Autores principales: Oliveira, Ubirajara, Soares-Filho, Britaldo, Rodrigues, Hermann, Figueira, Danilo, Gomes, Leticia, Leles, William, Berlinck, Christian, Morelli, Fabiano, Bustamante, Mercedes, Ometto, Jean, Miranda, Heloísa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039015/
https://www.ncbi.nlm.nih.gov/pubmed/36964148
http://dx.doi.org/10.1038/s41598-023-30560-9
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author Oliveira, Ubirajara
Soares-Filho, Britaldo
Rodrigues, Hermann
Figueira, Danilo
Gomes, Leticia
Leles, William
Berlinck, Christian
Morelli, Fabiano
Bustamante, Mercedes
Ometto, Jean
Miranda, Heloísa
author_facet Oliveira, Ubirajara
Soares-Filho, Britaldo
Rodrigues, Hermann
Figueira, Danilo
Gomes, Leticia
Leles, William
Berlinck, Christian
Morelli, Fabiano
Bustamante, Mercedes
Ometto, Jean
Miranda, Heloísa
author_sort Oliveira, Ubirajara
collection PubMed
description Wildfires are aggravating due to climate change. Public policies need territorial intelligence to prevent and promptly fight fires, especially in vast regions like Brazil. To this end, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.04 ha spatial resolution. In both versions, the model attains 65–89% of spatial match. Model results together with ancillary data, e.g., historical burned areas and annual CO(2) emissions from fires, are available on an interactive web-platform that serves as a tool for fire prevention and fight, particularly in the selected conservation units where the platform is being used for daily operations.
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spelling pubmed-100390152023-03-26 A near real-time web-system for predicting fire spread across the Cerrado biome Oliveira, Ubirajara Soares-Filho, Britaldo Rodrigues, Hermann Figueira, Danilo Gomes, Leticia Leles, William Berlinck, Christian Morelli, Fabiano Bustamante, Mercedes Ometto, Jean Miranda, Heloísa Sci Rep Article Wildfires are aggravating due to climate change. Public policies need territorial intelligence to prevent and promptly fight fires, especially in vast regions like Brazil. To this end, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.04 ha spatial resolution. In both versions, the model attains 65–89% of spatial match. Model results together with ancillary data, e.g., historical burned areas and annual CO(2) emissions from fires, are available on an interactive web-platform that serves as a tool for fire prevention and fight, particularly in the selected conservation units where the platform is being used for daily operations. Nature Publishing Group UK 2023-03-24 /pmc/articles/PMC10039015/ /pubmed/36964148 http://dx.doi.org/10.1038/s41598-023-30560-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Oliveira, Ubirajara
Soares-Filho, Britaldo
Rodrigues, Hermann
Figueira, Danilo
Gomes, Leticia
Leles, William
Berlinck, Christian
Morelli, Fabiano
Bustamante, Mercedes
Ometto, Jean
Miranda, Heloísa
A near real-time web-system for predicting fire spread across the Cerrado biome
title A near real-time web-system for predicting fire spread across the Cerrado biome
title_full A near real-time web-system for predicting fire spread across the Cerrado biome
title_fullStr A near real-time web-system for predicting fire spread across the Cerrado biome
title_full_unstemmed A near real-time web-system for predicting fire spread across the Cerrado biome
title_short A near real-time web-system for predicting fire spread across the Cerrado biome
title_sort near real-time web-system for predicting fire spread across the cerrado biome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039015/
https://www.ncbi.nlm.nih.gov/pubmed/36964148
http://dx.doi.org/10.1038/s41598-023-30560-9
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