Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data coll...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Peralta, Nahuel R., Assefa, Yared, Du, Juan, Barden, Charles J., Ciampitti, Ignacio A.
Formato: Objeto de conferencia Resumen
Lenguaje:Inglés
Publicado: 2018
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/70979
http://47jaiio.sadio.org.ar/sites/default/files/CAI-1.pdf
Aporte de:
id I19-R120-10915-70979
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
high-resolution satellite imagery
forecasting corn yields
spatial econometric
within-field variability
spellingShingle Ciencias Informáticas
high-resolution satellite imagery
forecasting corn yields
spatial econometric
within-field variability
Peralta, Nahuel R.
Assefa, Yared
Du, Juan
Barden, Charles J.
Ciampitti, Ignacio A.
Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield
topic_facet Ciencias Informáticas
high-resolution satellite imagery
forecasting corn yields
spatial econometric
within-field variability
description A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at midgrowing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington) of Kansas (total of 457 ha). Three basic tests were conducted on the data: (1) spatial dependence on each of the yield and vegetation indices (VIs) using Moran’s I test; (2) model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS) and spatial econometric (SPL) models; and (3) model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test) for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG) was tested positive and statistically significant for most of the fields (p < 0.05), except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02) was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to inform precision agricultural management decisions.
format Objeto de conferencia
Resumen
author Peralta, Nahuel R.
Assefa, Yared
Du, Juan
Barden, Charles J.
Ciampitti, Ignacio A.
author_facet Peralta, Nahuel R.
Assefa, Yared
Du, Juan
Barden, Charles J.
Ciampitti, Ignacio A.
author_sort Peralta, Nahuel R.
title Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield
title_short Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield
title_full Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield
title_fullStr Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield
title_full_unstemmed Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield
title_sort mid-season high-resolution satellite imagery for forecasting site-specific corn yield
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/70979
http://47jaiio.sadio.org.ar/sites/default/files/CAI-1.pdf
work_keys_str_mv AT peraltanahuelr midseasonhighresolutionsatelliteimageryforforecastingsitespecificcornyield
AT assefayared midseasonhighresolutionsatelliteimageryforforecastingsitespecificcornyield
AT dujuan midseasonhighresolutionsatelliteimageryforforecastingsitespecificcornyield
AT bardencharlesj midseasonhighresolutionsatelliteimageryforforecastingsitespecificcornyield
AT ciampittiignacioa midseasonhighresolutionsatelliteimageryforforecastingsitespecificcornyield
bdutipo_str Repositorios
_version_ 1764820482043936768