| Summary: | The topic of this dissertation is the seasonal snow surface roughness and albedo. These are studied using optical satellite data and terrestrial laser scanning. The use of remote sensing data requires knowledge on the optical properties of the measured surface. For snow, these properties are affected by surface roughness. In this dissertation, two different methods for measuring snow surface roughness were validated and used in the field. One of them is based on plate photography. It is easy to use in the field and able to study surface features in sub-millimeter scale. The other method is based on mobile laser scanning and is able to produce 3D surface descriptions of large areas. The plate-photography-based method was used in the field to gather 669 profiles of the snow surface. The profiles were analyzed using multiscale parameters. The validation of satellite data requires observations at the surface. This validation data typically consists of pointwise measurements, whereas the satellite data observations cover larger areas. Laser scanning provides data that cover larger areas, thus more in line with the satellite data. This could in the future be used for satellite data validation. The usability of laser scanning data on snow surfaces was improved by studying the incidence angle dependency of the laser scanning intensity data on different snow types. A function for correcting the incidence angle effect on all measured snow types was developed. The backscattering of laser beam on snow surface was found to take place at the very surface for dry snow, and within 1cm depth for wet snow. The final part of this dissertation studies the changes in surface albedo prior to melting and the timing of the melt season in Northern Hemisphere land areas between 40°N and 80°N. The albedo prior to melt had changed significantly in the boreal forest area, but not in the tundra. The direction of change is different in different areas. The melt season takes place at the same time of year for most of the study area, but for ...
|
|---|