Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest

Wildfires play a major role in driving vegetation changes and can cause important environmental and economic losses in Mediterranean forests, especially where the dominant species lacks efficient postfire regeneration mechanisms. In these areas, postdisturbance vegetation management strategies need...

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Autores: Martín Alcón, Santiago, Coll Mir, Lluís, De Cáceres, Miquel, Guitart i Xarpell, Lídia, Cabré, Mariló, Just, Ariadna, González-Olabarria, José Ramón
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2015
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/68974
Acceso en línea:https://doi.org/10.1139/cjfr-2014-0430
http://hdl.handle.net/10459.1/68974
Access Level:acceso abierto
Palabra clave:Postfire regeneration types
Remote sensing data
Wildfire effects
Postdisturbance management
Pinus nigra
id ES_833886dbb2bb60896ce4e09e9ab732cd
oai_identifier_str oai:repositori.udl.cat:10459.1/68974
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
title Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
spellingShingle Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
Martín Alcón, Santiago
Postfire regeneration types
Remote sensing data
Wildfire effects
Postdisturbance management
Pinus nigra
title_short Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
title_full Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
title_fullStr Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
title_full_unstemmed Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
title_sort Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest
dc.creator.none.fl_str_mv Martín Alcón, Santiago
Coll Mir, Lluís
De Cáceres, Miquel
Guitart i Xarpell, Lídia
Cabré, Mariló
Just, Ariadna
González-Olabarria, José Ramón
author Martín Alcón, Santiago
author_facet Martín Alcón, Santiago
Coll Mir, Lluís
De Cáceres, Miquel
Guitart i Xarpell, Lídia
Cabré, Mariló
Just, Ariadna
González-Olabarria, José Ramón
author_role author
author2 Coll Mir, Lluís
De Cáceres, Miquel
Guitart i Xarpell, Lídia
Cabré, Mariló
Just, Ariadna
González-Olabarria, José Ramón
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Postfire regeneration types
Remote sensing data
Wildfire effects
Postdisturbance management
Pinus nigra
topic Postfire regeneration types
Remote sensing data
Wildfire effects
Postdisturbance management
Pinus nigra
description Wildfires play a major role in driving vegetation changes and can cause important environmental and economic losses in Mediterranean forests, especially where the dominant species lacks efficient postfire regeneration mechanisms. In these areas, postdisturbance vegetation management strategies need to be based on detailed, spatially continuous inventories of the burned area. Here, we present a methodology in which we combine airborne LiDAR and multispectral imagery to assess postfire regeneration types in a spatially continuous way, using a Mediterranean black pine (Pinus nigra Arn ssp. salzmannii) forest that burned in 1998 as a case study. Five postfire regeneration types were obtained by clustering field-plot data using Ward’s method. Two of the five regeneration types presented high tree cover (one clearly dominated by hardwoods and the other dominated by pines), a third type presented low to moderate tree cover, being dominated by hardwoods, and the remaining two types matched to areas dominated by soil–herbaceous or shrub layers with very low or no tree cover (i.e., very low to no tree species regeneration). These five types of regeneration were used to conduct a supervised classification of remote sensing data using a nonparametric supervised classification technique. Compared with independent field validation points, the remote sensing based assessment method resulted in a global classification accuracy of 82.7%. Proportions of regeneration types in the study area indicated a general shift from the former pine-dominated forest toward hardwood dominance and showed no serious problems of regeneration failure. Our methodological approach appears to be appropriate for informing postdisturbance vegetation management strategies over large areas.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1139/cjfr-2014-0430
http://hdl.handle.net/10459.1/68974
url https://doi.org/10.1139/cjfr-2014-0430
http://hdl.handle.net/10459.1/68974
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MINECO//AGL2012-40039-C02-01
Versió postprint del document publicat a: https://doi.org/10.1139/cjfr-2014-0430
Canadian Journal of Forest Research, 2015, vol. 45, núm. 7, p. 856-866
dc.rights.none.fl_str_mv (c) Canadian Science Publishing, 2015
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Canadian Science Publishing, 2015
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv NRC Research Press (Canadian Science Publishing)
publisher.none.fl_str_mv NRC Research Press (Canadian Science Publishing)
dc.source.none.fl_str_mv reponame:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
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spelling Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forestMartín Alcón, SantiagoColl Mir, LluísDe Cáceres, MiquelGuitart i Xarpell, LídiaCabré, MarilóJust, AriadnaGonzález-Olabarria, José RamónPostfire regeneration typesRemote sensing dataWildfire effectsPostdisturbance managementPinus nigraWildfires play a major role in driving vegetation changes and can cause important environmental and economic losses in Mediterranean forests, especially where the dominant species lacks efficient postfire regeneration mechanisms. In these areas, postdisturbance vegetation management strategies need to be based on detailed, spatially continuous inventories of the burned area. Here, we present a methodology in which we combine airborne LiDAR and multispectral imagery to assess postfire regeneration types in a spatially continuous way, using a Mediterranean black pine (Pinus nigra Arn ssp. salzmannii) forest that burned in 1998 as a case study. Five postfire regeneration types were obtained by clustering field-plot data using Ward’s method. Two of the five regeneration types presented high tree cover (one clearly dominated by hardwoods and the other dominated by pines), a third type presented low to moderate tree cover, being dominated by hardwoods, and the remaining two types matched to areas dominated by soil–herbaceous or shrub layers with very low or no tree cover (i.e., very low to no tree species regeneration). These five types of regeneration were used to conduct a supervised classification of remote sensing data using a nonparametric supervised classification technique. Compared with independent field validation points, the remote sensing based assessment method resulted in a global classification accuracy of 82.7%. Proportions of regeneration types in the study area indicated a general shift from the former pine-dominated forest toward hardwood dominance and showed no serious problems of regeneration failure. Our methodological approach appears to be appropriate for informing postdisturbance vegetation management strategies over large areas.Les feux de forêt jouent un rôle déterminant dans la composition de la végétation et peuvent causer d’importantes pertes économiques et environnementales dans les forêts méditerranéennes, particulièrement dans les endroits où les espèces dominantes n’ont pas de mécanismes efficaces de régénération après feu. Dans ces endroits, les stratégies de gestion de la végétation après feu doivent être fondées sur des inventaires détaillés et continus dans l’espace des zones brûlées. Nous présentons ici une méthodologie qui combine le lidar aéroporté et l’imagerie multispectrale pour évaluer les types de régénération après feu de manière continue dans l’espace, en utilisant comme étude de cas une forêt de pin de Salzmann (Pinus nigra Arn. ssp. salzmannii) qui a brûlé en 1998. Cinq types de régénération après feu ont été obtenus en regroupant les données de placettes sur le terrain à l’aide de la méthode de Ward. Deux des cinq types de régénération avaient une fort couvert d’espèces arborescentes dominé dans un cas par des feuillus et dans l’autre par des pins; un troisième type avait un couvert arboré faible à modéré dominé par des feuillus; les deux derniers types correspondaient aux régions dominées par des strates herbacées ou arbustives où la régénération arborescente était très faible ou inexistante. Ces cinq classes ont été utilisées pour effectuer une classification dirigée des données de télédétection à l’aide d’une technique de classification dirigée non paramétrique. Comparativement à des points de contrôle indépendants sur le terrain, la classification de la méthode d’évaluation fondée sur la télédétection avait une précision globale de 82,7 %. La proportion des types de régénération dans la zone d’étude indiquait qu’il y avait une évolution générale de la forêt jadis dominée par les pins vers une dominance des feuillus et ne révélait aucun problème sérieux de régénération. Notre approche méthodologique semble appropriée pour appuyer les stratégies de gestion de la végétation à la suite d’une perturbation sur de vastes superficies.This research was primarily supported by the Spanish Ministry of Science and Innovation via the RESILFOR project (AGL2012-40039-C02-01). It also was part of a cooperative agreement between the Forest Sciences Center of Catalonia and the Institut Cartogràfic i Geològic de Catalunya aimed at using aerial RS data for forest characterization. The Catalan Agency for Management of University and Research Grants provided S.M.A. with support through a “predoctoral” grant (FI-DGR), and the Spanish Ministry of Science and Innovation provided L.C., J.R.G., and M.C. with support through postdoctoral “Ramon y Cajal” contracts.NRC Research Press (Canadian Science Publishing)2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttps://doi.org/10.1139/cjfr-2014-0430http://hdl.handle.net/10459.1/68974reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)Inglésinfo:eu-repo/grantAgreement/MINECO//AGL2012-40039-C02-01Versió postprint del document publicat a: https://doi.org/10.1139/cjfr-2014-0430Canadian Journal of Forest Research, 2015, vol. 45, núm. 7, p. 856-866(c) Canadian Science Publishing, 2015info:eu-repo/semantics/openAccessoai:repositori.udl.cat:10459.1/689742026-06-24T12:42:17Z
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