Estimating flow resistance of wetlands using SAR images and interaction models

Autores
Salvia, M.; Franco, M.; Grings, F.; Perna, P.; Martino, R.; Karszenbaum, H.; Ferrazzoli, P.
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
Fil:Salvia, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Grings, F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Perna, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Karszenbaum, H. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fuente
Remote Sens. 2009;1(4):992-1008
Materia
Marsh hydraulic conductivity
Microwave interaction model
Synthetic Aperture Radar (SAR)
Wetland management
Ancillary data
Argentina
Backscattering coefficients
Fire event
Flow resistance
Herbaceous vegetation
Interaction model
Marsh hydraulic conductivity
Marsh vegetation
Microwave interaction model
Regional scale
Remote sensing data
River deltas
SAR Images
Test case
Vegetation structure
Wetland management
Backscattering
Drag
Drag coefficient
Imaging systems
Remote sensing
Vegetation
Wetlands
Synthetic aperture radar
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/2.5/ar
Repositorio
Biblioteca Digital (UBA-FCEN)
Institución
Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
OAI Identificador
paperaa:paper_20724292_v1_n4_p992_Salvia
Acceder
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oai_identifier_str paperaa:paper_20724292_v1_n4_p992_Salvia
network_acronym_str BDUBAFCEN
repository_id_str 1896
network_name_str Biblioteca Digital (UBA-FCEN)
spelling Estimating flow resistance of wetlands using SAR images and interaction modelsSalvia, M.Franco, M.Grings, F.Perna, P.Martino, R.Karszenbaum, H.Ferrazzoli, P.Marsh hydraulic conductivityMicrowave interaction modelSynthetic Aperture Radar (SAR)Wetland managementAncillary dataArgentinaBackscattering coefficientsFire eventFlow resistanceHerbaceous vegetationInteraction modelMarsh hydraulic conductivityMarsh vegetationMicrowave interaction modelRegional scaleRemote sensing dataRiver deltasSAR ImagesTest caseVegetation structureWetland managementBackscatteringDragDrag coefficientImaging systemsRemote sensingVegetationWetlandsSynthetic aperture radarThe inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.Fil:Salvia, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Grings, F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Perna, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Karszenbaum, H. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.2009info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12110/paper_20724292_v1_n4_p992_SalviaRemote Sens. 2009;1(4):992-1008reponame:Biblioteca Digital (UBA-FCEN)instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesinstacron:UBA-FCENenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/ar2025-10-23T11:18:27Zpaperaa:paper_20724292_v1_n4_p992_SalviaInstitucionalhttps://digital.bl.fcen.uba.ar/Universidad públicaNo correspondehttps://digital.bl.fcen.uba.ar/cgi-bin/oaiserver.cgiana@bl.fcen.uba.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18962025-10-23 11:18:29.126Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesfalse
dc.title.none.fl_str_mv Estimating flow resistance of wetlands using SAR images and interaction models
title Estimating flow resistance of wetlands using SAR images and interaction models
spellingShingle Estimating flow resistance of wetlands using SAR images and interaction models
Salvia, M.
Marsh hydraulic conductivity
Microwave interaction model
Synthetic Aperture Radar (SAR)
Wetland management
Ancillary data
Argentina
Backscattering coefficients
Fire event
Flow resistance
Herbaceous vegetation
Interaction model
Marsh hydraulic conductivity
Marsh vegetation
Microwave interaction model
Regional scale
Remote sensing data
River deltas
SAR Images
Test case
Vegetation structure
Wetland management
Backscattering
Drag
Drag coefficient
Imaging systems
Remote sensing
Vegetation
Wetlands
Synthetic aperture radar
title_short Estimating flow resistance of wetlands using SAR images and interaction models
title_full Estimating flow resistance of wetlands using SAR images and interaction models
title_fullStr Estimating flow resistance of wetlands using SAR images and interaction models
title_full_unstemmed Estimating flow resistance of wetlands using SAR images and interaction models
title_sort Estimating flow resistance of wetlands using SAR images and interaction models
dc.creator.none.fl_str_mv Salvia, M.
Franco, M.
Grings, F.
Perna, P.
Martino, R.
Karszenbaum, H.
Ferrazzoli, P.
author Salvia, M.
author_facet Salvia, M.
Franco, M.
Grings, F.
Perna, P.
Martino, R.
Karszenbaum, H.
Ferrazzoli, P.
author_role author
author2 Franco, M.
Grings, F.
Perna, P.
Martino, R.
Karszenbaum, H.
Ferrazzoli, P.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Marsh hydraulic conductivity
Microwave interaction model
Synthetic Aperture Radar (SAR)
Wetland management
Ancillary data
Argentina
Backscattering coefficients
Fire event
Flow resistance
Herbaceous vegetation
Interaction model
Marsh hydraulic conductivity
Marsh vegetation
Microwave interaction model
Regional scale
Remote sensing data
River deltas
SAR Images
Test case
Vegetation structure
Wetland management
Backscattering
Drag
Drag coefficient
Imaging systems
Remote sensing
Vegetation
Wetlands
Synthetic aperture radar
topic Marsh hydraulic conductivity
Microwave interaction model
Synthetic Aperture Radar (SAR)
Wetland management
Ancillary data
Argentina
Backscattering coefficients
Fire event
Flow resistance
Herbaceous vegetation
Interaction model
Marsh hydraulic conductivity
Marsh vegetation
Microwave interaction model
Regional scale
Remote sensing data
River deltas
SAR Images
Test case
Vegetation structure
Wetland management
Backscattering
Drag
Drag coefficient
Imaging systems
Remote sensing
Vegetation
Wetlands
Synthetic aperture radar
dc.description.none.fl_txt_mv The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
Fil:Salvia, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Grings, F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Perna, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Karszenbaum, H. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
description The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
publishDate 2009
dc.date.none.fl_str_mv 2009
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/20.500.12110/paper_20724292_v1_n4_p992_Salvia
url http://hdl.handle.net/20.500.12110/paper_20724292_v1_n4_p992_Salvia
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/2.5/ar
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/2.5/ar
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Remote Sens. 2009;1(4):992-1008
reponame:Biblioteca Digital (UBA-FCEN)
instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron:UBA-FCEN
reponame_str Biblioteca Digital (UBA-FCEN)
collection Biblioteca Digital (UBA-FCEN)
instname_str Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron_str UBA-FCEN
institution UBA-FCEN
repository.name.fl_str_mv Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
repository.mail.fl_str_mv ana@bl.fcen.uba.ar
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score 12.982451

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