| Abstract [eng] |
The main aim of this dissertation thesis was to develop a snow cover detection methodology using various satellite sensors. The scope of satellite Earth observations is increasing every year, but different satellite sensors have different operating principles, resolution and revisit frequency. To obtain useful information about the snow cover, specialised satellite data processing algorithms are needed. In this dissertation, algorithms and methods were developed to take advantage of different sensors to: 1) determine snowfall cases using data from passive microwave sensors; 2) fill the cloud-gaps in the snow cover products based on visible satellite sensors; 3) determine snow cover in different land cover types using synthetic aperture radar; 4) increase resolution of satellite snow water equivalent product using high resolution auxiliary data. This study focuses on the snow cover parameters and their monitoring in the Baltic States, but the proposed methodology can be applied to any region in the midlatitudes, with elevation lower than 500 m. The number of ground-based snow cover measurements in the Baltic States is declining and satellite data can be used to fill this observation gap. The satellite data processing methodology proposed in this thesis can be applied for seasonal snow cover monitoring and long-term climate trends detection. |
