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...
Published in: | The Cryosphere |
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Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2020
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Subjects: | |
Online Access: | https://doi.org/10.5194/tc-14-1409-2020 https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d |
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author | C. Portenier F. Hüsler S. Härer S. Wunderle |
author_facet | C. Portenier F. Hüsler S. Härer S. Wunderle |
author_sort | C. Portenier |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 4 |
container_start_page | 1409 |
container_title | The Cryosphere |
container_volume | 14 |
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 |
genre | The Cryosphere |
genre_facet | The Cryosphere |
geographic | Principal Point |
geographic_facet | Principal Point |
id | ftdoajarticles:oai:doaj.org/article:803763dd21344b3aa1e65a2d070db04d |
institution | Open Polar |
language | English |
long_lat | ENVELOPE(-63.431,-63.431,-64.912,-64.912) |
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op_doi | https://doi.org/10.5194/tc-14-1409-2020 |
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_source | The Cryosphere, Vol 14, Pp 1409-1423 (2020) |
publishDate | 2020 |
publisher | Copernicus Publications |
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spelling | ftdoajarticles:oai:doaj.org/article:803763dd21344b3aa1e65a2d070db04d 2025-01-17T01:06:00+00:00 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 |
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 |
title | 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_short | Towards a webcam-based snow cover monitoring network: methodology and evaluation |
title_sort | towards a webcam-based snow cover monitoring network: methodology and evaluation |
topic | Environmental sciences GE1-350 Geology QE1-996.5 |
topic_facet | Environmental sciences GE1-350 Geology QE1-996.5 |
url | https://doi.org/10.5194/tc-14-1409-2020 https://doaj.org/article/803763dd21344b3aa1e65a2d070db04d |