Wheat yield forecasting based on landsat vegetation indices time series data and reported crop statistics

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dc.contributor.advisorNagy, Attila
dc.contributor.authorAdeniyi, Odunayo David
dc.contributor.departmentDE--Mezőgazdaság- Élelmiszertudományi és Környezetgazdálkodási Karhu_HU
dc.date.accessioned2020-04-27T15:01:19Z
dc.date.available2020-04-27T15:01:19Z
dc.date.created2020-04-24
dc.description.abstractDue to increase demand of food grain in the world, assessment of yield before actual production is important in making policies and decision in agricultural production system. In this study, wheat yield forecast was derived by regressing ground truthing yield data against time series of spatial vegetation indices. These spatial vegetation indices derived from Landsat 8 image data: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Soil Adjusted Vegetation Index (SAVI) were compared to evaluate the most appropriate index that performs better in forecasting wheat production at Karcag, Kunhegyes and Ecsegfalva settlements in Jász-Nagykun-Szolnok county, in the Northern Great Plain region of central Hungary.hu_HU
dc.description.courseAgricultural Environmental Management Engineeringhu_HU
dc.description.degreeMSc/MAhu_HU
dc.format.extent40hu_HU
dc.identifier.urihttp://hdl.handle.net/2437/285068
dc.language.isoenhu_HU
dc.subjectLandsathu_HU
dc.subjectWheat yieldhu_HU
dc.subjectNDVIhu_HU
dc.subjectSAVIhu_HU
dc.subjectForecastinghu_HU
dc.subject.dspaceDEENK Témalista::Környezettudományokhu_HU
dc.subject.dspaceDEENK Témalista::Mezőgazdaságtudományhu_HU
dc.titleWheat yield forecasting based on landsat vegetation indices time series data and reported crop statisticshu_HU
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