Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain

Autores
Garzo, Pedro Andrés; Fernández Montblanc, Tomás
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The high exposure of coastal areas worldwide to natural and anthropogenic disasters emphasizes the relevance of disaster management processes that ensure a prompt damage detection and identification of affected areas. This paper aimed to develop a novel approach for disaster monitoring in coastal areas using SAR data. The method was based on an interferometric coherence difference analysis of Sentinel 1 data. To calibrate and validate the method, the Emma Storm, a severe coastal storm that affected the southwest coast of the Iberian Peninsula in 2018, was chosen as a case study. A coastal land use/land cover method optimization by optical and UAV field data resulted in an overall improvement of about 20% in the identification of disaster-affected areas by reducing false alarms by up to 33%. Finally, the method achieved hit and false alarm rates of about 80% and 20%, respectively, leading to the identification of approximately 30% (7000 ha) of the study area as being affected by the storm. Marshes and vegetated dunes were the most significantly impacted covers. In addition, SAR data enabled the impact assessment with a time lag of 2 days, contrasting the 25-day delay of optical data. The proposed method stands out as a valuable tool for regional-scale coastal disaster monitoring. In addition, it can be automated and operated at a low cost, making it a valuable tool for decision-making support.
Fil: Garzo, Pedro Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Geología de Costas y del Cuaternario. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Geología de Costas y del Cuaternario; Argentina
Fil: Fernández Montblanc, Tomás. Universidad de Cádiz; España. Universidad de Cadiz. Centro Andaluz Superior de Estudios Marinos.; España
Materia
SYNTHETIC APERTURE RADARS
DISASTER MONITORING
COASTAL HAZARDS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/221705

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spelling Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern SpainGarzo, Pedro AndrésFernández Montblanc, TomásSYNTHETIC APERTURE RADARSDISASTER MONITORINGCOASTAL HAZARDShttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1The high exposure of coastal areas worldwide to natural and anthropogenic disasters emphasizes the relevance of disaster management processes that ensure a prompt damage detection and identification of affected areas. This paper aimed to develop a novel approach for disaster monitoring in coastal areas using SAR data. The method was based on an interferometric coherence difference analysis of Sentinel 1 data. To calibrate and validate the method, the Emma Storm, a severe coastal storm that affected the southwest coast of the Iberian Peninsula in 2018, was chosen as a case study. A coastal land use/land cover method optimization by optical and UAV field data resulted in an overall improvement of about 20% in the identification of disaster-affected areas by reducing false alarms by up to 33%. Finally, the method achieved hit and false alarm rates of about 80% and 20%, respectively, leading to the identification of approximately 30% (7000 ha) of the study area as being affected by the storm. Marshes and vegetated dunes were the most significantly impacted covers. In addition, SAR data enabled the impact assessment with a time lag of 2 days, contrasting the 25-day delay of optical data. The proposed method stands out as a valuable tool for regional-scale coastal disaster monitoring. In addition, it can be automated and operated at a low cost, making it a valuable tool for decision-making support.Fil: Garzo, Pedro Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Geología de Costas y del Cuaternario. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Geología de Costas y del Cuaternario; ArgentinaFil: Fernández Montblanc, Tomás. Universidad de Cádiz; España. Universidad de Cadiz. Centro Andaluz Superior de Estudios Marinos.; EspañaMultidisciplinary Digital Publishing Institute2023-06-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/221705Garzo, Pedro Andrés; Fernández Montblanc, Tomás; Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain; Multidisciplinary Digital Publishing Institute; Remote Sensing; 15; 13; 22-6-2023; 1-242072-4292CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2072-4292/15/13/3233info:eu-repo/semantics/altIdentifier/doi/10.3390/rs15133233info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:34:28Zoai:ri.conicet.gov.ar:11336/221705instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:34:28.703CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
title Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
spellingShingle Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
Garzo, Pedro Andrés
SYNTHETIC APERTURE RADARS
DISASTER MONITORING
COASTAL HAZARDS
title_short Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
title_full Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
title_fullStr Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
title_full_unstemmed Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
title_sort Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain
dc.creator.none.fl_str_mv Garzo, Pedro Andrés
Fernández Montblanc, Tomás
author Garzo, Pedro Andrés
author_facet Garzo, Pedro Andrés
Fernández Montblanc, Tomás
author_role author
author2 Fernández Montblanc, Tomás
author2_role author
dc.subject.none.fl_str_mv SYNTHETIC APERTURE RADARS
DISASTER MONITORING
COASTAL HAZARDS
topic SYNTHETIC APERTURE RADARS
DISASTER MONITORING
COASTAL HAZARDS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The high exposure of coastal areas worldwide to natural and anthropogenic disasters emphasizes the relevance of disaster management processes that ensure a prompt damage detection and identification of affected areas. This paper aimed to develop a novel approach for disaster monitoring in coastal areas using SAR data. The method was based on an interferometric coherence difference analysis of Sentinel 1 data. To calibrate and validate the method, the Emma Storm, a severe coastal storm that affected the southwest coast of the Iberian Peninsula in 2018, was chosen as a case study. A coastal land use/land cover method optimization by optical and UAV field data resulted in an overall improvement of about 20% in the identification of disaster-affected areas by reducing false alarms by up to 33%. Finally, the method achieved hit and false alarm rates of about 80% and 20%, respectively, leading to the identification of approximately 30% (7000 ha) of the study area as being affected by the storm. Marshes and vegetated dunes were the most significantly impacted covers. In addition, SAR data enabled the impact assessment with a time lag of 2 days, contrasting the 25-day delay of optical data. The proposed method stands out as a valuable tool for regional-scale coastal disaster monitoring. In addition, it can be automated and operated at a low cost, making it a valuable tool for decision-making support.
Fil: Garzo, Pedro Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Geología de Costas y del Cuaternario. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Geología de Costas y del Cuaternario; Argentina
Fil: Fernández Montblanc, Tomás. Universidad de Cádiz; España. Universidad de Cadiz. Centro Andaluz Superior de Estudios Marinos.; España
description The high exposure of coastal areas worldwide to natural and anthropogenic disasters emphasizes the relevance of disaster management processes that ensure a prompt damage detection and identification of affected areas. This paper aimed to develop a novel approach for disaster monitoring in coastal areas using SAR data. The method was based on an interferometric coherence difference analysis of Sentinel 1 data. To calibrate and validate the method, the Emma Storm, a severe coastal storm that affected the southwest coast of the Iberian Peninsula in 2018, was chosen as a case study. A coastal land use/land cover method optimization by optical and UAV field data resulted in an overall improvement of about 20% in the identification of disaster-affected areas by reducing false alarms by up to 33%. Finally, the method achieved hit and false alarm rates of about 80% and 20%, respectively, leading to the identification of approximately 30% (7000 ha) of the study area as being affected by the storm. Marshes and vegetated dunes were the most significantly impacted covers. In addition, SAR data enabled the impact assessment with a time lag of 2 days, contrasting the 25-day delay of optical data. The proposed method stands out as a valuable tool for regional-scale coastal disaster monitoring. In addition, it can be automated and operated at a low cost, making it a valuable tool for decision-making support.
publishDate 2023
dc.date.none.fl_str_mv 2023-06-22
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/221705
Garzo, Pedro Andrés; Fernández Montblanc, Tomás; Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain; Multidisciplinary Digital Publishing Institute; Remote Sensing; 15; 13; 22-6-2023; 1-24
2072-4292
CONICET Digital
CONICET
url http://hdl.handle.net/11336/221705
identifier_str_mv Garzo, Pedro Andrés; Fernández Montblanc, Tomás; Land use/land cover optimized SAR coherence analysis for rapid coastal disaster monitoring: the impact of the Emma Storm in southern Spain; Multidisciplinary Digital Publishing Institute; Remote Sensing; 15; 13; 22-6-2023; 1-24
2072-4292
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2072-4292/15/13/3233
info:eu-repo/semantics/altIdentifier/doi/10.3390/rs15133233
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
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