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Nolin, A.W., and Selkowitz, D., (2004). Multi-angle/Multi-spectral Mapping of Snow Covered Area and Vegetation Density Using MISR. Eos Trans. AGU, 85(47), Fall Meet. Suppl. 2004, Abstract # C31A-0281

Vegetation structure and density affect the dynamics of snow accumulation and ablation. The presence of vegetation also affects our ability to accurately estimate snow-covered area (SCA) from satellite-based sensors. The objective of this case study is to simultaneously retrieve subpixel estimates of snow covered area and vegetation density from multi-angle imagery. Imagery from the Multi-angle Imaging SpectroRadiometer (MISR) was acquired over Glacier National Park and a portion of the Colorado Rocky Mountains. Vegetation density can be related to the shape of the angular signature for a pixel. Here, we invert the Rahman-Pinty-Verstraete (RPV) model to compute values of a semi-empirical parameter (the k-parameter) that is statistically correlated with vegetation density. For the same pixels, we perform linear spectral unmixing using the four-band multi-spectral data at each of the nine MISR viewing angles. In areas with a mixture of vegetation and snow, SCA estimates vary as a function of viewing angle and vegetation density. Using both the multi-angle and multi-spectral data from MISR, we are able formulate corrections for SCA estimates based on the vegetation density. Moreover, the vegetation density information itself is an important retrieved parameter that can be used in snowmelt/runoff models.

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Updated: 14-Jan-2005