Subsurface soil moisture estimation by VI-LST method

Autores
Holzman, Mauro Ezequiel; Rivas, Raúl; Bayala, Martín Ignacio
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this letter, the relationship between temperature vegetation dryness index (TVDI) from the Moderate Resolution Imaging Spectroradiometer and subsurface soil moisture (SM) cover crop and native grassland of the Argentine Pampas is analyzed.High correlation (R2 > 0.69) between TVDI and SM measurements was found at different soil depths. In addition, we found that the potential of this index to reflect subsurface soil wetness fluctuations depends on root system depth, root distribution in the soil, and physical soil characteristics. Results indicate that thermal and reflectance data combination could be used to monitor subsurface SM below vegetated areas.
Fil: Holzman, Mauro Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina
Fil: Rivas, Raúl. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina
Fil: Bayala, Martín Ignacio. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina
Materia
Optical–Thermal
Soil Moisture (Sm)
Stress Index
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:11336/10861
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Subsurface soil moisture estimation by VI-LST methodHolzman, Mauro EzequielRivas, RaúlBayala, Martín IgnacioOptical–ThermalSoil Moisture (Sm)Stress Indexhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1In this letter, the relationship between temperature vegetation dryness index (TVDI) from the Moderate Resolution Imaging Spectroradiometer and subsurface soil moisture (SM) cover crop and native grassland of the Argentine Pampas is analyzed.High correlation (R2 > 0.69) between TVDI and SM measurements was found at different soil depths. In addition, we found that the potential of this index to reflect subsurface soil wetness fluctuations depends on root system depth, root distribution in the soil, and physical soil characteristics. Results indicate that thermal and reflectance data combination could be used to monitor subsurface SM below vegetated areas.Fil: Holzman, Mauro Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; ArgentinaFil: Rivas, Raúl. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; ArgentinaFil: Bayala, Martín Ignacio. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; ArgentinaInstitute Of Electrical And Electronics Engineers2014-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/10861Holzman, Mauro Ezequiel; Rivas, Raúl; Bayala, Martín Ignacio; Subsurface soil moisture estimation by VI-LST method; Institute Of Electrical And Electronics Engineers; Ieee Geoscience And Remote Sensing Letters; 11; 11; 5-2014; 1951-19551545-598Xenginfo:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6803861info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2014.2314617info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:05:26Zoai:ri.conicet.gov.ar:11336/10861instacron: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:34982025-10-22 11:05:27.081CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Subsurface soil moisture estimation by VI-LST method
title Subsurface soil moisture estimation by VI-LST method
spellingShingle Subsurface soil moisture estimation by VI-LST method
Holzman, Mauro Ezequiel
Optical–Thermal
Soil Moisture (Sm)
Stress Index
title_short Subsurface soil moisture estimation by VI-LST method
title_full Subsurface soil moisture estimation by VI-LST method
title_fullStr Subsurface soil moisture estimation by VI-LST method
title_full_unstemmed Subsurface soil moisture estimation by VI-LST method
title_sort Subsurface soil moisture estimation by VI-LST method
dc.creator.none.fl_str_mv Holzman, Mauro Ezequiel
Rivas, Raúl
Bayala, Martín Ignacio
author Holzman, Mauro Ezequiel
author_facet Holzman, Mauro Ezequiel
Rivas, Raúl
Bayala, Martín Ignacio
author_role author
author2 Rivas, Raúl
Bayala, Martín Ignacio
author2_role author
author
dc.subject.none.fl_str_mv Optical–Thermal
Soil Moisture (Sm)
Stress Index
topic Optical–Thermal
Soil Moisture (Sm)
Stress Index
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
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 In this letter, the relationship between temperature vegetation dryness index (TVDI) from the Moderate Resolution Imaging Spectroradiometer and subsurface soil moisture (SM) cover crop and native grassland of the Argentine Pampas is analyzed.High correlation (R2 > 0.69) between TVDI and SM measurements was found at different soil depths. In addition, we found that the potential of this index to reflect subsurface soil wetness fluctuations depends on root system depth, root distribution in the soil, and physical soil characteristics. Results indicate that thermal and reflectance data combination could be used to monitor subsurface SM below vegetated areas.
Fil: Holzman, Mauro Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina
Fil: Rivas, Raúl. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina
Fil: Bayala, Martín Ignacio. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina
description In this letter, the relationship between temperature vegetation dryness index (TVDI) from the Moderate Resolution Imaging Spectroradiometer and subsurface soil moisture (SM) cover crop and native grassland of the Argentine Pampas is analyzed.High correlation (R2 > 0.69) between TVDI and SM measurements was found at different soil depths. In addition, we found that the potential of this index to reflect subsurface soil wetness fluctuations depends on root system depth, root distribution in the soil, and physical soil characteristics. Results indicate that thermal and reflectance data combination could be used to monitor subsurface SM below vegetated areas.
publishDate 2014
dc.date.none.fl_str_mv 2014-05
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/11336/10861
Holzman, Mauro Ezequiel; Rivas, Raúl; Bayala, Martín Ignacio; Subsurface soil moisture estimation by VI-LST method; Institute Of Electrical And Electronics Engineers; Ieee Geoscience And Remote Sensing Letters; 11; 11; 5-2014; 1951-1955
1545-598X
url http://hdl.handle.net/11336/10861
identifier_str_mv Holzman, Mauro Ezequiel; Rivas, Raúl; Bayala, Martín Ignacio; Subsurface soil moisture estimation by VI-LST method; Institute Of Electrical And Electronics Engineers; Ieee Geoscience And Remote Sensing Letters; 11; 11; 5-2014; 1951-1955
1545-598X
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6803861
info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2014.2314617
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
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
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score 12.982451

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