Reflectance Modeling of Snow-Covered Forests in Hilly Terrain

Seasonal snow covers large land areas of the Earth. Information about the snow extent in these regions is important for climate studies and water resource management. A linear spectral mixture model for snow-covered forests (the SnowFor model) has previously been developed for flat terrain. The SnowFor model includes reflectance components for snow, trees and snow-free ground. In this paper, the model is extended to handle radiometric effects caused by topography on mixed pixels of snow and trees through subpixel topographic reflectance modeling. Empirical reflectance models for snow and trees, based on the local solar incidence angle, are proposed (TopoSnow and TopoTree models), and integrated into the SnowFor model. Experiments with two Landsat Thematic Mapper (TM) images are carried out in hilly, forested terrain in Alptal, Switzerland with full snow cover. Results show that the calibrated TopoSnow and TopoTree models enhance the modeling of reflectance variability from snow-covered forests for visible and near-infrared wavelengths. The performance of four other topographic correction methods is evaluated for snow-covered forests.