Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza

Autores
Mescua, J.F.
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A combination of two methodologies is presented for detection and mapping of gypsum using ASTER L3A imagery. One of the methodologies uses the Quartz index defined for the ASTER TIR subsystem, which can be used for gypsum detection given its low response in Qi. The other consists in the combination of two band ratios of the ASTER SWIR subsystem, (4/5)/(7/5), which allows the identification of gypsum highlighting its high response in 4/5 and low response in 7/5. Two areas in the Cordillera Principal in the province of Mendoza were selected as case studies, and a field survey was conducted in order to evaluate the results. Both techniques are proved successful, yet classify erroneously some pixels as gypsum. Errors by excess are different for each method, which allows for these two techniques to be combined using a "decision tree" classifier to solve the misclassifications.
Fil:Mescua, J.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fuente
Rev. Asoc. Geol. Argent. 2010;66(4):619-622
Materia
Auquilco Formation
Processing
Remote sensing
Satellite
ASTER
classification
field survey
gypsum
remote sensing
satellite imagery
Argentina
Mendoza
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_00044822_v66_n4_p619_Mescua
Acceder
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oai_identifier_str paperaa:paper_00044822_v66_n4_p619_Mescua
network_acronym_str BDUBAFCEN
repository_id_str 1896
network_name_str Biblioteca Digital (UBA-FCEN)
spelling Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza Mescua, J.F.Auquilco FormationProcessingRemote sensingSatelliteASTERclassificationfield surveygypsumremote sensingsatellite imageryArgentinaMendozaA combination of two methodologies is presented for detection and mapping of gypsum using ASTER L3A imagery. One of the methodologies uses the Quartz index defined for the ASTER TIR subsystem, which can be used for gypsum detection given its low response in Qi. The other consists in the combination of two band ratios of the ASTER SWIR subsystem, (4/5)/(7/5), which allows the identification of gypsum highlighting its high response in 4/5 and low response in 7/5. Two areas in the Cordillera Principal in the province of Mendoza were selected as case studies, and a field survey was conducted in order to evaluate the results. Both techniques are proved successful, yet classify erroneously some pixels as gypsum. Errors by excess are different for each method, which allows for these two techniques to be combined using a "decision tree" classifier to solve the misclassifications.Fil:Mescua, J.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.2010info: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_00044822_v66_n4_p619_MescuaRev. Asoc. Geol. Argent. 2010;66(4):619-622reponame: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/ar2025-09-29T13:43:09Zpaperaa:paper_00044822_v66_n4_p619_MescuaInstitucionalhttps://digital.bl.fcen.uba.ar/Universidad públicaNo correspondehttps://digital.bl.fcen.uba.ar/cgi-bin/oaiserver.cgiana@bl.fcen.uba.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18962025-09-29 13:43:10.486Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesfalse
dc.title.none.fl_str_mv Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
title Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
spellingShingle Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
Mescua, J.F.
Auquilco Formation
Processing
Remote sensing
Satellite
ASTER
classification
field survey
gypsum
remote sensing
satellite imagery
Argentina
Mendoza
title_short Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
title_full Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
title_fullStr Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
title_full_unstemmed Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
title_sort Gypsum classification based on ASTER images in the Principal Cordillera of Mendoza
dc.creator.none.fl_str_mv Mescua, J.F.
author Mescua, J.F.
author_facet Mescua, J.F.
author_role author
dc.subject.none.fl_str_mv Auquilco Formation
Processing
Remote sensing
Satellite
ASTER
classification
field survey
gypsum
remote sensing
satellite imagery
Argentina
Mendoza
topic Auquilco Formation
Processing
Remote sensing
Satellite
ASTER
classification
field survey
gypsum
remote sensing
satellite imagery
Argentina
Mendoza
dc.description.none.fl_txt_mv A combination of two methodologies is presented for detection and mapping of gypsum using ASTER L3A imagery. One of the methodologies uses the Quartz index defined for the ASTER TIR subsystem, which can be used for gypsum detection given its low response in Qi. The other consists in the combination of two band ratios of the ASTER SWIR subsystem, (4/5)/(7/5), which allows the identification of gypsum highlighting its high response in 4/5 and low response in 7/5. Two areas in the Cordillera Principal in the province of Mendoza were selected as case studies, and a field survey was conducted in order to evaluate the results. Both techniques are proved successful, yet classify erroneously some pixels as gypsum. Errors by excess are different for each method, which allows for these two techniques to be combined using a "decision tree" classifier to solve the misclassifications.
Fil:Mescua, J.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
description A combination of two methodologies is presented for detection and mapping of gypsum using ASTER L3A imagery. One of the methodologies uses the Quartz index defined for the ASTER TIR subsystem, which can be used for gypsum detection given its low response in Qi. The other consists in the combination of two band ratios of the ASTER SWIR subsystem, (4/5)/(7/5), which allows the identification of gypsum highlighting its high response in 4/5 and low response in 7/5. Two areas in the Cordillera Principal in the province of Mendoza were selected as case studies, and a field survey was conducted in order to evaluate the results. Both techniques are proved successful, yet classify erroneously some pixels as gypsum. Errors by excess are different for each method, which allows for these two techniques to be combined using a "decision tree" classifier to solve the misclassifications.
publishDate 2010
dc.date.none.fl_str_mv 2010
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_00044822_v66_n4_p619_Mescua
url http://hdl.handle.net/20.500.12110/paper_00044822_v66_n4_p619_Mescua
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 Rev. Asoc. Geol. Argent. 2010;66(4):619-622
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 13.070432

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