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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/221705
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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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844614362199752704 |
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13.070432 |