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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ftunivbern:oai:boris.unibe.ch:143988 2023-08-20T04:10:08+02:00 Towards a webcam-based snow cover monitoring network: methodology and evaluation Portenier, Céline Hüsler, Fabia Härer, Stefan Wunderle, Stefan 2020 application/pdf https://boris.unibe.ch/143988/1/tc-14-1409-2020.pdf https://boris.unibe.ch/143988/ eng eng Copernicus Publications https://boris.unibe.ch/143988/ info:eu-repo/semantics/openAccess Portenier, Céline; Hüsler, Fabia; Härer, Stefan; Wunderle, Stefan (2020). Towards a webcam-based snow cover monitoring network: methodology and evaluation. The Cryosphere, 14(4), pp. 1409-1423. Copernicus Publications 10.5194/tc-14-1409-2020 <http://dx.doi.org/10.5194/tc-14-1409-2020> 550 Earth sciences & geology info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion PeerReviewed 2020 ftunivbern https://doi.org/10.5194/tc-14-1409-2020 2023-07-31T22:00:02Z 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 BORIS (Bern Open Repository and Information System, University of Bern) Principal Point ENVELOPE(-63.431,-63.431,-64.912,-64.912) The Cryosphere 14 4 1409 1423 |
institution |
Open Polar |
collection |
BORIS (Bern Open Repository and Information System, University of Bern) |
op_collection_id |
ftunivbern |
language |
English |
topic |
550 Earth sciences & geology |
spellingShingle |
550 Earth sciences & geology Portenier, Céline Hüsler, Fabia Härer, Stefan Wunderle, Stefan Towards a webcam-based snow cover monitoring network: methodology and evaluation |
topic_facet |
550 Earth sciences & geology |
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 |
Portenier, Céline Hüsler, Fabia Härer, Stefan Wunderle, Stefan |
author_facet |
Portenier, Céline Hüsler, Fabia Härer, Stefan Wunderle, Stefan |
author_sort |
Portenier, Céline |
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://boris.unibe.ch/143988/1/tc-14-1409-2020.pdf https://boris.unibe.ch/143988/ |
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 |
Portenier, Céline; Hüsler, Fabia; Härer, Stefan; Wunderle, Stefan (2020). Towards a webcam-based snow cover monitoring network: methodology and evaluation. The Cryosphere, 14(4), pp. 1409-1423. Copernicus Publications 10.5194/tc-14-1409-2020 <http://dx.doi.org/10.5194/tc-14-1409-2020> |
op_relation |
https://boris.unibe.ch/143988/ |
op_rights |
info:eu-repo/semantics/openAccess |
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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1774724108733382656 |