Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics

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dc.contributor.authorDempewolf, Jan
dc.contributor.authorAdusei, Bernard
dc.contributor.authorBecker-Reshef, Inbal
dc.contributor.authorHansen, Matthew
dc.contributor.authorPotapov, Peter
dc.contributor.authorKhan, Ahmad
dc.contributor.authorBarker, Brian
dc.date.accessioned2024-01-23T17:17:40Z
dc.date.available2024-01-23T17:17:40Z
dc.date.issued2014-10-13
dc.description.abstractPolicy makers, government planners and agricultural market participants in Pakistan require accurate and timely information about wheat yield and production. Punjab Province is by far the most important wheat producing region in the country. The manual collection of field data and data processing for crop forecasting by the provincial government requires significant amounts of time before official reports can be released. Several studies have shown that wheat yield can be effectively forecast using satellite remote sensing data. In this study, we developed a methodology for estimating wheat yield and area for Punjab Province from freely available Landsat and MODIS satellite imagery approximately six weeks before harvest. Wheat yield was derived by regressing reported yield values against time series of four different peak-season MODIS-derived vegetation indices. We also tested deriving wheat area from the same MODIS time series using a regression-tree approach. Among the four evaluated indices, WDRVI provided more consistent and accurate yield forecasts compared to NDVI, EVI2 and saturation-adjusted normalized difference vegetation index (SANDVI). The lowest RMSE values at the district level for forecast versus reported yield were found when using six or more years of training data. Forecast yield for the 2007/2008 to 2012/2013 growing seasons were within 0.2% and 11.5% of final reported values. Absolute deviations of wheat area and production forecasts from reported values were slightly greater compared to using the previous year’s or the three- or six-year moving average values, implying that 250-m MODIS data does not provide sufficient spatial resolution for providing improved wheat area and production forecasts.
dc.description.urihttps://doi.org/10.3390/rs6109653
dc.identifierhttps://doi.org/10.13016/dspace/b6kn-d2qv
dc.identifier.citationDempewolf, J.; Adusei, B.; Becker-Reshef, I.; Hansen, M.; Potapov, P.; Khan, A.; Barker, B. Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics. Remote Sens. 2014, 6, 9653-9675.
dc.identifier.urihttp://hdl.handle.net/1903/31591
dc.language.isoen_US
dc.publisherMDPI
dc.relation.isAvailableAtCollege of Behavioral & Social Sciencesen_us
dc.relation.isAvailableAtGeographyen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.subjectagriculture
dc.subjectwheat
dc.subjectyield
dc.subjectproduction
dc.subjectforecast
dc.subjectMODIS
dc.subjectWDRVI
dc.titleWheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics
dc.typeArticle
local.equitableAccessSubmissionNo

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