Author(s)

Davinder Singh, Rajender Singh

Department of Geography, University of Jammu, Jammu, India.

Due to the high number of bands in the hyperspectral image, the selection of optimum bands for crop classification is a prerequisite. The Hyperion sensor has 242 spectral bands out of which 143 useable bands were selected. The bands reflected wavelength from 400 to 1000 nm to the VNIR spectrometer and transmitted the band from 900 to 2500 nm to the SWIR spectrometer. Spectral Angle Mapping Classification (SAMC) approach and a multi-scale object oriented method are applied for crop studies. The result obtained from the accuracy assessment by comparing Ground Control Points (GCP) with the help of image spectra shows 78% of overall accuracy. This shows that these data are highly useful in studying the crop diversification.

Hyperspectal Remote Sensing, Hyperion Data, Spectral Angle Mapping Classification

Singh, D. and Singh, R. (2015) Evaluation of EO-1 Hyperion Data for Crop Studies in Part of Indo-Gangatic Plains: A Case Study of Meerut District. Advances in Remote Sensing, 4, 263-269. doi: 10.4236/ars.2015.44021.