Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery

Autores
Revollo Sarmiento, Gisela Noelia; Revollo Sarmiento, Natalia Veronica; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Ponds and tidal courses are significant landforms that frequently arise in marshes and tidal flats environments. An understanding of their development and permanence is relevant to determine future dynamic processes that alter tidal flats and salt marshes environments, such as changes in the sea level, increase in the wave activity, and some other variations associated to the climate change. Direct access for monitoring in these regions is complex, extremely expensive and not always feasible. Remote sensing imagery represents a monitoring alternative, but requires the research of specific image processing procedures to extract the information concerning to these environmental studies. In this work, we developed a methodology for assessing the relevant morphological parameters of ponds and tidal courses using Google Earth imagery. An automatic classifier identifies these landforms as such (accuracy over 86%), producing a shape descriptors dataset. Then, ponds and tidal courses in tidal flats are morphologically characterized, and their behavior is compared to the surrounding environment. Subsequent analysis found significant differences in morphological characteristics that arise independently of the marsh environmental conditions. The evidence suggests that the evolution processes of the depressions in salt flat environments are clearly different in comparison with salt marshes environments. In salt marshes, the permanence and evolution of the depressions is related to the age of marshes, whereas in tidal flats the dynamic processes and sediment input have influence on depressions evolution.
Fil: Revollo Sarmiento, Gisela Noelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Fil: Revollo Sarmiento, Natalia Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geología; Argentina
Materia
CLASSIFICATION
DIGITAL IMAGE PROCESSING
PONDS
SHAPE DESCRIPTORS
TIDAL COURSES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/134092
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/134092
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imageryRevollo Sarmiento, Gisela NoeliaRevollo Sarmiento, Natalia VeronicaDelrieux, Claudio AugustoPerillo, Gerardo Miguel E.CLASSIFICATIONDIGITAL IMAGE PROCESSINGPONDSSHAPE DESCRIPTORSTIDAL COURSEShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Ponds and tidal courses are significant landforms that frequently arise in marshes and tidal flats environments. An understanding of their development and permanence is relevant to determine future dynamic processes that alter tidal flats and salt marshes environments, such as changes in the sea level, increase in the wave activity, and some other variations associated to the climate change. Direct access for monitoring in these regions is complex, extremely expensive and not always feasible. Remote sensing imagery represents a monitoring alternative, but requires the research of specific image processing procedures to extract the information concerning to these environmental studies. In this work, we developed a methodology for assessing the relevant morphological parameters of ponds and tidal courses using Google Earth imagery. An automatic classifier identifies these landforms as such (accuracy over 86%), producing a shape descriptors dataset. Then, ponds and tidal courses in tidal flats are morphologically characterized, and their behavior is compared to the surrounding environment. Subsequent analysis found significant differences in morphological characteristics that arise independently of the marsh environmental conditions. The evidence suggests that the evolution processes of the depressions in salt flat environments are clearly different in comparison with salt marshes environments. In salt marshes, the permanence and evolution of the depressions is related to the age of marshes, whereas in tidal flats the dynamic processes and sediment input have influence on depressions evolution.Fil: Revollo Sarmiento, Gisela Noelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Revollo Sarmiento, Natalia Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geología; ArgentinaAcademic Press Ltd - Elsevier Science Ltd2020-09-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/134092Revollo Sarmiento, Gisela Noelia; Revollo Sarmiento, Natalia Veronica; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery; Academic Press Ltd - Elsevier Science Ltd; Estuarine, Coastal and Shelf Science; 246; 29-9-2020; 1-13; 1070410272-7714CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecss.2020.107041info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0272771420307721info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:59:10Zoai:ri.conicet.gov.ar:11336/134092instacron: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 09:59:11.13CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
title Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
spellingShingle Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
Revollo Sarmiento, Gisela Noelia
CLASSIFICATION
DIGITAL IMAGE PROCESSING
PONDS
SHAPE DESCRIPTORS
TIDAL COURSES
title_short Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
title_full Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
title_fullStr Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
title_full_unstemmed Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
title_sort Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery
dc.creator.none.fl_str_mv Revollo Sarmiento, Gisela Noelia
Revollo Sarmiento, Natalia Veronica
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
author Revollo Sarmiento, Gisela Noelia
author_facet Revollo Sarmiento, Gisela Noelia
Revollo Sarmiento, Natalia Veronica
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
author_role author
author2 Revollo Sarmiento, Natalia Veronica
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
author2_role author
author
author
dc.subject.none.fl_str_mv CLASSIFICATION
DIGITAL IMAGE PROCESSING
PONDS
SHAPE DESCRIPTORS
TIDAL COURSES
topic CLASSIFICATION
DIGITAL IMAGE PROCESSING
PONDS
SHAPE DESCRIPTORS
TIDAL COURSES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Ponds and tidal courses are significant landforms that frequently arise in marshes and tidal flats environments. An understanding of their development and permanence is relevant to determine future dynamic processes that alter tidal flats and salt marshes environments, such as changes in the sea level, increase in the wave activity, and some other variations associated to the climate change. Direct access for monitoring in these regions is complex, extremely expensive and not always feasible. Remote sensing imagery represents a monitoring alternative, but requires the research of specific image processing procedures to extract the information concerning to these environmental studies. In this work, we developed a methodology for assessing the relevant morphological parameters of ponds and tidal courses using Google Earth imagery. An automatic classifier identifies these landforms as such (accuracy over 86%), producing a shape descriptors dataset. Then, ponds and tidal courses in tidal flats are morphologically characterized, and their behavior is compared to the surrounding environment. Subsequent analysis found significant differences in morphological characteristics that arise independently of the marsh environmental conditions. The evidence suggests that the evolution processes of the depressions in salt flat environments are clearly different in comparison with salt marshes environments. In salt marshes, the permanence and evolution of the depressions is related to the age of marshes, whereas in tidal flats the dynamic processes and sediment input have influence on depressions evolution.
Fil: Revollo Sarmiento, Gisela Noelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Fil: Revollo Sarmiento, Natalia Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geología; Argentina
description Ponds and tidal courses are significant landforms that frequently arise in marshes and tidal flats environments. An understanding of their development and permanence is relevant to determine future dynamic processes that alter tidal flats and salt marshes environments, such as changes in the sea level, increase in the wave activity, and some other variations associated to the climate change. Direct access for monitoring in these regions is complex, extremely expensive and not always feasible. Remote sensing imagery represents a monitoring alternative, but requires the research of specific image processing procedures to extract the information concerning to these environmental studies. In this work, we developed a methodology for assessing the relevant morphological parameters of ponds and tidal courses using Google Earth imagery. An automatic classifier identifies these landforms as such (accuracy over 86%), producing a shape descriptors dataset. Then, ponds and tidal courses in tidal flats are morphologically characterized, and their behavior is compared to the surrounding environment. Subsequent analysis found significant differences in morphological characteristics that arise independently of the marsh environmental conditions. The evidence suggests that the evolution processes of the depressions in salt flat environments are clearly different in comparison with salt marshes environments. In salt marshes, the permanence and evolution of the depressions is related to the age of marshes, whereas in tidal flats the dynamic processes and sediment input have influence on depressions evolution.
publishDate 2020
dc.date.none.fl_str_mv 2020-09-29
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/11336/134092
Revollo Sarmiento, Gisela Noelia; Revollo Sarmiento, Natalia Veronica; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery; Academic Press Ltd - Elsevier Science Ltd; Estuarine, Coastal and Shelf Science; 246; 29-9-2020; 1-13; 107041
0272-7714
CONICET Digital
CONICET
url http://hdl.handle.net/11336/134092
identifier_str_mv Revollo Sarmiento, Gisela Noelia; Revollo Sarmiento, Natalia Veronica; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery; Academic Press Ltd - Elsevier Science Ltd; Estuarine, Coastal and Shelf Science; 246; 29-9-2020; 1-13; 107041
0272-7714
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecss.2020.107041
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0272771420307721
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Academic Press Ltd - Elsevier Science Ltd
publisher.none.fl_str_mv Academic Press Ltd - Elsevier Science Ltd
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
repository.name.fl_str_mv 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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score 13.070432

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