Identification of Optimal Absorbance Spectral Bands from Aviris-Ng Using Standard Derivative Analysis

Abstract

The high dimensional hyperspectral data due to its narrow bands ranging between 250-3500 nm, becomes a serious issue for data processing and analysis. Selection of optimal absorbance spectral bands from original spectra brings great possibility in removing the redundancy, quantifying pigments such as chlorophyll, carotenoids, anthocyanin and the retrieval of biophysical variables such as LAI, Biomass corresponding to crops using advance derivative techniques. As part of this study atmospheric corrected reflectance AVIRIS-NG (Airborne Visible Infrared Imaging Spectroradiometer-Next Generation) hyperspectral sensor data over Anand study site on wheat crop were used. Two well proven techniques continuum removal and second derivative were used for the identification of absorption bands and also useful to capture the subtle difference in the spectra required in order to locate any specific feature present in the spectra. In the continuum removed graph, chlorophyll reflection is observed in the green region of electromagnetic spectrum, in red region a peak of reflection is observed due to the presence of carotenoid pigment, and in the NIR (Near - Infrared) region dip is observed due to the presence of anthocyanins pigment and Leaf area index. Therefore, findings of the study might be useful to separate and better identification of absorption bands of biophysical and biochemical parameters presence in crop spectra. which indicated that they can be used for species identification of any crop. © 2022 IEEE.