Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data

The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require a...

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Autores: González Ferreiro, Eduardo, Arellano Pérez, Stéfano, Castedo Dorado, Fernando, Hevia Cabal, Andrea, Vega, José Antonio, Vega-Nieva, Daniel Jose, Álvarez González, Juan Gabriel, Ruiz González, Ana Daría
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/15627
Acceso en línea:http://hdl.handle.net/10347/15627
Access Level:acceso abierto
Palabra clave:Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310604 Ordenación de montes
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310606 Protección
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310608 Silvicultura
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spelling Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning dataGonzález Ferreiro, EduardoArellano Pérez, StéfanoCastedo Dorado, FernandoHevia Cabal, AndreaVega, José AntonioVega-Nieva, Daniel JoseÁlvarez González, Juan GabrielRuiz González, Ana DaríaMaterias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310604 Ordenación de montesMaterias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310606 ProtecciónMaterias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310608 SilviculturaThe fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus lowdensity airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.Public Library of ScienceUniversidade de Santiago de Compostela. Departamento de Enxeñaría AgroforestalÁrea de Enxeñaría e Arquitectura20172017-04-2720172017-04-27journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10347/15627reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostelainstname:Universidad de Santiago de Compostela (USC)InglésengEuropean Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 633464open accesshttp://purl.org/coar/access_right/c_abf2© 2017 González-Ferreiro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:minerva.usc.gal:10347/156272026-06-15T12:47:27Z
dc.title.none.fl_str_mv Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
title Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
spellingShingle Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
González Ferreiro, Eduardo
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310604 Ordenación de montes
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310606 Protección
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310608 Silvicultura
title_short Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
title_full Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
title_fullStr Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
title_full_unstemmed Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
title_sort Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
dc.creator.none.fl_str_mv González Ferreiro, Eduardo
Arellano Pérez, Stéfano
Castedo Dorado, Fernando
Hevia Cabal, Andrea
Vega, José Antonio
Vega-Nieva, Daniel Jose
Álvarez González, Juan Gabriel
Ruiz González, Ana Daría
author González Ferreiro, Eduardo
author_facet González Ferreiro, Eduardo
Arellano Pérez, Stéfano
Castedo Dorado, Fernando
Hevia Cabal, Andrea
Vega, José Antonio
Vega-Nieva, Daniel Jose
Álvarez González, Juan Gabriel
Ruiz González, Ana Daría
author_role author
author2 Arellano Pérez, Stéfano
Castedo Dorado, Fernando
Hevia Cabal, Andrea
Vega, José Antonio
Vega-Nieva, Daniel Jose
Álvarez González, Juan Gabriel
Ruiz González, Ana Daría
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade de Santiago de Compostela. Departamento de Enxeñaría Agroforestal
Área de Enxeñaría e Arquitectura
dc.subject.none.fl_str_mv Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310604 Ordenación de montes
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310606 Protección
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310608 Silvicultura
topic Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310604 Ordenación de montes
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310606 Protección
Materias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310608 Silvicultura
description The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus lowdensity airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-04-27
2017
2017-04-27
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10347/15627
url http://hdl.handle.net/10347/15627
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 633464
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname:Universidad de Santiago de Compostela (USC)
instname_str Universidad de Santiago de Compostela (USC)
reponame_str Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
collection Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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