Extracting High Resolution Snow Distribution Information with Inexpensive Autonomous Cameras

9 pages•Published: September 20, 2018

Pauline Millet, Hendrik Huwald and Steven V. Weijs

Abstract

This study details a procedure to derive high resolution snow cover information using low-cost autonomous cameras. Images from time lapse photography of target areas are used to obtain temporally resolved binary snow-covered area information. Various image processing steps, such as distortion correction, alignment, projection using the Digital Elevation Model (DEM), and classification using clustering are described. Several innovations, such as matching the mountain silhouette with the DEM, and application of specific filters are described to make this terrestrial remote sensing method generally applicable to derive valuable snow information.

Keyphrases: clustering, image processing, mapping, snow covered area, snow monitoring, time lapse photos

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1397-1405.

Links:	https://easychair.org/publications/paper/VlrW
	https://doi.org/10.29007/93gh

BibTeX entry

@inproceedings{HIC2018:Extracting_High_Resolution_Snow,
  author    = {Pauline Millet and Hendrik Huwald and Steven V. Weijs},
  title     = {Extracting High Resolution Snow Distribution Information with Inexpensive Autonomous Cameras},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/VlrW},
  doi       = {10.29007/93gh},
  pages     = {1397-1405},
  year      = {2018}}

Download PDF Open PDF in browser