Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity

12 páginas, 1 tabla, 7 figuras.

Detalles Bibliográficos
Autores: Novo Gómez, Ana, Fernández Filgueira, Cristina, Míguez, Clara, Suárez-Vidal, Estefanía
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/373930
Acceso en línea:http://hdl.handle.net/10261/373930
Access Level:acceso abierto
Palabra clave:Potential soil loss
Fire severity
Spatial analysis
Remote sensing
Soil burn severity
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spelling Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severityNovo Gómez, AnaFernández Filgueira, CristinaMíguez, ClaraSuárez-Vidal, EstefaníaPotential soil lossFire severitySpatial analysisRemote sensingSoil burn severity12 páginas, 1 tabla, 7 figuras.The area burned in Spain exceeded historical records in 2022, when exceptionally warm conditions influenced wildfire events. The predicted intensification of wildfire regimes includes an increase in frequency, severity, and size. Therefore, a study of the wildfires that occurred in 2022 is necessary to understand their behaviour and possible environmental impacts. The objective of this study is to analyse the applicability of using spectral indices and Geographic Information System (GIS) approaches to map the spatial distribution and estimate potential soil losses using Sentinel-2 imagery and fire severity field data. Soil losses were estimated using an empirical model based on soil burn severity data collected in the field after wildfire. The relationship between the Normalized Difference Infrared Index (NDII), Difference Normalized Wildfire Ash Index (dNWAI), and the Blue Normalized Difference Vegetation Index (BNDVI) with the estimated soil losses was then evaluated. In addition, the influence of different time scales of the satellite images was analysed. The first period considered (Date I) ranges from 8 to 20 days after the beginning of the wildfire, which coincides with the field data collection. The second period considered (Date II) ranges from 28 to 35 days after the start of the wildfire. The results obtained showed a significant dependence relationship between the BNDVI index (using satellite images of Date I) and the estimated soil losses (R2 = 0.756), while the results of the NDII (R2 = 0.31) and dNWAI (R2 = 0.061), showed no spatial relationship with the estimated soil losses. Three of the largest wildfires in 2022 in Spain were analysed, and the results showed strong correlations of BNDVI index for Folgoso do Courel (R2 = 0.808), for Carballeda de Valedorras (R2 = 0.906), and for Sierra de la Culebra (R2 = 0.939). In addition, these results allowed the mapping and quantification of potential soil losses in areas where fire severity was high, totalling ∼2,50,000 Mg ha−1 in Folgoso do Courel, ∼3,70,000 Mg ha−1 in Carballeda de Valdeorras, and ∼4,70,000 Mg ha−1 in Sierra de la Culebra. Moreover, BNDVI values for estimating soil loss vary by vegetation type, and there is a positive correlation between severity classes and the BNDVI index. This approach can inform post-fire land management decisions in future wildfires and could be applied to other regions.This research was funded by the Spanish Research Agency of the Spanish Ministry of Science and Innovation through project ENFIRES-NW, PID2020-116494RR-C42.ElsevierAgencia Estatal de Investigación (España)Ministerio de Ciencia e Innovación (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2024202420242024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/373930reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116494RR-C42http://dx.doi.org/10.1016/j.ecoinf.2024.102793Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3739302026-05-22T06:33:51Z
dc.title.none.fl_str_mv Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
title Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
spellingShingle Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
Novo Gómez, Ana
Potential soil loss
Fire severity
Spatial analysis
Remote sensing
Soil burn severity
title_short Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
title_full Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
title_fullStr Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
title_full_unstemmed Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
title_sort Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity
dc.creator.none.fl_str_mv Novo Gómez, Ana
Fernández Filgueira, Cristina
Míguez, Clara
Suárez-Vidal, Estefanía
author Novo Gómez, Ana
author_facet Novo Gómez, Ana
Fernández Filgueira, Cristina
Míguez, Clara
Suárez-Vidal, Estefanía
author_role author
author2 Fernández Filgueira, Cristina
Míguez, Clara
Suárez-Vidal, Estefanía
author2_role author
author
author
dc.contributor.none.fl_str_mv Agencia Estatal de Investigación (España)
Ministerio de Ciencia e Innovación (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Potential soil loss
Fire severity
Spatial analysis
Remote sensing
Soil burn severity
topic Potential soil loss
Fire severity
Spatial analysis
Remote sensing
Soil burn severity
description 12 páginas, 1 tabla, 7 figuras.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/373930
url http://hdl.handle.net/10261/373930
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116494RR-C42
http://dx.doi.org/10.1016/j.ecoinf.2024.102793
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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