Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest

[EN] This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [S...

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Detalhes bibliográficos
Autores: Guerra Hernández, Juan, Görgens, Eric Bastos, García Gutiérrez, Jorge, Rodríguez, Luis Carlos Estraviz, Tomé, Margarida, González Ferreiro, Eduardo Manuel
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Recursos:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/22718
Acesso em linha:https://www.tandfonline.com/doi/abs/10.5721/EuJRS20164911
https://hdl.handle.net/10612/22718
Access Level:acceso abierto
Palavra-chave:Ingeniería forestal
Topografía
Biomass components
Remote sensing
Airborne laser scanning
Mediterranean forest
Feature selection approaches
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spelling Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forestGuerra Hernández, JuanGörgens, Eric BastosGarcía Gutiérrez, JorgeRodríguez, Luis Carlos EstravizTomé, MargaridaGonzález Ferreiro, Eduardo ManuelIngeniería forestalTopografíaBiomass componentsRemote sensingAirborne laser scanningMediterranean forestFeature selection approaches[EN] This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most casesSITaylor & FrancisIngeniería Cartografica, Geodesica y FotogrametriaEscuela Superior y Tecnica de Ingenieros de Minas2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://www.tandfonline.com/doi/abs/10.5721/EuJRS20164911https://hdl.handle.net/10612/22718reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónIngléshttp://creativecommons.org/licenses/by-nd/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/227182026-06-24T12:43:27Z
dc.title.none.fl_str_mv Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
title Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
spellingShingle Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
Guerra Hernández, Juan
Ingeniería forestal
Topografía
Biomass components
Remote sensing
Airborne laser scanning
Mediterranean forest
Feature selection approaches
title_short Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
title_full Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
title_fullStr Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
title_full_unstemmed Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
title_sort Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
dc.creator.none.fl_str_mv Guerra Hernández, Juan
Görgens, Eric Bastos
García Gutiérrez, Jorge
Rodríguez, Luis Carlos Estraviz
Tomé, Margarida
González Ferreiro, Eduardo Manuel
author Guerra Hernández, Juan
author_facet Guerra Hernández, Juan
Görgens, Eric Bastos
García Gutiérrez, Jorge
Rodríguez, Luis Carlos Estraviz
Tomé, Margarida
González Ferreiro, Eduardo Manuel
author_role author
author2 Görgens, Eric Bastos
García Gutiérrez, Jorge
Rodríguez, Luis Carlos Estraviz
Tomé, Margarida
González Ferreiro, Eduardo Manuel
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Ingeniería Cartografica, Geodesica y Fotogrametria
Escuela Superior y Tecnica de Ingenieros de Minas
dc.subject.none.fl_str_mv Ingeniería forestal
Topografía
Biomass components
Remote sensing
Airborne laser scanning
Mediterranean forest
Feature selection approaches
topic Ingeniería forestal
Topografía
Biomass components
Remote sensing
Airborne laser scanning
Mediterranean forest
Feature selection approaches
description [EN] This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.tandfonline.com/doi/abs/10.5721/EuJRS20164911
https://hdl.handle.net/10612/22718
url https://www.tandfonline.com/doi/abs/10.5721/EuJRS20164911
https://hdl.handle.net/10612/22718
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad de León
instname_str Universidad de León
reponame_str BULERIA. Repositorio Institucional de la Universidad de León
collection BULERIA. Repositorio Institucional de la Universidad de León
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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