Spectral reflectance behavior of different boreal snow types
Abstract Spectral reflectance of natural snow samples representing various stratigraphies was investigated in a controlled dark laboratory environment. Mean and Std dev. of band specific reflectance values were determined for several satellite sensor bands utilized in remote sensing of snow. The ref...
| Published in: | Journal of Glaciology |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Cambridge University Press (CUP)
2019
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1017/jog.2019.68 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143019000686 |
| Summary: | Abstract Spectral reflectance of natural snow samples representing various stratigraphies was investigated in a controlled dark laboratory environment. Mean and Std dev. of band specific reflectance values were determined for several satellite sensor bands utilized in remote sensing of snow. The reflectance values for dry, moist, wet and wet and littered snow for different instruments varied between 0.63–0.97 in the visible and near-infrared bands at an incoming light zenith angle of θ = 55°. The results indicate that in MODIS band 4 (545–565 nm), essential to snow mapping, the reflectance of snow drops by 9% when dry snow changes to wet snow and by a further 10% when typical forest litter inclusions exist on the wet snow surface. A separate investigation of individual snow types revealed that they can be grouped either as dry or wet snow based on their spectral behavior. However, some snow types were located between these two distinct groups, such as snow with near-surface melt-freeze crusts, and could not be clearly distinguished. The reflectance statistics collected and analyzed here can be directly used to refine accuracy characterization and parametrization of snow mapping algorithms, such as the SCAmod method, used for the mapping of snow cover area. |
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