Use of vegetation index and meteorological parameters for the prediction of crop yield in India
Monsoon rainfall distribution over the Indian sub-continent is inconsistent every year. Due to uncertainty and dependence on the monsoon onset and weather conditions, estimation of crop yield in India is difficult. In this paper, analyses of the crop yield, normalized difference vegetation index, soil moisture, surface temperature and rainfall data for 16 years (from 1984 to 1999) have been carried out. A non-linear iterative multivariate optimization approach (quasi-Newton method with least square loss function) has been used to derive an empirical piecewise linear crop yield prediction equation (with a break point). The derived empirical equation (based on 1984 to 1998 data) has been used to predict 1999 crop yield with R2>0.90. The model has been validated for the three years 1997, 1998 and 1999. A crop yield prediction equation has been obtained for each province in India (for wheat and rice) that accounts for>90% of the variance in the dataset.
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Document Type: Research Article
Department of Civil Engineering, Indian Institute of Technology, Kanpur, 208 016, India
Department of Civil Engineering, Indian Institute of Technology, Kanpur, 208 016, India,Center for Earth Observing and Space Research, College of Sciences, George Mason University, Fairfax, VA 22030
Center for Earth Observing and Space Research, College of Sciences, George Mason University, Fairfax, VA 22030
Publication date: 2007-01-01
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