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

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Absztrakt

Due 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.

Leírás
Kulcsszavak
Landsat, Wheat yield, NDVI, SAVI, Forecasting
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