Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.790 IF 4.790
  • IF 5-year value: 5.921 IF 5-year
    5.921
  • CiteScore value: 5.27 CiteScore
    5.27
  • SNIP value: 1.551 SNIP 1.551
  • IPP value: 5.08 IPP 5.08
  • SJR value: 3.016 SJR 3.016
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 63 Scimago H
    index 63
  • h5-index value: 51 h5-index 51
Discussion papers
https://doi.org/10.5194/tc-2019-142
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-142
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 05 Jul 2019

Submitted as: research article | 05 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

Towards a webcam-based snow cover monitoring network: methodology and evaluation

Céline Portenier1, Fabia Hüsler2, Stefan Härer3, and Stefan Wunderle1 Céline Portenier et al.
  • 1Institute of Geography and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • 2Federal Office for the Environment FOEN, Ittigen, Switzerland
  • 3Professorship Ecoclimatology, Technical University of Munich, Freising, Germany

Abstract. Snow cover variability has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Terrestrial photography offers a high potential to monitor snow cover variability, but its application is often limited to the small catchment scale. Here, we present a semi-automatic procedure to derive snow cover maps from arbitrary webcam images. We use freely available webcam images of the Swiss Alps and propose a procedure for the georectification and snow classification of such images. In order to avoid the effort of manually setting ground control points (GCPs) for each webcam, we implement a new registration approach that automatically resolves camera parameters (camera orientation, principal point, field of view (FOV)) by using an estimate of the webcams position and a high-resolution digital elevation model (DEM). Furthermore, two recent snow classification methods are compared and analyzed. The resulting snow cover maps have the same spatial resolution as the DEM and indicate whether a grid cell is snow-covered, snow-free, or not visible from webcams' positions. GCPs were used to evaluate our novel automatic image registration approach. The evaluation reveals in a root mean square error (RMSE) of 14.1 m for standard lens webcams (FOV < 48°) and a RMSE of 36.3 m for wide-angle lens webcams (FOV ≥ 48°). Overall, our results highlight the potential of our method to built up a webcam-based snow cover monitoring network.

Céline Portenier et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Céline Portenier et al.
Céline Portenier et al.
Viewed  
Total article views: 290 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
202 83 5 290 3 6
  • HTML: 202
  • PDF: 83
  • XML: 5
  • Total: 290
  • BibTeX: 3
  • EndNote: 6
Views and downloads (calculated since 05 Jul 2019)
Cumulative views and downloads (calculated since 05 Jul 2019)
Viewed (geographical distribution)  
Total article views: 169 (including HTML, PDF, and XML) Thereof 167 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 17 Sep 2019
Publications Copernicus
Download
Short summary
We present a method to derive snow cover maps from freely available webcam images in the Swiss Alps. With marginal manual user input, we can transform a webcam image into a georeferenced map and therewith perform snow cover analyses with a high spatio-temporal resolution over a large area. Our evaluation has shown that webcams could not only serve as a reference for improved validation of satellite-based approaches, but also complement satellite-based snow cover retrieval.
We present a method to derive snow cover maps from freely available webcam images in the Swiss...
Citation