Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression

Detalhes bibliográficos
Autor(a) principal: Oliveira, Sandra
Data de Publicação: 2014
Outros Autores: Pereira, José M.C., San-Miguel-Ayanz, Jesús, Lourenço, Luciano Fernandes
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/88954
https://doi.org/10.1016/j.apgeog.2014.04.002
Resumo: The spatial patterns of fire occurrence were analyzed in two regions of Southern Europe, focusing on the long-term factors that influence fire distribution. The relationship between fire occurrence and the physical and anthropogenic variables collected was investigated with Geographically Weighted Regression (GWR) and the results were compared with Ordinary Least Squares (OLS). Local patterns of the significant variables were explored and a strong spatial variability of their explanatory power was revealed. Climate (precipitation), livestock and land cover (shrubland) were found to be significant in both regions, although in particular areas and to different extents. Regarding model performance, GWR showed an improvement over OLS in both regions. The investigation of the spatial variation in the importance of the main drivers over a broad study area, gives a valuable contribution to the improvement of fire management and prevention strategies, adjusted to the particular conditions of different areas.
id RCAP_dd4db3f3268ab8f96543bfd7e41c358a
oai_identifier_str oai:estudogeral.uc.pt:10316/88954
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted RegressionFire densitySpatial patternsDriving factorsSouth European regionsGeographically Weighted RegressionThe spatial patterns of fire occurrence were analyzed in two regions of Southern Europe, focusing on the long-term factors that influence fire distribution. The relationship between fire occurrence and the physical and anthropogenic variables collected was investigated with Geographically Weighted Regression (GWR) and the results were compared with Ordinary Least Squares (OLS). Local patterns of the significant variables were explored and a strong spatial variability of their explanatory power was revealed. Climate (precipitation), livestock and land cover (shrubland) were found to be significant in both regions, although in particular areas and to different extents. Regarding model performance, GWR showed an improvement over OLS in both regions. The investigation of the spatial variation in the importance of the main drivers over a broad study area, gives a valuable contribution to the improvement of fire management and prevention strategies, adjusted to the particular conditions of different areas.Elsevier2014-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/88954http://hdl.handle.net/10316/88954https://doi.org/10.1016/j.apgeog.2014.04.002eng01436228https://www.sciencedirect.com/science/article/pii/S0143622814000630?via%3DihubOliveira, SandraPereira, José M.C.San-Miguel-Ayanz, JesúsLourenço, Luciano Fernandesinfo: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:RCAAP2023-10-13T10:02:53Zoai:estudogeral.uc.pt:10316/88954Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:09:25.004914Repositório 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 Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
title Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
spellingShingle Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
Oliveira, Sandra
Fire density
Spatial patterns
Driving factors
South European regions
Geographically Weighted Regression
title_short Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
title_full Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
title_fullStr Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
title_full_unstemmed Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
title_sort Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression
author Oliveira, Sandra
author_facet Oliveira, Sandra
Pereira, José M.C.
San-Miguel-Ayanz, Jesús
Lourenço, Luciano Fernandes
author_role author
author2 Pereira, José M.C.
San-Miguel-Ayanz, Jesús
Lourenço, Luciano Fernandes
author2_role author
author
author
dc.contributor.author.fl_str_mv Oliveira, Sandra
Pereira, José M.C.
San-Miguel-Ayanz, Jesús
Lourenço, Luciano Fernandes
dc.subject.por.fl_str_mv Fire density
Spatial patterns
Driving factors
South European regions
Geographically Weighted Regression
topic Fire density
Spatial patterns
Driving factors
South European regions
Geographically Weighted Regression
description The spatial patterns of fire occurrence were analyzed in two regions of Southern Europe, focusing on the long-term factors that influence fire distribution. The relationship between fire occurrence and the physical and anthropogenic variables collected was investigated with Geographically Weighted Regression (GWR) and the results were compared with Ordinary Least Squares (OLS). Local patterns of the significant variables were explored and a strong spatial variability of their explanatory power was revealed. Climate (precipitation), livestock and land cover (shrubland) were found to be significant in both regions, although in particular areas and to different extents. Regarding model performance, GWR showed an improvement over OLS in both regions. The investigation of the spatial variation in the importance of the main drivers over a broad study area, gives a valuable contribution to the improvement of fire management and prevention strategies, adjusted to the particular conditions of different areas.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
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/10316/88954
http://hdl.handle.net/10316/88954
https://doi.org/10.1016/j.apgeog.2014.04.002
url http://hdl.handle.net/10316/88954
https://doi.org/10.1016/j.apgeog.2014.04.002
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 01436228
https://www.sciencedirect.com/science/article/pii/S0143622814000630?via%3Dihub
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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
_version_ 1799133988104699904