Estimating snow grain size using AVIRIS data

Abstract

Estimates of snow grain size for the near-surface snow layer were calculated for the Tioga Pass region and Mammoth Mountain in the Sierra Nevada, California, using an inversion technique and data collected by the Airborne Visible / Infrared Imaging Spectrometer (AVIRIS). The inversion method takes advantage of the sensitivity of near-infrared snowpack reflectance to snow grain size. The Tioga Pass and Mammoth Mountain single-band AVIRIS radiance images were atmospherically corrected to obtain surface reflectance. Given the solar and viewing geometry for the time and location of each AVIRIS overflight, a discrete-ordinate model was used to calculate directional reflectance as a function of snowpack grain size, for a wide range of snow grain radii. The resulting radius vs. reflectance curves were each fit using a nonlinear least-squares technique which provided a means of transforming surface reflectance in each AVIRIS image to optically equivalent grain size on a per-pixel basis. This inversion technique has been validated using a combination of ground-based reflectance measurements and grain size measurements derived from stereologic analysis of snow samples for a wide range of snow grain sizes. The model results and grain size estimates derived from the AVIRIS data show that, for solar incidence angles between 0° and 30°, the technique provides good estimates of grain size. Otherwise, the local angle of solar incidence must be known more exactly. This work provides the first quantitative estimates for grain size using data acquired from an airborne remote sensing instrument and is an important step in improving our ability to retrieve snow physical properties independent of field measurements.