Publication Type:

Journal Article


Journal of Chemical and Pharmaceutical Sciences, SPB Pharma Society, Volume 9, Number 1, p.489-493 (2016)



Rice is one of the routinely consumed diets of Kerala that is commonly cultivated in Palakkad and Malappuram districts. The study here describes the disparity in paddy yield based on different disease infestation levels on paddy crops by analyzing hyper spectral data that are obtained from the EO-1 Hyperion Sensor. In an optical wavelength range the hyper spectral data contains a large number of narrow spectral channels, and they can vary from several tens to a few hundred in number. In this paper, remote sensing technology is used to recognize disease infested plants based on the spectral reflectance of each band in the image; spectral reflectance may change according to the chlorophyll contents. Hyper spectral data is preprocessed using ERDAS IMAGINE 9.2 software. An end member spectrum is then developed by unsupervised classification (K-Mean algorithm) using ENVI 4.7, for automatically cluster pixels to each classes namely, high yield, low yield, moderate yield, and severe yield. The cultivation of rice crop in tonnes of grains per hectare area (6257.11ha) for different variety is determined as an outcome of this study.


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Cite this Research Publication

Pa Kavitha and Sundaram, G. A. Shanmugha, “Yield per hectare of rice crop from EOS hyperspectral data analysis”, Journal of Chemical and Pharmaceutical Sciences, vol. 9, pp. 489-493, 2016.