Integration of Webcam data for deriving Snow cover and snow depth from Sentinel-1, Sentinel-2 and Pléiades data

Short Description

Starting point / motivation

The variability in snow cover have huge impact on climate, on a variety of ecosystems, and on socio-economic aspects of human life. Snowfall and persistence of snow cover are strongly dependent on atmospheric temperature and precipitation, thus likely to change in complex ways in a changing climate.

In the Alpine region, snow cover variability is a high socio-economic aspect not only as local water resource and storage, but also as climate-related hazard and winter tourism. To quantify the effect of climate change on snow variation and the annual and inter-annual snow dynamics required by local stakeholders, a continuous reliable measurement of the temporal and spatial variability of snow cover is needed.

For monitoring snow cover variability, the most important parameters are the amount and duration of seasonal snow cover and snow depth from where the amount of water stored within the snowpack can be derived.

The available techniques and sampling strategies employed to quantify snow cover and depth have all strengths and limitations. To monitor the extent of wet snow areas during the melting season Synthetic Aperture Radar satellite data are currently used in the Alps. At dry snow conditions, the snow cover extent for complex alpine terrain can be retrieved from high-resolution optical satellite imagery.

However, the fundamental challenges of satellite data remain in terms of data availability, spatial resolution and cloud cover. Furthermore, quantifying large scale snow depth from satellite platform remains on open issue.

In this respect, snow depth is currently estimated at local and regional scale by mean of photogrammetric techniques from manned and unmanned aerial platforms. However, snow is a challenging surface for photogrammetric techniques due to its relatively uniform surface with limited identifiable features. An alternative to airborne technologies to derive snow cover and depth is terrestrial photography.

Currently this technique is used on study areas under control conditions such as camera information are known, and often linked to meteorological stations equipped with snow depth sensors or snow stakes in the field of view of the camera. Only recently, outdoor webcam images are considered as potential data source for deriving snow cover, thanks to their high spatio-temporal resolution and availability.

WebSnow focuses on improving snow cover maps and snow depth estimates using a large network (accessible via Bergfex) of webcam images available at different elevation zone from ski resort and mountain areas.

Contents and goals

The overall goal of the project is to develop a methodology and study the feasibility of using webcam images for 

  • validating and improving snow cover maps from high resolution Sentinel-1 & -2 data and for
  • deriving snow depth from Pléiades images at higher temporal resolutions and larger areas than what is feasible using UAV and aerial images.

The success on those project ambitions holds the potential to increase knowledge about snow variation needed from local stakeholders for evaluating socio-economic aspects and as support to estimate the consequences in real-time of climate change and consequent decision making processes.

Expected results

Finally, demonstrating the feasibility of the proposed approach will promote the exploitation of satellite images in an operational context in a challenging environment.

Project Partners


Vienna University of Technology - Department of Geodesy and Geoinformation

Project partner

  • ENVEO - ENVironmental Earth Observation IT GmbH
  • Swiss Federal Research Institute WSL

Contact Address

Vienna University of Technology
Department of Geodesy and Geoinformation
Univ.Prof. Dipl.Ing. Dr.techn. Norbert Pfeifer
Wiedner Hauptstraße 8-10/E120.7
A-1040 Vienna