Remote Sensing - the view from above

Airborne and spaceborne remote sensing instruments can acquire continuous data over wide area even in poorly accessible terrain. These advantages make them an important tool for snow- and natural hazard research. There are roughly three types of remote sensing instruments:

optical sensors (passive) measure the reflected sunlight in different wavelengths to acquire information about physical and chemical properties of objects at the earth surface. Such measurements are usually quite easy to interpret and have a high spatial resolution but these sensors cannot penetrate clouds and are therefore not working during bad weather conditions.

radar sensors (active) send out radar waves and measure the signals reflected at the earth surface. Radar waves can penetrate even thick clouds and can therefore acquire data even during bad weather conditions. Radar waves can penetrate material such as snow and provide information on layers below the snow surface. But the radar signals are difficult to interpret and further research is necessary to fully understand the signals.

LiDAR sensors (active) send out waves within the visible and near infrared part of the electromagnetic spectrum and measure the time to the earth surface and back. Using this technology, very precise models of the earth surface can be generated. But this method works only from helicopters and airplanes and is therefore only suitable for smaller areas.

The SLF uses remote sensing instruments mainly for the following research questions:

Digital Elevation Models

DEM (digital elevation models) und DSM (digital surface models) are the basis for numerical simulations of mass movements such as avalanches, debris flows,  rockfall with RAMMS (Christen et al. 2010) and many further research applications. We investigate different technologies such as LiDAR and photogrammetric image correlation to generate precise terrain models in high mountain regions. Within selected test sites we quantify the achieved accuracies and identify systematic errors. We also investigate the effects of terrain model resolution and quality on the numerical simulation results (Bühler et al. 2011).

Detection and mapping of avalanche deposits

Fast access and accurate information on recent avalanche events are essential for avalanche forecasting and avalanche research. After extreme events such as the avalanche winter 1999 in Switzerland, remote sensing systems can map avalanche deposits over wide area. Of special interest are parameters such as run out distance, release area and deposition height. Using recently developed automated algorithms, very large datasets can be analyzed efficiently and fast (Bühler et al. 2009). The resulting information is valuable for the evaluation and calibration of avalanche dynamic models.

Small scale variability of snow depth

Information on snow depth and its spatial variability is important for many applications in snow and avalanche research (Schweizer et al. 2008) as well as for hydrology research (Lehning et al. 2006). Today, snow depth is mainly measured at isolated spots using automated stations or observers. But such methods cannot capture the spatial variability in alpine terrain. We are testing remote sensing based methods to map snow depth continuously over wide areas and evaluate their potential for existing applications such as avalanche forecasting and run off prediction.

Three-dimensional illustration of snow depth derived from an airborne scanner data at the Wannengrat, Davos GR.

Snow type mapping

The reflection of snow within the near infrared part of the electromagnetic spectrum is dependent on snow properties such as grain size (Warren 1982). Particularly old snow with its coarse grains appears darker in the imagery as windblown snow with its fine grains. Therefore we can use optical remote sensing instruments to map different snow types at the surface (Dozier et al. 2009). We test different airborne and spaceborne sensors in regard to operational snow type mapping in high alpine terrain.

The same subset of a snow covered area; left the blue band which is visible for the human eye and right the near infrared band which is invisible for "our eyes".

Contact

• Dr. Yves Bühler

  Organisational unit:	Snow Avalanches and Prevention Avalanche Dynamics and Risk Management
  Phone:	+41 81 4170 163
  Fax:	+41 81 4170 110
  Room:	Da A 2 11
  E-Mail:	,
  Web:	http://www.wsl.ch/info/mitarbeitende/buehlery