A Hyperspectral Method for Remotely Sensing the Grain Size of Snow

We have developed a robust, accurate inversion technique for estimating the grain size in a snowpack's surface layer from imaging spectrometer data. Using a radiative transfer model, the method relates an ice absorption feature, centered at λ=1.03 μm, to the optically equivalent snow grain size...

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Bibliographic Details
Published in:Remote sensing of environment 2000-11, Vol.74 (2), p.207-216
Main Authors: Nolin, Anne W, Dozier, Jeff
Format: Article
Language:English
Subjects:
Applied geophysics
Earth sciences
Earth, ocean, space
Exact sciences and technology
Grain size and shape
Hydrology
Hydrology. Hydrogeology
Internal geophysics
Light absorption
Light reflection
Parameter estimation
Snow
Spectrometers
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Summary:We have developed a robust, accurate inversion technique for estimating the grain size in a snowpack's surface layer from imaging spectrometer data. Using a radiative transfer model, the method relates an ice absorption feature, centered at λ=1.03 μm, to the optically equivalent snow grain size. Because the interpretation is based on the area—not depth—of the absorption feature scaled to absolute reflectance, the method is insensitive to instrument noise and does not require a topographic correction. We tested the method using Airborne Visible/Infrared Imaging Spectrometer data over the eastern Sierra Nevada, California, and we validated it with a combination of ground-based spectrometer data and grain size measurements.
ISSN:0034-4257
1879-0704
DOI:10.1016/S0034-4257(00)00111-5