Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach

Autores
Blanco, Paula Daniela; Metternicht, Graciela; del Valle, Hector Francisco
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Soil erosion is a key factor in land degradation processes in the sandy rangelands of the Peninsula Valdes of Patagonia, Argentina. Mapping landform and vegetation patterns is important for improving prediction, monitoring and planning of areas threatened by sand and shrub encroachment. This paper investigates the contribution of optical sensors, such as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and textural measures derived from microwave Radarsat Advanced Synthetic Aperture Radar (ASAR) to their discrimination. An evaluation is undertaken to compare the classification accuracy achieved by specific regions of the spectrum and their synergistic use in an object-oriented approach. Image segmentation and object-oriented classifications were applied to the datasets. This required defining appropriate fuzzy membership functions for characterizing active and stabilized lineal dunes and the main vegetation classes. Improvements in the discrimination of active and stabilized dunes (vegetated by either scrub or grass) were achieved by using an object-oriented classification that integrated microwave and visible near-infrared (NIR) data. Changes in surface roughness caused by different vegetation types stabilizing the dunes affected the radar backscattering. Whereas Radarsat enabled a clear separation of scrub-stabilized dunes, Terra-ASTER showed superior performance in the cartography of grass-stabilized dunes. The synergistic use of microwave and visible and near-infrared (VNIR) data yielded a substantial increase in the discrimination and mapping of landform/vegetation patterns.
Fil: Blanco, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Fil: Metternicht, Graciela. United Nations Environment Programme; Panamá
Fil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Materia
ASTER
RADARSAT-1
LANDFORM MAPPING
VEGETATION PATTERNS
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:11336/96074
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/96074
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approachBlanco, Paula DanielaMetternicht, Gracieladel Valle, Hector FranciscoASTERRADARSAT-1LANDFORM MAPPINGVEGETATION PATTERNShttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Soil erosion is a key factor in land degradation processes in the sandy rangelands of the Peninsula Valdes of Patagonia, Argentina. Mapping landform and vegetation patterns is important for improving prediction, monitoring and planning of areas threatened by sand and shrub encroachment. This paper investigates the contribution of optical sensors, such as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and textural measures derived from microwave Radarsat Advanced Synthetic Aperture Radar (ASAR) to their discrimination. An evaluation is undertaken to compare the classification accuracy achieved by specific regions of the spectrum and their synergistic use in an object-oriented approach. Image segmentation and object-oriented classifications were applied to the datasets. This required defining appropriate fuzzy membership functions for characterizing active and stabilized lineal dunes and the main vegetation classes. Improvements in the discrimination of active and stabilized dunes (vegetated by either scrub or grass) were achieved by using an object-oriented classification that integrated microwave and visible near-infrared (NIR) data. Changes in surface roughness caused by different vegetation types stabilizing the dunes affected the radar backscattering. Whereas Radarsat enabled a clear separation of scrub-stabilized dunes, Terra-ASTER showed superior performance in the cartography of grass-stabilized dunes. The synergistic use of microwave and visible and near-infrared (VNIR) data yielded a substantial increase in the discrimination and mapping of landform/vegetation patterns.Fil: Blanco, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Metternicht, Graciela. United Nations Environment Programme; PanamáFil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaTaylor & Francis2009-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/96074Blanco, Paula Daniela; Metternicht, Graciela; del Valle, Hector Francisco; Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach; Taylor & Francis; International Journal of Remote Sensing; 30; 10; 5-2009; 2579-26050143-1161CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1080/01431160802552785info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/01431160802552785info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:38:24Zoai:ri.conicet.gov.ar:11336/96074instacron: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 09:38:24.863CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
title Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
spellingShingle Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
Blanco, Paula Daniela
ASTER
RADARSAT-1
LANDFORM MAPPING
VEGETATION PATTERNS
title_short Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
title_full Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
title_fullStr Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
title_full_unstemmed Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
title_sort Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach
dc.creator.none.fl_str_mv Blanco, Paula Daniela
Metternicht, Graciela
del Valle, Hector Francisco
author Blanco, Paula Daniela
author_facet Blanco, Paula Daniela
Metternicht, Graciela
del Valle, Hector Francisco
author_role author
author2 Metternicht, Graciela
del Valle, Hector Francisco
author2_role author
author
dc.subject.none.fl_str_mv ASTER
RADARSAT-1
LANDFORM MAPPING
VEGETATION PATTERNS
topic ASTER
RADARSAT-1
LANDFORM MAPPING
VEGETATION PATTERNS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Soil erosion is a key factor in land degradation processes in the sandy rangelands of the Peninsula Valdes of Patagonia, Argentina. Mapping landform and vegetation patterns is important for improving prediction, monitoring and planning of areas threatened by sand and shrub encroachment. This paper investigates the contribution of optical sensors, such as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and textural measures derived from microwave Radarsat Advanced Synthetic Aperture Radar (ASAR) to their discrimination. An evaluation is undertaken to compare the classification accuracy achieved by specific regions of the spectrum and their synergistic use in an object-oriented approach. Image segmentation and object-oriented classifications were applied to the datasets. This required defining appropriate fuzzy membership functions for characterizing active and stabilized lineal dunes and the main vegetation classes. Improvements in the discrimination of active and stabilized dunes (vegetated by either scrub or grass) were achieved by using an object-oriented classification that integrated microwave and visible near-infrared (NIR) data. Changes in surface roughness caused by different vegetation types stabilizing the dunes affected the radar backscattering. Whereas Radarsat enabled a clear separation of scrub-stabilized dunes, Terra-ASTER showed superior performance in the cartography of grass-stabilized dunes. The synergistic use of microwave and visible and near-infrared (VNIR) data yielded a substantial increase in the discrimination and mapping of landform/vegetation patterns.
Fil: Blanco, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Fil: Metternicht, Graciela. United Nations Environment Programme; Panamá
Fil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
description Soil erosion is a key factor in land degradation processes in the sandy rangelands of the Peninsula Valdes of Patagonia, Argentina. Mapping landform and vegetation patterns is important for improving prediction, monitoring and planning of areas threatened by sand and shrub encroachment. This paper investigates the contribution of optical sensors, such as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and textural measures derived from microwave Radarsat Advanced Synthetic Aperture Radar (ASAR) to their discrimination. An evaluation is undertaken to compare the classification accuracy achieved by specific regions of the spectrum and their synergistic use in an object-oriented approach. Image segmentation and object-oriented classifications were applied to the datasets. This required defining appropriate fuzzy membership functions for characterizing active and stabilized lineal dunes and the main vegetation classes. Improvements in the discrimination of active and stabilized dunes (vegetated by either scrub or grass) were achieved by using an object-oriented classification that integrated microwave and visible near-infrared (NIR) data. Changes in surface roughness caused by different vegetation types stabilizing the dunes affected the radar backscattering. Whereas Radarsat enabled a clear separation of scrub-stabilized dunes, Terra-ASTER showed superior performance in the cartography of grass-stabilized dunes. The synergistic use of microwave and visible and near-infrared (VNIR) data yielded a substantial increase in the discrimination and mapping of landform/vegetation patterns.
publishDate 2009
dc.date.none.fl_str_mv 2009-05
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/11336/96074
Blanco, Paula Daniela; Metternicht, Graciela; del Valle, Hector Francisco; Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach; Taylor & Francis; International Journal of Remote Sensing; 30; 10; 5-2009; 2579-2605
0143-1161
CONICET Digital
CONICET
url http://hdl.handle.net/11336/96074
identifier_str_mv Blanco, Paula Daniela; Metternicht, Graciela; del Valle, Hector Francisco; Improving the discrimination of vegetation and landform patterns in sandy rangelands: A synergistic approach; Taylor & Francis; International Journal of Remote Sensing; 30; 10; 5-2009; 2579-2605
0143-1161
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/01431160802552785
info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/01431160802552785
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
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
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
_version_ 1844613213676634112
score 13.070432

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