Spatial crop yield estimation based on remotely sensed stress index

Autores
Holzman, Mauro; Rivas, Raúl; Bayala, Martín; Ocampo, Dora; Carmona, Facundo
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The improvement of methods to evaluate the real impact of soil moisture availability on crop systems is crucial because the importance for world economy and food production. The relationship between the remote sensed stress index TVDI, root-zone soil moisture and soybean yield was analyzed in a sandy region of Argentine Pampas. High correlation (R2 =0.68) between TVDI and soybean yield was observed. The obtained adjustment allows us to evaluate the spatial variability of yield during a humid and dry period 2-3 months before harvest. Since the method requires remote sensed data, it could be applied over areas with poor data coverage.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
Ciencias Agrarias
stress index
soil moisture
remote sensing
COMPUTERS IN OTHER SYSTEMS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/42000

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spelling Spatial crop yield estimation based on remotely sensed stress indexHolzman, MauroRivas, RaúlBayala, MartínOcampo, DoraCarmona, FacundoCiencias InformáticasCiencias Agrariasstress indexsoil moistureremote sensingCOMPUTERS IN OTHER SYSTEMSThe improvement of methods to evaluate the real impact of soil moisture availability on crop systems is crucial because the importance for world economy and food production. The relationship between the remote sensed stress index TVDI, root-zone soil moisture and soybean yield was analyzed in a sandy region of Argentine Pampas. High correlation (R2 =0.68) between TVDI and soybean yield was observed. The obtained adjustment allows us to evaluate the spatial variability of yield during a humid and dry period 2-3 months before harvest. Since the method requires remote sensed data, it could be applied over areas with poor data coverage.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2014-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf96-101http://sedici.unlp.edu.ar/handle/10915/42000enginfo:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/CAI/9.pdfinfo:eu-repo/semantics/altIdentifier/issn/1851-2526info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:01:14Zoai:sedici.unlp.edu.ar:10915/42000Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:01:14.409SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Spatial crop yield estimation based on remotely sensed stress index
title Spatial crop yield estimation based on remotely sensed stress index
spellingShingle Spatial crop yield estimation based on remotely sensed stress index
Holzman, Mauro
Ciencias Informáticas
Ciencias Agrarias
stress index
soil moisture
remote sensing
COMPUTERS IN OTHER SYSTEMS
title_short Spatial crop yield estimation based on remotely sensed stress index
title_full Spatial crop yield estimation based on remotely sensed stress index
title_fullStr Spatial crop yield estimation based on remotely sensed stress index
title_full_unstemmed Spatial crop yield estimation based on remotely sensed stress index
title_sort Spatial crop yield estimation based on remotely sensed stress index
dc.creator.none.fl_str_mv Holzman, Mauro
Rivas, Raúl
Bayala, Martín
Ocampo, Dora
Carmona, Facundo
author Holzman, Mauro
author_facet Holzman, Mauro
Rivas, Raúl
Bayala, Martín
Ocampo, Dora
Carmona, Facundo
author_role author
author2 Rivas, Raúl
Bayala, Martín
Ocampo, Dora
Carmona, Facundo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Ciencias Agrarias
stress index
soil moisture
remote sensing
COMPUTERS IN OTHER SYSTEMS
topic Ciencias Informáticas
Ciencias Agrarias
stress index
soil moisture
remote sensing
COMPUTERS IN OTHER SYSTEMS
dc.description.none.fl_txt_mv The improvement of methods to evaluate the real impact of soil moisture availability on crop systems is crucial because the importance for world economy and food production. The relationship between the remote sensed stress index TVDI, root-zone soil moisture and soybean yield was analyzed in a sandy region of Argentine Pampas. High correlation (R2 =0.68) between TVDI and soybean yield was observed. The obtained adjustment allows us to evaluate the spatial variability of yield during a humid and dry period 2-3 months before harvest. Since the method requires remote sensed data, it could be applied over areas with poor data coverage.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description The improvement of methods to evaluate the real impact of soil moisture availability on crop systems is crucial because the importance for world economy and food production. The relationship between the remote sensed stress index TVDI, root-zone soil moisture and soybean yield was analyzed in a sandy region of Argentine Pampas. High correlation (R2 =0.68) between TVDI and soybean yield was observed. The obtained adjustment allows us to evaluate the spatial variability of yield during a humid and dry period 2-3 months before harvest. Since the method requires remote sensed data, it could be applied over areas with poor data coverage.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
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