Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Ciência Florestal (Online) |
Texto Completo: | https://periodicos.ufsm.br/cienciaflorestal/article/view/64171 |
Resumo: | Created in 2014, the Serra da Gandarela National Park (SGNP), is repeatedly affected by wildfires. This Conservation Unit is located in the Iron Quadrangle (MG), in a transition zone between the Cerrado and the Atlantic Forest biomes, and is characterized by a complex mosaic of phytophysiognomies. The aim of this investigation was to compare the performance of two risk mapping models for forest fire in the SGNP and its surroundings, based on two different approaches, being one by multicriteria analysis, AHP method and the other a simple probability method, called Hot Spot History, which provided information on the areas of highest and lowest risk and their environmental and human characteristics. Spatial data from remote sensing and GIS were used to simulate, in sequence, the fire ignition, the fire spread and, finally, the risk of wildfire. The validation of the risk models was performed by the Kappa coefficient (K). The results showed that the model based on the History of Hot Points obtained greater accuracy (0.61) than the model generated by the AHP method (0.54). The Brazilian Savanna, Rupestrian Fields and Field coverings were the most susceptible to wildfire, as they are formed by herbaceous vegetations and are located very close to urban agglomerations and roads. The slopes oriented to the North and West were important for the prediction of wildfires slope and, on the other hand, the slope of the terrain was not important to discretize the areas of greater and lesser fragility to the referred ecological disturbance. |
id |
UFSM-6_b015113ed0fe3ca5dc32e466de78babe |
---|---|
oai_identifier_str |
oai:ojs.pkp.sfu.ca:article/64171 |
network_acronym_str |
UFSM-6 |
network_name_str |
Ciência Florestal (Online) |
repository_id_str |
|
spelling |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, BrazilSuscetibilidade a incêndios florestais em unidade de conservação localizada na região de transição dos Biomas Cerrado e Mata Atlântica, BrasilRupestrian FieldsGISMulticriteria AnalysisCampos RupestresSIGAnálise multicritérioCreated in 2014, the Serra da Gandarela National Park (SGNP), is repeatedly affected by wildfires. This Conservation Unit is located in the Iron Quadrangle (MG), in a transition zone between the Cerrado and the Atlantic Forest biomes, and is characterized by a complex mosaic of phytophysiognomies. The aim of this investigation was to compare the performance of two risk mapping models for forest fire in the SGNP and its surroundings, based on two different approaches, being one by multicriteria analysis, AHP method and the other a simple probability method, called Hot Spot History, which provided information on the areas of highest and lowest risk and their environmental and human characteristics. Spatial data from remote sensing and GIS were used to simulate, in sequence, the fire ignition, the fire spread and, finally, the risk of wildfire. The validation of the risk models was performed by the Kappa coefficient (K). The results showed that the model based on the History of Hot Points obtained greater accuracy (0.61) than the model generated by the AHP method (0.54). The Brazilian Savanna, Rupestrian Fields and Field coverings were the most susceptible to wildfire, as they are formed by herbaceous vegetations and are located very close to urban agglomerations and roads. The slopes oriented to the North and West were important for the prediction of wildfires slope and, on the other hand, the slope of the terrain was not important to discretize the areas of greater and lesser fragility to the referred ecological disturbance.O Parque Nacional da Serra da Gandarela (SGNP), criado em 2014, é repetidamente afetado por incêndios florestais. Essa Unidade de Conservação está localizada no quadrilátero ferrífero (MG), em uma área de transição entre os biomas Cerrado e Mata Atlântica, e é caracterizada por um complexo mosaico de fitofisionomias. O objetivo desta investigação foi comparar o desempenho de dois modelos de mapeamento de risco para incêndios florestais no SGNP e seu entorno, com base em duas abordagens distintas, uma por análise multicritério, método AHP e um método de probabilidade simples, denominado Hot Spot History, que forneceu informações sobre as áreas de maior e menor risco e suas características ambientais e humanas. Dados espaciais de sensoriamento remoto e SIG foram usados para simular, na sequência, a ignição do fogo, a propagação do fogo e, por fim, o risco de incêndio florestal. A validação dos modelos de risco foi realizada pelo coeficiente Kappa (K). Os resultados mostraram que o modelo baseado no Histórico de Hot Points obteve maior precisão (0,61) do que o modelo gerado pelo método AHP (0,54). As coberturas de Cerrado, Campos Rupestres e Campo foram as mais suscetíveis aos incêndios florestais, por serem vegetações herbáceas e localizadas muito próximas a aglomerações urbanas e rodovias. As inclinações orientadas a Norte e Oeste foram importantes para a previsão de incêndios florestais e, por outro lado, a inclinação do terreno não foi importante para discretizar as áreas de maior e menor fragilidade ao referido distúrbio ecológico.Universidade Federal de Santa Maria2022-03-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontextoinfo:eu-repo/semantics/otherapplication/pdftext/xmlhttps://periodicos.ufsm.br/cienciaflorestal/article/view/6417110.5902/1980509864171Ciência Florestal; Vol. 32 No. 1 (2022); 451-473Ciência Florestal; v. 32 n. 1 (2022); 451-4731980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMenghttps://periodicos.ufsm.br/cienciaflorestal/article/view/64171/46367https://periodicos.ufsm.br/cienciaflorestal/article/view/64171/50707Copyright (c) 2022 Ciência Florestalhttps://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessLacerda, Heitor CarvalhoFaria, André Luiz LopesTorres, Fillipe Tamiozzo PereiraFonseca, Humberto PaivaSoares, Wesley OliveiraSilva, Marco Antônio Saraiva2023-03-20T12:03:55Zoai:ojs.pkp.sfu.ca:article/64171Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2023-03-20T12:03:55Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil Suscetibilidade a incêndios florestais em unidade de conservação localizada na região de transição dos Biomas Cerrado e Mata Atlântica, Brasil |
title |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil |
spellingShingle |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil Lacerda, Heitor Carvalho Rupestrian Fields GIS Multicriteria Analysis Campos Rupestres SIG Análise multicritério |
title_short |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil |
title_full |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil |
title_fullStr |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil |
title_full_unstemmed |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil |
title_sort |
Susceptibility to wildfire in a conservation unit located in the transition region of Cerrado and Atlantic Forest Biomes, Brazil |
author |
Lacerda, Heitor Carvalho |
author_facet |
Lacerda, Heitor Carvalho Faria, André Luiz Lopes Torres, Fillipe Tamiozzo Pereira Fonseca, Humberto Paiva Soares, Wesley Oliveira Silva, Marco Antônio Saraiva |
author_role |
author |
author2 |
Faria, André Luiz Lopes Torres, Fillipe Tamiozzo Pereira Fonseca, Humberto Paiva Soares, Wesley Oliveira Silva, Marco Antônio Saraiva |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Lacerda, Heitor Carvalho Faria, André Luiz Lopes Torres, Fillipe Tamiozzo Pereira Fonseca, Humberto Paiva Soares, Wesley Oliveira Silva, Marco Antônio Saraiva |
dc.subject.por.fl_str_mv |
Rupestrian Fields GIS Multicriteria Analysis Campos Rupestres SIG Análise multicritério |
topic |
Rupestrian Fields GIS Multicriteria Analysis Campos Rupestres SIG Análise multicritério |
description |
Created in 2014, the Serra da Gandarela National Park (SGNP), is repeatedly affected by wildfires. This Conservation Unit is located in the Iron Quadrangle (MG), in a transition zone between the Cerrado and the Atlantic Forest biomes, and is characterized by a complex mosaic of phytophysiognomies. The aim of this investigation was to compare the performance of two risk mapping models for forest fire in the SGNP and its surroundings, based on two different approaches, being one by multicriteria analysis, AHP method and the other a simple probability method, called Hot Spot History, which provided information on the areas of highest and lowest risk and their environmental and human characteristics. Spatial data from remote sensing and GIS were used to simulate, in sequence, the fire ignition, the fire spread and, finally, the risk of wildfire. The validation of the risk models was performed by the Kappa coefficient (K). The results showed that the model based on the History of Hot Points obtained greater accuracy (0.61) than the model generated by the AHP method (0.54). The Brazilian Savanna, Rupestrian Fields and Field coverings were the most susceptible to wildfire, as they are formed by herbaceous vegetations and are located very close to urban agglomerations and roads. The slopes oriented to the North and West were important for the prediction of wildfires slope and, on the other hand, the slope of the terrain was not important to discretize the areas of greater and lesser fragility to the referred ecological disturbance. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-25 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion texto info:eu-repo/semantics/other |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/64171 10.5902/1980509864171 |
url |
https://periodicos.ufsm.br/cienciaflorestal/article/view/64171 |
identifier_str_mv |
10.5902/1980509864171 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/64171/46367 https://periodicos.ufsm.br/cienciaflorestal/article/view/64171/50707 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Ciência Florestal https://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Ciência Florestal https://creativecommons.org/licenses/by-nc/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/xml |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Ciência Florestal; Vol. 32 No. 1 (2022); 451-473 Ciência Florestal; v. 32 n. 1 (2022); 451-473 1980-5098 0103-9954 reponame:Ciência Florestal (Online) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Ciência Florestal (Online) |
collection |
Ciência Florestal (Online) |
repository.name.fl_str_mv |
Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br |
_version_ |
1799944135880212480 |