Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles

Artículo

Bibliographic Details
Authors: Beltrán Marcos, David, Suárez-Seoane, Susana, Fernández Guisuraga, José Manuel, Fernández García, Víctor, Pinto Prieto, Rayo, García Llamas, Paula, Calvo Galván, María Leonor
Format: article
Status:Published version
Publication Date:2021
Country:España
Institution:Universidad Rey Juan Carlos
Repository:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/12947
Online Access:https://www.mdpi.com/1999-4907/12/2/179/htm
http://hdl.handle.net/10612/12947
https://doi.org/10.3390/f12020179
Access Level:Open access
Keyword:Ecología. Medio ambiente
Ingeniería forestal
Ceniza
Suelo
Índices de agua
2417.13 Ecología Vegetal
2511.06 Conservación de Suelos
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spelling Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial VehiclesBeltrán Marcos, DavidSuárez-Seoane, SusanaFernández Guisuraga, José ManuelFernández García, VíctorPinto Prieto, RayoGarcía Llamas, PaulaCalvo Galván, María LeonorEcología. Medio ambienteIngeniería forestalCenizaSueloÍndices de agua2417.13 Ecología Vegetal2511.06 Conservación de SuelosArtículoThe evaluation of the effect of burn severity on forest soils is essential to determine the impact of wildfires on a range of key ecological processes, such as nutrient cycling and vegetation recovery. The main objective of this study was to assess the potentiality of different spectral products derived from RGB and multispectral imagery collected by unmanned aerial vehicles (UAVs) at very high spatial resolution for discriminating spatial variations in soil burn severity after a heterogeneous wildfire. In the case study, we chose a mixed-severity fire that occurred in the northwest (NW) of the Iberian Peninsula (Spain) in 2019 that affected 82.74 ha covered by three different types of forests, each dominated by Pinus pinaster, Pinus sylvestris, and Quercus pyrenaica. We evaluated soil burn severity in the field 1 month after the fire using the Composite Burn Soil Index (CBSI), as well as a pool of five individual indicators (ash depth, ash cover, fine debris cover, coarse debris cover, and unstructured soil depth) of easy interpretation. Simultaneously, we operated an unmanned aerial vehicle to obtain RGB and multispectral postfire images, allowing for deriving six spectral indices. Then, we explored the relationship between spectral indices and field soil burn severity metrics by means of univariate proportional odds regression models. These models were used to predict CBSI categories, and classifications were validated through confusion matrices. Results indicated that multispectral indices outperformed RGB indices when assessing soil burn severity, being more strongly related to CBSI than to individual indicators. The Normalized Difference Water Index (NDWI) was the best-performing spectral index for modelling CBSI (R2cv = 0.69), showing the best ability to predict CBSI categories (overall accuracy = 0.83). Among the individual indicators of soil burn severity, ash depth was the one that achieved the best results, specifically when it was modelled from NDWI (R2cv = 0.53). This work provides a useful background to design quick and accurate assessments of soil burn severity to be implemented immediately after the fire, which is a key factor to identify priority areas for emergency actions after forest fires.SIMDPIEcologiaFacultad de Ciencias Biologicas y Ambientales2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://www.mdpi.com/1999-4907/12/2/179/htmhttp://hdl.handle.net/10612/12947https://doi.org/10.3390/f12020179reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad Rey Juan CarlosIngléshttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/129472026-06-24T12:43:27Z
dc.title.none.fl_str_mv Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
title Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
spellingShingle Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
Beltrán Marcos, David
Ecología. Medio ambiente
Ingeniería forestal
Ceniza
Suelo
Índices de agua
2417.13 Ecología Vegetal
2511.06 Conservación de Suelos
title_short Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
title_full Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
title_fullStr Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
title_full_unstemmed Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
title_sort Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles
dc.creator.none.fl_str_mv Beltrán Marcos, David
Suárez-Seoane, Susana
Fernández Guisuraga, José Manuel
Fernández García, Víctor
Pinto Prieto, Rayo
García Llamas, Paula
Calvo Galván, María Leonor
author Beltrán Marcos, David
author_facet Beltrán Marcos, David
Suárez-Seoane, Susana
Fernández Guisuraga, José Manuel
Fernández García, Víctor
Pinto Prieto, Rayo
García Llamas, Paula
Calvo Galván, María Leonor
author_role author
author2 Suárez-Seoane, Susana
Fernández Guisuraga, José Manuel
Fernández García, Víctor
Pinto Prieto, Rayo
García Llamas, Paula
Calvo Galván, María Leonor
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Ecologia
Facultad de Ciencias Biologicas y Ambientales
dc.subject.none.fl_str_mv Ecología. Medio ambiente
Ingeniería forestal
Ceniza
Suelo
Índices de agua
2417.13 Ecología Vegetal
2511.06 Conservación de Suelos
topic Ecología. Medio ambiente
Ingeniería forestal
Ceniza
Suelo
Índices de agua
2417.13 Ecología Vegetal
2511.06 Conservación de Suelos
description Artículo
publishDate 2021
dc.date.none.fl_str_mv 2021
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.mdpi.com/1999-4907/12/2/179/htm
http://hdl.handle.net/10612/12947
https://doi.org/10.3390/f12020179
url https://www.mdpi.com/1999-4907/12/2/179/htm
http://hdl.handle.net/10612/12947
https://doi.org/10.3390/f12020179
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad Rey Juan Carlos
instname_str Universidad Rey Juan Carlos
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 15.301603

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