Abstract
Background: For a primarily agriculture-based country like India, reliable, accurate and timely information on types of crops grown, their acreages and yield are of vital importance. In this study, attempts have been made to predict wheat crop yield in Saharanpur district of Uttar Pradesh for the year 2016-17 using various spectral indices (Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, Ratio Vegetation Index and Transformed Normalized Difference Vegetation Index) and agrometeorological variables. Methods: The spectral indices were derived using agrometeorological data (Growing Degree Days, Temperature Difference and Helio Thermal Units) and the ground truth information was collected using the Global Positioning System in the field. Observed acreage data for the wheat crop were collected from the Saharanpur district headquarter. Result: The NDVI showed the highest correlation with wheat crop yield. The spectral yield model using only the NDVI showed an R2 value of 0.81 with an RMSE of 88.02 kg/ha. However, by incorporating the NDVI with temperature, the model shows much better performance with an R2 value of 0.95 and an RMSE of 49.86 kg/ha. The rainfall showed lesser correlation with the wheat crop yield as compared to the temperature, probably due to ground water dominated region.
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