Snowcover mapping with the Airborne Visible/Infrared Imaging Spectrometer

Abstract

In alpine areas where rugged topography inhibits snow mapping from the ground, remote sensing data allows us to acquire snowmelt model input data that would typically be unavailable. In this research, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected over Mammoth Mountain in the Sierra Nevada, California. Both snow covered area and snow grain size are important inputs for spatially-distributed snowmelt, models and for models that require spatial estimates of snow albedo. Spectral mixture analysis was used to derive the fraction of snow covered area in each AVIRIS image pixel. When compared with snowcover estimates from concurrent aerial photographs, this mapping technique was found to be accurate even for snowcover in partially shadowed and vegetated areas. Snow grain size was mapped using an inversion model that relates an ice absorption feature centered at 1.03 /spl mu/m to an optically-equivalent grain size. The magnitude of both the depth and area of this ice absorption feature are sensitive to snow grain size; the area calculation has been found to be insensitive to signal noise. Image analysis using a digital elevation model of the study area has shown that grain size estimates ace independent of topographic illumination effects so this method is particularly useful in topographically complex regions. To validate the inversion algorithm, snow samples from Mammoth Mountain were collected over a wide range of slopes, aspects, and elevations. These samples were analyzed to determine grain size, density and dust concentrations. These results show that grain sizes retrieved from the AVIRIS image data closely correspond to those of the snow samples. Snowpack density and dust concentrations do not appear to have had any effect on the image data estimates. The combination of aerial photographs, ground reflectance measurements, snow samples, and AVIRIS data have provided us with a validation for both the snow covered area and grain size mapping techniques. >