Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina

Autores
Lopresti, Mariano F.; Di Bella, Carlos Marcelo; Degioanni, Americo
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In countries like Argentina, whose economy depends heavily on crop production, the estimation of harvests is an elementary requirement. Besides providing objectivity, the use of remote sensing allows estimating yield in advance. Since the time of maximum leaf area in wheat corresponds with the critical period of the crop, a good relationship is expected between the Normalized Difference Vegetation Index (NDVI) and yield. The present study was carried out in the North of Buenos Aires province, Argentina. Based on the type of soil, the study area can be divided into two homogeneous subzones: a subzone with lower clay content in the southwest and a subzone with higher clay content in the northeast. Nine growing seasons (2003–2011) were studied. In the first five years, an empirical model was calibrated and validated with field-observed wheat yields and MOD13q1 product-NDVI data, whereas in the other four years, the calibrated model was applied by means of yield maps and by comparing with official yields. The MOD13q1 image corresponding to Julian day 289 showed the best fit between NDVI and yield to estimate wheat yield early. Through yield maps, better weather conditions showed higher yields and higher soil productivity presented a greater proportion of the area occupied by higher yields. At department level, an R2 value of 0.75 was found after relating the estimation of the calibrated empirical model with official yields. The method used allows predicting wheat yield 30 days before harvest. Through yield maps, the NDVI perceived the temporal and spatial variability in the study area.
Fil: Lopresti, Mariano F.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Di Bella, Carlos Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Degioanni, Americo. Universidad Nacional de Rio Cuarto. Facultad de Agronomia y Veterinaria. Departamento de Ecología Agraria; Argentina
Materia
Empirical Models
Modis
Ndvi
Remote Sensing
Wheat
Yield
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/56173
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, ArgentinaLopresti, Mariano F.Di Bella, Carlos MarceloDegioanni, AmericoEmpirical ModelsModisNdviRemote SensingWheatYieldhttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4In countries like Argentina, whose economy depends heavily on crop production, the estimation of harvests is an elementary requirement. Besides providing objectivity, the use of remote sensing allows estimating yield in advance. Since the time of maximum leaf area in wheat corresponds with the critical period of the crop, a good relationship is expected between the Normalized Difference Vegetation Index (NDVI) and yield. The present study was carried out in the North of Buenos Aires province, Argentina. Based on the type of soil, the study area can be divided into two homogeneous subzones: a subzone with lower clay content in the southwest and a subzone with higher clay content in the northeast. Nine growing seasons (2003–2011) were studied. In the first five years, an empirical model was calibrated and validated with field-observed wheat yields and MOD13q1 product-NDVI data, whereas in the other four years, the calibrated model was applied by means of yield maps and by comparing with official yields. The MOD13q1 image corresponding to Julian day 289 showed the best fit between NDVI and yield to estimate wheat yield early. Through yield maps, better weather conditions showed higher yields and higher soil productivity presented a greater proportion of the area occupied by higher yields. At department level, an R2 value of 0.75 was found after relating the estimation of the calibrated empirical model with official yields. The method used allows predicting wheat yield 30 days before harvest. Through yield maps, the NDVI perceived the temporal and spatial variability in the study area.Fil: Lopresti, Mariano F.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; ArgentinaFil: Di Bella, Carlos Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; ArgentinaFil: Degioanni, Americo. Universidad Nacional de Rio Cuarto. Facultad de Agronomia y Veterinaria. Departamento de Ecología Agraria; ArgentinaChina Agricultural University2015-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/56173Lopresti, Mariano F.; Di Bella, Carlos Marcelo; Degioanni, Americo; Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina; China Agricultural University; Information Processing in Agriculture; 2; 2; 9-2015; 73-842214-3173CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.inpa.2015.06.001info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S221431731500027Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:44:30Zoai:ri.conicet.gov.ar:11336/56173instacron: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 09:44:30.38CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
title Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
spellingShingle Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
Lopresti, Mariano F.
Empirical Models
Modis
Ndvi
Remote Sensing
Wheat
Yield
title_short Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
title_full Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
title_fullStr Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
title_full_unstemmed Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
title_sort Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
dc.creator.none.fl_str_mv Lopresti, Mariano F.
Di Bella, Carlos Marcelo
Degioanni, Americo
author Lopresti, Mariano F.
author_facet Lopresti, Mariano F.
Di Bella, Carlos Marcelo
Degioanni, Americo
author_role author
author2 Di Bella, Carlos Marcelo
Degioanni, Americo
author2_role author
author
dc.subject.none.fl_str_mv Empirical Models
Modis
Ndvi
Remote Sensing
Wheat
Yield
topic Empirical Models
Modis
Ndvi
Remote Sensing
Wheat
Yield
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv In countries like Argentina, whose economy depends heavily on crop production, the estimation of harvests is an elementary requirement. Besides providing objectivity, the use of remote sensing allows estimating yield in advance. Since the time of maximum leaf area in wheat corresponds with the critical period of the crop, a good relationship is expected between the Normalized Difference Vegetation Index (NDVI) and yield. The present study was carried out in the North of Buenos Aires province, Argentina. Based on the type of soil, the study area can be divided into two homogeneous subzones: a subzone with lower clay content in the southwest and a subzone with higher clay content in the northeast. Nine growing seasons (2003–2011) were studied. In the first five years, an empirical model was calibrated and validated with field-observed wheat yields and MOD13q1 product-NDVI data, whereas in the other four years, the calibrated model was applied by means of yield maps and by comparing with official yields. The MOD13q1 image corresponding to Julian day 289 showed the best fit between NDVI and yield to estimate wheat yield early. Through yield maps, better weather conditions showed higher yields and higher soil productivity presented a greater proportion of the area occupied by higher yields. At department level, an R2 value of 0.75 was found after relating the estimation of the calibrated empirical model with official yields. The method used allows predicting wheat yield 30 days before harvest. Through yield maps, the NDVI perceived the temporal and spatial variability in the study area.
Fil: Lopresti, Mariano F.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Di Bella, Carlos Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Degioanni, Americo. Universidad Nacional de Rio Cuarto. Facultad de Agronomia y Veterinaria. Departamento de Ecología Agraria; Argentina
description In countries like Argentina, whose economy depends heavily on crop production, the estimation of harvests is an elementary requirement. Besides providing objectivity, the use of remote sensing allows estimating yield in advance. Since the time of maximum leaf area in wheat corresponds with the critical period of the crop, a good relationship is expected between the Normalized Difference Vegetation Index (NDVI) and yield. The present study was carried out in the North of Buenos Aires province, Argentina. Based on the type of soil, the study area can be divided into two homogeneous subzones: a subzone with lower clay content in the southwest and a subzone with higher clay content in the northeast. Nine growing seasons (2003–2011) were studied. In the first five years, an empirical model was calibrated and validated with field-observed wheat yields and MOD13q1 product-NDVI data, whereas in the other four years, the calibrated model was applied by means of yield maps and by comparing with official yields. The MOD13q1 image corresponding to Julian day 289 showed the best fit between NDVI and yield to estimate wheat yield early. Through yield maps, better weather conditions showed higher yields and higher soil productivity presented a greater proportion of the area occupied by higher yields. At department level, an R2 value of 0.75 was found after relating the estimation of the calibrated empirical model with official yields. The method used allows predicting wheat yield 30 days before harvest. Through yield maps, the NDVI perceived the temporal and spatial variability in the study area.
publishDate 2015
dc.date.none.fl_str_mv 2015-09
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/11336/56173
Lopresti, Mariano F.; Di Bella, Carlos Marcelo; Degioanni, Americo; Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina; China Agricultural University; Information Processing in Agriculture; 2; 2; 9-2015; 73-84
2214-3173
CONICET Digital
CONICET
url http://hdl.handle.net/11336/56173
identifier_str_mv Lopresti, Mariano F.; Di Bella, Carlos Marcelo; Degioanni, Americo; Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina; China Agricultural University; Information Processing in Agriculture; 2; 2; 9-2015; 73-84
2214-3173
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.inpa.2015.06.001
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S221431731500027X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv China Agricultural University
publisher.none.fl_str_mv China Agricultural University
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 13.070432

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