Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems

P. 137-144

Detalles Bibliográficos
Autores: García Llamas, Paula, Suárez Seoane, Susana, Fernández Guisuraga, José Manuel, Fernández García, Víctor, Fernández Manso, Alfonso, Quintano Pastor, Carmen, Taboada Palomares, Ángela, Marcos Porras, Elena María, Calvo Galván, María Leonor
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/11248
Acceso en línea:https://www.sciencedirect.com/science/article/pii/S030324341930176X
http://hdl.handle.net/10612/11248
https://doi.org/10.1016/j.jag.2019.04.006
Access Level:acceso abierto
Palabra clave:Ecología. Medio ambiente
Composition burn index
Remote sensing
Thermal indices
Spectral indices
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spelling Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystemsGarcía Llamas, PaulaSuárez Seoane, SusanaFernández Guisuraga, José ManuelFernández García, VíctorFernández Manso, AlfonsoQuintano Pastor, CarmenTaboada Palomares, ÁngelaMarcos Porras, Elena MaríaCalvo Galván, María LeonorEcología. Medio ambienteComposition burn indexRemote sensingThermal indicesSpectral indicesP. 137-144The development of improved spatial and spectral resolution sensors provides new opportunities to assess burn severity more accurately. This study evaluates the ability of remote sensing indices derived from three remote sensing sensors (i.e., Landsat 8 OLI/TIRS, Sentinel-2 MSI and Deimos-1 SLIM-6-22) to assess burn severity (site, vegetation and soil burn severity). As a case study, we used a megafire (9,939 ha) that occurred in a Mediterranean ecosystem in northwestern Spain. Remote sensing indices included seven reflective, two thermal and four mixed indices, which were derived from each satellite and were validated with field burn severity metrics obtained from CBI index. Correlation patterns of field burn severity and remote sensing indices were relatively consistent across the different sensors. Additionally, regardless of the sensor, indices that incorporated SWIR bands (i.e., NBR-based indices), exceed those using red and NIR bands, and thermal and mixed indices. High resolution Sentinel-2 imagery only slightly improved the performance of indices based on NBR compared to Landsat 8. The dNDVI index from Landsat 8 and Sentinel-2 images showed relatively similar correlation values to NBR-based indices for site and soil burn severity, but showed limitations using Deimos-1. In general, mono-temporal and relativized indices better correlated with vegetation burn severity in heterogeneous systems than differenced indices. This study showed good potential for Landsat 8 OLI/TIRS and Sentinel-2 MSI for burn severity assessment in fire-prone heterogeneous ecosystems, although we highlight the need for further evaluation of Deimos-1 SLIM-6-22 in different fire scenarios, especially using bi-temporal indices.SIElsevierEcologiaFacultad de Ciencias Biologicas y Ambientales2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttps://www.sciencedirect.com/science/article/pii/S030324341930176Xhttp://hdl.handle.net/10612/11248https://doi.org/10.1016/j.jag.2019.04.006reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónInglésinfo:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/112482026-06-24T12:43:27Z
dc.title.none.fl_str_mv Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
title Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
spellingShingle Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
García Llamas, Paula
Ecología. Medio ambiente
Composition burn index
Remote sensing
Thermal indices
Spectral indices
title_short Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
title_full Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
title_fullStr Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
title_full_unstemmed Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
title_sort Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
dc.creator.none.fl_str_mv García Llamas, Paula
Suárez Seoane, Susana
Fernández Guisuraga, José Manuel
Fernández García, Víctor
Fernández Manso, Alfonso
Quintano Pastor, Carmen
Taboada Palomares, Ángela
Marcos Porras, Elena María
Calvo Galván, María Leonor
author García Llamas, Paula
author_facet García Llamas, Paula
Suárez Seoane, Susana
Fernández Guisuraga, José Manuel
Fernández García, Víctor
Fernández Manso, Alfonso
Quintano Pastor, Carmen
Taboada Palomares, Ángela
Marcos Porras, Elena María
Calvo Galván, María Leonor
author_role author
author2 Suárez Seoane, Susana
Fernández Guisuraga, José Manuel
Fernández García, Víctor
Fernández Manso, Alfonso
Quintano Pastor, Carmen
Taboada Palomares, Ángela
Marcos Porras, Elena María
Calvo Galván, María Leonor
author2_role author
author
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
Composition burn index
Remote sensing
Thermal indices
Spectral indices
topic Ecología. Medio ambiente
Composition burn index
Remote sensing
Thermal indices
Spectral indices
description P. 137-144
publishDate 2019
dc.date.none.fl_str_mv 2019
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://www.sciencedirect.com/science/article/pii/S030324341930176X
http://hdl.handle.net/10612/11248
https://doi.org/10.1016/j.jag.2019.04.006
url https://www.sciencedirect.com/science/article/pii/S030324341930176X
http://hdl.handle.net/10612/11248
https://doi.org/10.1016/j.jag.2019.04.006
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
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: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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