One of the objectives of the SnowBall project was to develop new methods and algorithms to extract snow parameters from optical and radar satellite. The Multi-sensor/multi-temporal Wet Snow (MWS) algorithm is novelty of this project, and fuses optical and SAR data to map the wet snow area. The idea was to combine multi temporal observations of optical and SAR wet snow in a fusion model to generate improved coverage in space and time. The developed algorithm fuses the optical and SAR observations using a Hidden Markov Model (HMM) approach. The snow map includes four thematic snow classes, based on the international standard classes (dry snow, moist snow, wet snow and very wet snow) obtained from Sentinel-1 (radar) and MODIS/Sentinel-3 (optical) satellite data. The results obtained for both study areas from Norway and those from Romania were validated using data recorded by sensors placed at meteorological and hydrometrical stations or measurements collected within field campaigns. For more details about the methodology please check this presentation. Everyone is welcome to explore, download and test the obtained results using the SnowBall Geoportal functionalities.
We provide two ways to download the snow wetness products:
Use the control to filter the calendar by the dates when products are available for each collection. Then, use the download icons to download the products in the desired format:
SnowBall Geoportal is build entirely with standard compliant free and open source software and open data.
For more information about SnowBall geoportal access and data products please contact firstname.lastname@example.org