Use of Satellite Imagery for Estimating Sowing Dates of Wheat in Uttaranchal, India

A.S. Nain, K.C. Kersebaum, and V.K. Dadhwal (India)


Modelling, Remote Sensing, Agriculture, Wheat


The information on sowing dates of crop is an important step for the forecast of the crop yield. Remotely sensed data can be a valuable tool when crop models are applied in a GIS environment for simulating regional behavior of crop. An attempt has been made in the present study to derive sowing information using satellite-based imageries. LISS-III (Linear Imaging Self-Scanning) imageries of Indian Remote sensing Satellite (IRS) containing information on Agriculture-farm of GBPUA&T, Pantnagar, India, have been acquired for the period of 1996-97 to 1999-2000. A spectral profile of active vegetative growth stage of wheat was generated and regressed with DAS (days after sowing). A Normalized Difference Vegetation Index (NDVI) based model was developed for estimating sowing dates of wheat. The data of 24 plots were used for obtaining coefficients for exponential based model, while performance of the model was tested for independent 12 plots. Analysis showed that model could estimate sowing date with a minimum difference of 1 day and maximum difference of 24 days with an average deviation of 8 days. The Standard Error of the Estimate was 9.22 for the estimates made after an average of 78 DAS for the all plots, while it was 10.24 in the calibration period and 6.42 in the prediction period.

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