A Bayesian spatio-temporal analysis of forest fires in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/10427 |
Resumo: | In the last decade, forest fires have become a natural disaster in Portugal, causing great forest devastation, leading to both economic and environmental losses and putting at risk populations and the livelihoods of the forest itself. In this work, we present Bayesian hierarchical models to analyze spatio-temporal fire data on the proportion of burned area in Portugal, by municipalities and over three decades. Mixture of distributions was employed to model jointly the proportion of area burned and the excess of no burned area for early years. For getting estimates of the model parameters, we used Monte Carlo Markov chain methods. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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A Bayesian spatio-temporal analysis of forest fires in PortugalForest firesSpatio-temporal dataBayesian analysisIn the last decade, forest fires have become a natural disaster in Portugal, causing great forest devastation, leading to both economic and environmental losses and putting at risk populations and the livelihoods of the forest itself. In this work, we present Bayesian hierarchical models to analyze spatio-temporal fire data on the proportion of burned area in Portugal, by municipalities and over three decades. Mixture of distributions was employed to model jointly the proportion of area burned and the excess of no burned area for early years. For getting estimates of the model parameters, we used Monte Carlo Markov chain methods.2014-01-30T14:27:16Z2014-01-302012-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/10427http://hdl.handle.net/10174/10427engSilva, G.L. and Dias M.I. (2012). A Bayesian spatio-temporal analysis of forest fires in Portugal. In Proceedings of XXII Simposio Internacional de Estadística, Bucaramanga - Colombia, September 17-21, 2012ndmisd@uevora.ptProceedings of XXII Simposio Internacional de Estadística336Silva, Giovani LoiolaDias, Maria inêsinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T18:53:11Zoai:dspace.uevora.pt:10174/10427Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:04:16.355996Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
title |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
spellingShingle |
A Bayesian spatio-temporal analysis of forest fires in Portugal Silva, Giovani Loiola Forest fires Spatio-temporal data Bayesian analysis |
title_short |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
title_full |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
title_fullStr |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
title_full_unstemmed |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
title_sort |
A Bayesian spatio-temporal analysis of forest fires in Portugal |
author |
Silva, Giovani Loiola |
author_facet |
Silva, Giovani Loiola Dias, Maria inês |
author_role |
author |
author2 |
Dias, Maria inês |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Silva, Giovani Loiola Dias, Maria inês |
dc.subject.por.fl_str_mv |
Forest fires Spatio-temporal data Bayesian analysis |
topic |
Forest fires Spatio-temporal data Bayesian analysis |
description |
In the last decade, forest fires have become a natural disaster in Portugal, causing great forest devastation, leading to both economic and environmental losses and putting at risk populations and the livelihoods of the forest itself. In this work, we present Bayesian hierarchical models to analyze spatio-temporal fire data on the proportion of burned area in Portugal, by municipalities and over three decades. Mixture of distributions was employed to model jointly the proportion of area burned and the excess of no burned area for early years. For getting estimates of the model parameters, we used Monte Carlo Markov chain methods. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-01-01T00:00:00Z 2014-01-30T14:27:16Z 2014-01-30 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/10427 http://hdl.handle.net/10174/10427 |
url |
http://hdl.handle.net/10174/10427 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Silva, G.L. and Dias M.I. (2012). A Bayesian spatio-temporal analysis of forest fires in Portugal. In Proceedings of XXII Simposio Internacional de Estadística, Bucaramanga - Colombia, September 17-21, 2012 nd misd@uevora.pt Proceedings of XXII Simposio Internacional de Estadística 336 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799136527153889280 |