Snow grain size mapping using EO-1 Hyperion imagery in the Himalayan region, India

Sandeep Kumar Kaushik; Varun Narayan Mishra; Milap Punia

Sandeep Kumar Kaushik Weather Risk Management Services Pvt. Ltd., Gurugram, India
Varun Narayan Mishra Department of Physics, Indian Institute of Technology (BHU), Varanasi, India
Milap Punia Centre for the Study of Regional Development, Jawaharlal Nehru University, New Delhi, Indi

Abstract

It is complicated and time consuming to use traditional ground survey methods to study the physical properties of snow over vast and inaccessible areas. However, the emergence of Hyperspectral remote sensing provides a convenient and powerful tool for studying the physical properties of snow. This study demonstrates the potential of EO-1 Hyperion imagery for the estimation and mapping of one of snow physical parameters (i.e. snow grain size) in the Himalayan region, India. The analysis process consists of Fast Line-of-sight Atmospheric Analysis of SpectralHypercubes (FLAASH) to retrieve surface reflectance. The spectral reflectance of different types of snow grain size, debris cover and barren/rocky has been collected using image derived spectra. Snow grain size has been estimated using spectral angle mapper (SAM) algorithm. This study reveals the relatively high accuracy of the estimation and mapping of snow grain size classes i.e. fine, medium and coarse using SAM theory based on the Hyperion imagery.