A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements

Autores
Grimson, Rafael; Bali, Juan Lucas; Rajngewerc, Mariela; Martin, Laura San; Salvia, Maria Mercedes
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
When a passive microwave footprint intersects objects on the ground with different spectral characteristics, the corresponding observation is mixed. The retrieval of geophysical parameters is limited by this mixture. We propose to partition the study region into objects following an object-based image analysis procedure and then to refine this partition into small cells. Then, we introduce a statistical method to estimate the brightness temperature (TB) of each cell. The method assumes that TB of the cells corresponding to the same object is identically distributed and that the TB heterogeneity within each cell can be neglected. The implementation is based on an iterative expectation-maximization algorithm. We evaluated the proposed method using synthetic images and applied it to grid the TBs of sample AMSR -2 real data over a coastal region in Argentina.
Fil: Grimson, Rafael. Universidad Nacional de San Martín; Argentina
Fil: Bali, Juan Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rajngewerc, Mariela. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina
Fil: Martin, Laura San. Universidad Nacional de San Martín; Argentina
Fil: Salvia, Maria Mercedes. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Materia
Expectation-Maximization (Em) Algorithms
Inverse Problems
Passive Microwave Remote Sensing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC 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:11336/80643
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/80643
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed MeasurementsGrimson, RafaelBali, Juan LucasRajngewerc, MarielaMartin, Laura SanSalvia, Maria MercedesExpectation-Maximization (Em) AlgorithmsInverse ProblemsPassive Microwave Remote Sensinghttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1When a passive microwave footprint intersects objects on the ground with different spectral characteristics, the corresponding observation is mixed. The retrieval of geophysical parameters is limited by this mixture. We propose to partition the study region into objects following an object-based image analysis procedure and then to refine this partition into small cells. Then, we introduce a statistical method to estimate the brightness temperature (TB) of each cell. The method assumes that TB of the cells corresponding to the same object is identically distributed and that the TB heterogeneity within each cell can be neglected. The implementation is based on an iterative expectation-maximization algorithm. We evaluated the proposed method using synthetic images and applied it to grid the TBs of sample AMSR -2 real data over a coastal region in Argentina.Fil: Grimson, Rafael. Universidad Nacional de San Martín; ArgentinaFil: Bali, Juan Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rajngewerc, Mariela. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; ArgentinaFil: Martin, Laura San. Universidad Nacional de San Martín; ArgentinaFil: Salvia, Maria Mercedes. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaInstitute of Electrical and Electronics Engineers2018-09info: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/11336/80643Grimson, Rafael; Bali, Juan Lucas; Rajngewerc, Mariela; Martin, Laura San; Salvia, Maria Mercedes; A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements; Institute of Electrical and Electronics Engineers; Ieee Transactions On Geoscience And Remote Sensing; 57; 3; 9-2018; 1347-13570196-2892CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/8468198info:eu-repo/semantics/altIdentifier/doi/10.1109/TGRS.2018.2866196info:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)https://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:45Zoai:ri.conicet.gov.ar:11336/80643instacron: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:34982025-09-03 09:47:46.262CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
title A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
spellingShingle A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
Grimson, Rafael
Expectation-Maximization (Em) Algorithms
Inverse Problems
Passive Microwave Remote Sensing
title_short A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
title_full A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
title_fullStr A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
title_full_unstemmed A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
title_sort A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements
dc.creator.none.fl_str_mv Grimson, Rafael
Bali, Juan Lucas
Rajngewerc, Mariela
Martin, Laura San
Salvia, Maria Mercedes
author Grimson, Rafael
author_facet Grimson, Rafael
Bali, Juan Lucas
Rajngewerc, Mariela
Martin, Laura San
Salvia, Maria Mercedes
author_role author
author2 Bali, Juan Lucas
Rajngewerc, Mariela
Martin, Laura San
Salvia, Maria Mercedes
author2_role author
author
author
author
dc.subject.none.fl_str_mv Expectation-Maximization (Em) Algorithms
Inverse Problems
Passive Microwave Remote Sensing
topic Expectation-Maximization (Em) Algorithms
Inverse Problems
Passive Microwave Remote Sensing
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv When a passive microwave footprint intersects objects on the ground with different spectral characteristics, the corresponding observation is mixed. The retrieval of geophysical parameters is limited by this mixture. We propose to partition the study region into objects following an object-based image analysis procedure and then to refine this partition into small cells. Then, we introduce a statistical method to estimate the brightness temperature (TB) of each cell. The method assumes that TB of the cells corresponding to the same object is identically distributed and that the TB heterogeneity within each cell can be neglected. The implementation is based on an iterative expectation-maximization algorithm. We evaluated the proposed method using synthetic images and applied it to grid the TBs of sample AMSR -2 real data over a coastal region in Argentina.
Fil: Grimson, Rafael. Universidad Nacional de San Martín; Argentina
Fil: Bali, Juan Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rajngewerc, Mariela. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina
Fil: Martin, Laura San. Universidad Nacional de San Martín; Argentina
Fil: Salvia, Maria Mercedes. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
description When a passive microwave footprint intersects objects on the ground with different spectral characteristics, the corresponding observation is mixed. The retrieval of geophysical parameters is limited by this mixture. We propose to partition the study region into objects following an object-based image analysis procedure and then to refine this partition into small cells. Then, we introduce a statistical method to estimate the brightness temperature (TB) of each cell. The method assumes that TB of the cells corresponding to the same object is identically distributed and that the TB heterogeneity within each cell can be neglected. The implementation is based on an iterative expectation-maximization algorithm. We evaluated the proposed method using synthetic images and applied it to grid the TBs of sample AMSR -2 real data over a coastal region in Argentina.
publishDate 2018
dc.date.none.fl_str_mv 2018-09
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/11336/80643
Grimson, Rafael; Bali, Juan Lucas; Rajngewerc, Mariela; Martin, Laura San; Salvia, Maria Mercedes; A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements; Institute of Electrical and Electronics Engineers; Ieee Transactions On Geoscience And Remote Sensing; 57; 3; 9-2018; 1347-1357
0196-2892
CONICET Digital
CONICET
url http://hdl.handle.net/11336/80643
identifier_str_mv Grimson, Rafael; Bali, Juan Lucas; Rajngewerc, Mariela; Martin, Laura San; Salvia, Maria Mercedes; A Statistical Inverse Method for Gridding Passive Microwave Data with Mixed Measurements; Institute of Electrical and Electronics Engineers; Ieee Transactions On Geoscience And Remote Sensing; 57; 3; 9-2018; 1347-1357
0196-2892
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://ieeexplore.ieee.org/document/8468198
info:eu-repo/semantics/altIdentifier/doi/10.1109/TGRS.2018.2866196
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
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_ 1842268879799189504
score 13.13397

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