A Constrained Spectral Unmixing Approach to Snow- Cover Mapping in Forests using MODIS Data

A snow-cover mapping method accounting for forests (SnowFrac) is presented. SnowFrac uses spectral unmixing and endmember constraints to estimate the snow-cover fraction of a pixel. The unmixing is based on a linear spectral mixture model, which includes endmembers for snow, coniferous trees, branches of leafless deciduous trees and snow-free ground. Model input consists of a land-cover fraction map and endmember spectra. The land-cover fraction map is applied in the unmixing procedure to identify the number and types of endmembers for every pixel, but also to set constraints on the area fractions of the forest endmembers. Results are presented for non-forested areas, deciduous forests, coniferous forests and mixed deciduous/coniferous forests. Results are also compared to the MODIS L2 500 m snow product. Keywords-component; snow-cover mapping, forest, optical remote sensing, MODIS.