Iterative atmospheric correction scheme and the polarization color of alpine snow

Abstract

Proper characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of intensity-only measurements is overwhelmed by instruments with polarization capabilities. Because of their remarkable lack of spectral contrast, the polarized reflectances of land surfaces in the shortwave infrared spectral region (where atmospheric scattering is minimal) can be used to model the surface at shorter wavelengths, where aerosol retrievals are performed.