LAUSR

ABSTRACT Radiative transfer theory based retrievals of effective snow grain size (SGS), albedo were widely explored using hyper-spectral sensors. However, investigation of linkage between diagnostic absorption peak characteristics (PCs) and snow surface parameters remained scarce, though these are significant to determine composition and state of material. In present study, field data acquired during three winter seasons was analyzed to study variability of effective SGS with PCs (i.e. relative depth, peak position and asymmetry). Effective SGS was found positively correlated with relative depth, with correlation of 90% and 86% for absorption peaks around 1.24 µm and 1.03 µm respectively. Asymmetry was found in good correlation with SGS (74%) at 1.24 µm than at 1.03 µm (21%). Further, PCs were derived using Hyperion data in ENVI software on pixel basis. Significance of PCs is described and compared with effective SGS, which was retrieved using widely accepted Asymptotic Radiative Transfer model. This work provide an alternate approach to infer state of snow metamorphism using peak characteristics, in scarcity of reference spectral database of snow classes.