Evaluation of hyperspectral indices for LAI estimation and discrimination of potato crop under different irrigation treatments

Abstract

In this study, various hyperspectral indices were evaluated for estimation of leaf area index (LAI) and crop discrimination under different irrigation treatments. The study was conducted for potato crop using the spectral reflectance values measured by a hand‐held spectro‐radiometer. Three categories of hyperspectral indices, such as ratio/difference indices, multivariate indices and derivative based indices were computed. It was found that, among various band combinations for NDVI (normalized difference vegetation index) and SAVI (soil adjusted vegetation index), the band combination of the 780∼680, produced highest correlation coefficient with LAI. Among all the forms of LAI and VI empirical relationships, the power and exponential equations had highest R 2 and F values. Analysis of variance showed that, hyperspectral indices were found to be more efficient than the LAI to detect the differences among crops under different irrigation treatments. The discriminant analysis produced a set of five most optimum bands to discriminate the crops under three irrigation treatments.