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

Autores
Lopresti, Mariano Francisco; Di Bella, Carlos Marcelo; Degioanni, Américo José
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 Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Degioanni, Américo José. Universidad Nacional Río Cuarto, Facultad de Agronomía y Veterinaria, Departamento de Ecología Agraria; Argentina
Materia
Trigo
Cubierta Vegetal
Sensores
Sensors
Modelos de Simulación
Rendimiento
Teledetección
Técnicas de Predicción
Plant Cover
Simulation Models
Yields
Remote Sensing
Forecasting
Climatic Factors
Buenos Aires
Sensores Remotos
MODIS-NDVI
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/1236

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spelling Relationship between MODIS-NDVI data and wheat yield : a case study in northern Buenos Aires province, ArgentinaLopresti, Mariano FranciscoDi Bella, Carlos MarceloDegioanni, Américo JoséTrigoCubierta VegetalSensoresSensorsModelos de SimulaciónRendimientoTeledetecciónTécnicas de PredicciónPlant CoverSimulation ModelsYieldsRemote SensingForecastingClimatic FactorsBuenos AiresSensores RemotosMODIS-NDVIIn 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 Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; ArgentinaFil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Degioanni, Américo José. Universidad Nacional Río Cuarto, Facultad de Agronomía y Veterinaria, Departamento de Ecología Agraria; Argentina2017-09-18T13:43:23Z2017-09-18T13:43:23Z2015-07-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/1236http://www.sciencedirect.com/science/article/pii/S221431731500027X2214-3173https://doi.org/10.1016/j.inpa.2015.06.001engBuenos Aires (province)info:eu-repo/semantics/restrictedAccessreponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuaria2025-09-29T13:44:10Zoai:localhost:20.500.12123/1236instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:10.97INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
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 Francisco
Trigo
Cubierta Vegetal
Sensores
Sensors
Modelos de Simulación
Rendimiento
Teledetección
Técnicas de Predicción
Plant Cover
Simulation Models
Yields
Remote Sensing
Forecasting
Climatic Factors
Buenos Aires
Sensores Remotos
MODIS-NDVI
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 Francisco
Di Bella, Carlos Marcelo
Degioanni, Américo José
author Lopresti, Mariano Francisco
author_facet Lopresti, Mariano Francisco
Di Bella, Carlos Marcelo
Degioanni, Américo José
author_role author
author2 Di Bella, Carlos Marcelo
Degioanni, Américo José
author2_role author
author
dc.subject.none.fl_str_mv Trigo
Cubierta Vegetal
Sensores
Sensors
Modelos de Simulación
Rendimiento
Teledetección
Técnicas de Predicción
Plant Cover
Simulation Models
Yields
Remote Sensing
Forecasting
Climatic Factors
Buenos Aires
Sensores Remotos
MODIS-NDVI
topic Trigo
Cubierta Vegetal
Sensores
Sensors
Modelos de Simulación
Rendimiento
Teledetección
Técnicas de Predicción
Plant Cover
Simulation Models
Yields
Remote Sensing
Forecasting
Climatic Factors
Buenos Aires
Sensores Remotos
MODIS-NDVI
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 Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Degioanni, Américo José. Universidad Nacional Río Cuarto, Facultad de Agronomía 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 2015-07-18
2017-09-18T13:43:23Z
2017-09-18T13:43:23Z
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/20.500.12123/1236
http://www.sciencedirect.com/science/article/pii/S221431731500027X
2214-3173
https://doi.org/10.1016/j.inpa.2015.06.001
url http://hdl.handle.net/20.500.12123/1236
http://www.sciencedirect.com/science/article/pii/S221431731500027X
https://doi.org/10.1016/j.inpa.2015.06.001
identifier_str_mv 2214-3173
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Buenos Aires (province)
dc.source.none.fl_str_mv reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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