Cargando…

Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests

In this study we combine information from aerial LIDAR and hemispherical images taken in the field with ForeStereo—a forest inventory device—to assess the vulnerability and to design conservation strategies for endangered Mediterranean fir forests based on the mapping of fire risk and canopy structu...

Descripción completa

Detalles Bibliográficos
Autores principales: Cortés-Molino, Álvaro, Aulló-Maestro, Isabel, Fernandez-Luque, Ismael, Flores-Moya, Antonio, Carreira, José A., Salvo, A. Enrique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585724/
https://www.ncbi.nlm.nih.gov/pubmed/33150077
http://dx.doi.org/10.7717/peerj.10158
_version_ 1783599849061482496
author Cortés-Molino, Álvaro
Aulló-Maestro, Isabel
Fernandez-Luque, Ismael
Flores-Moya, Antonio
Carreira, José A.
Salvo, A. Enrique
author_facet Cortés-Molino, Álvaro
Aulló-Maestro, Isabel
Fernandez-Luque, Ismael
Flores-Moya, Antonio
Carreira, José A.
Salvo, A. Enrique
author_sort Cortés-Molino, Álvaro
collection PubMed
description In this study we combine information from aerial LIDAR and hemispherical images taken in the field with ForeStereo—a forest inventory device—to assess the vulnerability and to design conservation strategies for endangered Mediterranean fir forests based on the mapping of fire risk and canopy structure spatial variability. We focused on the largest continuous remnant population of the endangered tree species Abies pinsapo Boiss. spanning 252 ha in Sierra de las Nieves National Park (South Andalusia, Spain). We established 49 sampling plots over the study area. Stand structure variables were derived from ForeStereo device, a proximal sensing technology for tree diameter, height and crown dimensions and stand crown cover and basal area retrieval from stereoscopic hemispherical images photogrammetry. With this information, we developed regression models with airborne LIDAR data (spatial resolution of 0.5 points∙m(−2)). Thereafter, six fuel models were fitted to the plots according to the UCO40 classification criteria, and then the entire area was classified using the Nearest Neighbor algorithm on Sentinel imagery (overall accuracy of 0.56 and a KIA-Kappa Coefficient of 0.46). FlamMap software was used for fire simulation scenarios based on fuel models, stand structure, and terrain data. Besides the fire simulation, we analyzed canopy structure to assess the status and vulnerability of this fir population. The assessment shows a secondary growth forest that has an increasing presence of fuel models with the potential for high fire spread rate fire and burn probability. Our methodological approach has the potential to be integrated as a support tool for the adaptive management and conservation of A. pinsapo across its whole distribution area (<4,000 ha), as well as for other endangered circum-Mediterranean fir forests, as A. numidica de Lannoy and A. pinsapo marocana Trab. in North Africa.
format Online
Article
Text
id pubmed-7585724
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-75857242020-11-03 Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests Cortés-Molino, Álvaro Aulló-Maestro, Isabel Fernandez-Luque, Ismael Flores-Moya, Antonio Carreira, José A. Salvo, A. Enrique PeerJ Ecosystem Science In this study we combine information from aerial LIDAR and hemispherical images taken in the field with ForeStereo—a forest inventory device—to assess the vulnerability and to design conservation strategies for endangered Mediterranean fir forests based on the mapping of fire risk and canopy structure spatial variability. We focused on the largest continuous remnant population of the endangered tree species Abies pinsapo Boiss. spanning 252 ha in Sierra de las Nieves National Park (South Andalusia, Spain). We established 49 sampling plots over the study area. Stand structure variables were derived from ForeStereo device, a proximal sensing technology for tree diameter, height and crown dimensions and stand crown cover and basal area retrieval from stereoscopic hemispherical images photogrammetry. With this information, we developed regression models with airborne LIDAR data (spatial resolution of 0.5 points∙m(−2)). Thereafter, six fuel models were fitted to the plots according to the UCO40 classification criteria, and then the entire area was classified using the Nearest Neighbor algorithm on Sentinel imagery (overall accuracy of 0.56 and a KIA-Kappa Coefficient of 0.46). FlamMap software was used for fire simulation scenarios based on fuel models, stand structure, and terrain data. Besides the fire simulation, we analyzed canopy structure to assess the status and vulnerability of this fir population. The assessment shows a secondary growth forest that has an increasing presence of fuel models with the potential for high fire spread rate fire and burn probability. Our methodological approach has the potential to be integrated as a support tool for the adaptive management and conservation of A. pinsapo across its whole distribution area (<4,000 ha), as well as for other endangered circum-Mediterranean fir forests, as A. numidica de Lannoy and A. pinsapo marocana Trab. in North Africa. PeerJ Inc. 2020-10-22 /pmc/articles/PMC7585724/ /pubmed/33150077 http://dx.doi.org/10.7717/peerj.10158 Text en © 2020 Cortés-Molino et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Ecosystem Science
Cortés-Molino, Álvaro
Aulló-Maestro, Isabel
Fernandez-Luque, Ismael
Flores-Moya, Antonio
Carreira, José A.
Salvo, A. Enrique
Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests
title Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests
title_full Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests
title_fullStr Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests
title_full_unstemmed Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests
title_short Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests
title_sort using forestereo and lidar data to assess fire and canopy structure-related risks in relict abies pinsapo boiss. forests
topic Ecosystem Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585724/
https://www.ncbi.nlm.nih.gov/pubmed/33150077
http://dx.doi.org/10.7717/peerj.10158
work_keys_str_mv AT cortesmolinoalvaro usingforestereoandlidardatatoassessfireandcanopystructurerelatedrisksinrelictabiespinsapoboissforests
AT aullomaestroisabel usingforestereoandlidardatatoassessfireandcanopystructurerelatedrisksinrelictabiespinsapoboissforests
AT fernandezluqueismael usingforestereoandlidardatatoassessfireandcanopystructurerelatedrisksinrelictabiespinsapoboissforests
AT floresmoyaantonio usingforestereoandlidardatatoassessfireandcanopystructurerelatedrisksinrelictabiespinsapoboissforests
AT carreirajosea usingforestereoandlidardatatoassessfireandcanopystructurerelatedrisksinrelictabiespinsapoboissforests
AT salvoaenrique usingforestereoandlidardatatoassessfireandcanopystructurerelatedrisksinrelictabiespinsapoboissforests