Like many other countries in the world, Switzerland faces challenges (e.g., land management, environmental degradation) caused by increasing pressures on its natural resources. These challenges need to be overcome to meet the needs of a growing population. Switzerland is acknowledged as the water reservoir of Europe. While its territory represents four thousandths of the continent's total area, 6% of Europe's freshwater reserves are stored in Switzerland.
Snow is one of the most relevant natural water resources present in nature. It stores water in winter and releases it in spring during the melting season. Monitoring snow cover and its variability is an indicator of climate change and identification of snowmelt processes is essential for effective water-resource management.
Remotely-sensed Earth Observations (EO) data acquired by satellites are helpful to monitor snow conditions through time. Synthetic-Aperture Radar (SAR) images are effective and robust measures to identify meltingsnow, whereas optical data are able to identify snow cover extension.
Earth Observations Data Cubes (EODC) are a new paradigm revolutionizing the way users can interact with increasingly freely and openly available EO data. They minimize the time and scientific knowledge required to access, prepare and analyze large volume of data having consistent and spatially aligned calibrated observations.
Switzerland is the second country in the world to have a national-scale EODC. The Swiss Data Cube (SDC – http://www.swissdatacube.ch) is an initiative supported by the Federal Office for the Environment (FOEN) and developed, implemented and operated by the United Environment Program (UNEP)/GRID-Geneva in partnership with the University of Geneva (UNIGE). The objective of the SDC is to support the Swiss government for environmental monitoring and reporting as well as enable Swiss scientific institutions to fully benefit from EO data for research and innovation. Currently, the SDC contains 33 years of Landsat 5,7,8 (1984-2017) and 2.5 years of Sentinel-2 (2015-2017) optical Analysis Ready Data over Switzerland (total volume: 3TB; 110 billion observations).
Recently, UNIGE has developed a new algorithm using the SDC to map snow cover extension. Preliminary results have shown a clear decrease of snow cover over the Alps in the last 30 years. However, to provide an integrated and effective mechanism to monitor snow cover and its variability, SAR data are missing and impeding identification of snowmelt processes. A valid source is the European Space Agency (ESA) Sentinel-1 high-resolution C-band SAR satellite.
Consequently, the aims of this project are: (1) to develop a methodology for generating and ingesting Sentinel-1 Analysis Ready Data into the SDC; (2) improve the Snow Observations from Space (SOfS) algorithm to identify snow melted and iced areas; (3) generate time-series of 2D composite backscatter products over Switzerland; and (4) explore the potential of SAR/optical data fusion techniques as well as additional SAR data sources.
In addition to current work of the two teams, the project will be implemented by organizing three one-week meetings so that participants can efficiently work together. Regular teleconferences will be organized to foster exchanges and share updates. Finally, we plan to submit two peer-reviewed articles in high-impact open-access journals.
Dr. Gregory Giuliani, University of Geneva
Dr. David Small, University of Zurich
Prof. Pascal Peduzzi, University of Geneva
Prof. Michael Shaepman, University of Zurich
Mr Bruno Chatenoux, University of Geneva
Ms Charlotte Poussin, University of Geneva