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

Snow cover variability has a significant impact on climate and the environment and is of great socioeconomic importance for the European Alps. Terrestrial photography offers a high potential to monitor snow cover variability, but its application is often limited to small catchment scales. Here, we p...

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Published in:The Cryosphere
Main Authors: C. Portenier, F. Hüsler, S. Härer, S. Wunderle
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
Subjects:
Online Access:https://doi.org/10.5194/tc-14-1409-2020
https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d
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spelling ftdoajarticles:oai:doaj.org/article:803763dd21344b3aa1e65a2d070db04d 2023-05-15T18:32:27+02:00 Towards a webcam-based snow cover monitoring network: methodology and evaluation C. Portenier F. Hüsler S. Härer S. Wunderle 2020-04-01T00:00:00Z https://doi.org/10.5194/tc-14-1409-2020 https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d EN eng Copernicus Publications https://www.the-cryosphere.net/14/1409/2020/tc-14-1409-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-1409-2020 1994-0416 1994-0424 https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d The Cryosphere, Vol 14, Pp 1409-1423 (2020) Environmental sciences GE1-350 Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.5194/tc-14-1409-2020 2022-12-31T08:57:10Z Snow cover variability has a significant impact on climate and the environment and is of great socioeconomic importance for the European Alps. Terrestrial photography offers a high potential to monitor snow cover variability, but its application is often limited to small catchment scales. Here, we present a semiautomatic procedure to derive snow cover maps from publicly available webcam images in 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 novel registration approach that automatically resolves camera parameters (camera orientation; principal point; field of view, FOV) by using an estimate of the webcams' positions and a high-resolution digital elevation model (DEM). Furthermore, we propose an automatic image-to-image alignment to correct small changes in camera orientation and compare and analyze two recent snow classification methods. The resulting snow cover maps indicate whether a DEM grid is snow-covered, snow-free, or not visible from webcams' positions. GCPs are used to evaluate our novel automatic image registration approach. The evaluation reveals 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 ∘ ). In addition, we discuss projection uncertainties caused by the mapping of low-resolution webcam images onto the high-resolution DEM. Overall, our results highlight the potential of our method to build up a webcam-based snow cover monitoring network. Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles Principal Point ENVELOPE(-63.431,-63.431,-64.912,-64.912) The Cryosphere 14 4 1409 1423
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Environmental sciences
GE1-350
Geology
QE1-996.5
spellingShingle Environmental sciences
GE1-350
Geology
QE1-996.5
C. Portenier
F. Hüsler
S. Härer
S. Wunderle
Towards a webcam-based snow cover monitoring network: methodology and evaluation
topic_facet Environmental sciences
GE1-350
Geology
QE1-996.5
description Snow cover variability has a significant impact on climate and the environment and is of great socioeconomic importance for the European Alps. Terrestrial photography offers a high potential to monitor snow cover variability, but its application is often limited to small catchment scales. Here, we present a semiautomatic procedure to derive snow cover maps from publicly available webcam images in 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 novel registration approach that automatically resolves camera parameters (camera orientation; principal point; field of view, FOV) by using an estimate of the webcams' positions and a high-resolution digital elevation model (DEM). Furthermore, we propose an automatic image-to-image alignment to correct small changes in camera orientation and compare and analyze two recent snow classification methods. The resulting snow cover maps indicate whether a DEM grid is snow-covered, snow-free, or not visible from webcams' positions. GCPs are used to evaluate our novel automatic image registration approach. The evaluation reveals 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 ∘ ). In addition, we discuss projection uncertainties caused by the mapping of low-resolution webcam images onto the high-resolution DEM. Overall, our results highlight the potential of our method to build up a webcam-based snow cover monitoring network.
format Article in Journal/Newspaper
author C. Portenier
F. Hüsler
S. Härer
S. Wunderle
author_facet C. Portenier
F. Hüsler
S. Härer
S. Wunderle
author_sort C. Portenier
title Towards a webcam-based snow cover monitoring network: methodology and evaluation
title_short Towards a webcam-based snow cover monitoring network: methodology and evaluation
title_full Towards a webcam-based snow cover monitoring network: methodology and evaluation
title_fullStr Towards a webcam-based snow cover monitoring network: methodology and evaluation
title_full_unstemmed Towards a webcam-based snow cover monitoring network: methodology and evaluation
title_sort towards a webcam-based snow cover monitoring network: methodology and evaluation
publisher Copernicus Publications
publishDate 2020
url https://doi.org/10.5194/tc-14-1409-2020
https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d
long_lat ENVELOPE(-63.431,-63.431,-64.912,-64.912)
geographic Principal Point
geographic_facet Principal Point
genre The Cryosphere
genre_facet The Cryosphere
op_source The Cryosphere, Vol 14, Pp 1409-1423 (2020)
op_relation https://www.the-cryosphere.net/14/1409/2020/tc-14-1409-2020.pdf
https://doaj.org/toc/1994-0416
https://doaj.org/toc/1994-0424
doi:10.5194/tc-14-1409-2020
1994-0416
1994-0424
https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d
op_doi https://doi.org/10.5194/tc-14-1409-2020
container_title The Cryosphere
container_volume 14
container_issue 4
container_start_page 1409
op_container_end_page 1423
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