Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies
<p>The capability of time-lapse photography to retrieve snow depth time series was tested. Historically, snow depth has been measured manually by rulers, with a temporal resolution of once per day, and it is a time-consuming activity. In the last few decades, ultrasonic and/or optical sensors...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2021-01-01
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| Series: | The Cryosphere |
| Online Access: | https://tc.copernicus.org/articles/15/369/2021/tc-15-369-2021.pdf |
| _version_ | 1818602931180535808 |
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| author | M. Bongio A. N. Arslan C. M. Tanis C. De Michele |
| author_facet | M. Bongio A. N. Arslan C. M. Tanis C. De Michele |
| author_sort | M. Bongio |
| collection | DOAJ |
| description | <p>The capability of time-lapse photography to retrieve snow
depth time series was tested. Historically, snow depth has been measured
manually by rulers, with a temporal resolution of once per day, and it is a
time-consuming activity. In the last few decades, ultrasonic and/or optical
sensors have been developed to obtain automatic and regular measurements
with higher temporal resolution and accuracy. The Finnish Meteorological
Institute Image Processing Toolbox (FMIPROT) has been used to retrieve the
snow depth time series from camera images of a snow stake on the ground by
implementing an algorithm based on the brightness difference and contour
detection. Three case studies have been illustrated to highlight potentialities
and pitfalls of time-lapse photography in retrieving the snow depth time
series: Sodankylä peatland, a boreal forested site in Finland, and Gressoney-La-Trinité Dejola and Careser Dam, two alpine sites in Italy. This
study presents new possibilities and advantages in the retrieval of snow
depth in general and snow depth time series specifically, which can be
summarized as follows: (1) high temporal resolution – hourly or sub-hourly
time series, depending on the camera's scan rate; (2) high accuracy levels –
comparable to the most common method (manual measurements); (3) reliability
and visual identification of errors or misclassifications; (4) low-cost
solution; and (5) remote sensing technique – can be easily extended in remote and
dangerous areas.</p>
<p>The proper geometrical configuration between camera and stake, highlighting
the main characteristics which each single component must have, has been
proposed. Root mean square errors (RMSEs) and Nash–Sutcliffe efficiencies (NSEs)
were calculated for all three case studies comparing with estimates from
both the FMIPROT and visual inspection of images directly. The NSE values were 0.917, 0.963 and 0.916, while RMSEs were 0.039, 0.052 and 0.108 m for Sodankylä, Gressoney and Careser, respectively. In
terms of accuracy, the Sodankylä case study gave better results. The
worst performances occurred at Careser Dam located at 2600 m a.s.l., where
extreme weather conditions and a low temporal resolution of the camera occur,
strongly affecting the clarity of the images.</p> |
| first_indexed | 2024-12-16T13:15:07Z |
| format | Article |
| id | doaj.art-7c48dc909e884cf1962185086c9d91e2 |
| institution | Directory Open Access Journal |
| issn | 1994-0416 1994-0424 |
| language | English |
| last_indexed | 2024-12-16T13:15:07Z |
| publishDate | 2021-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The Cryosphere |
| spelling | doaj.art-7c48dc909e884cf1962185086c9d91e22022-12-21T22:30:29ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242021-01-011536938710.5194/tc-15-369-2021Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studiesM. Bongio0A. N. Arslan1C. M. Tanis2C. De Michele3Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, ItalyFinnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101 Helsinki, FinlandFinnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101 Helsinki, FinlandDepartment of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy<p>The capability of time-lapse photography to retrieve snow depth time series was tested. Historically, snow depth has been measured manually by rulers, with a temporal resolution of once per day, and it is a time-consuming activity. In the last few decades, ultrasonic and/or optical sensors have been developed to obtain automatic and regular measurements with higher temporal resolution and accuracy. The Finnish Meteorological Institute Image Processing Toolbox (FMIPROT) has been used to retrieve the snow depth time series from camera images of a snow stake on the ground by implementing an algorithm based on the brightness difference and contour detection. Three case studies have been illustrated to highlight potentialities and pitfalls of time-lapse photography in retrieving the snow depth time series: Sodankylä peatland, a boreal forested site in Finland, and Gressoney-La-Trinité Dejola and Careser Dam, two alpine sites in Italy. This study presents new possibilities and advantages in the retrieval of snow depth in general and snow depth time series specifically, which can be summarized as follows: (1) high temporal resolution – hourly or sub-hourly time series, depending on the camera's scan rate; (2) high accuracy levels – comparable to the most common method (manual measurements); (3) reliability and visual identification of errors or misclassifications; (4) low-cost solution; and (5) remote sensing technique – can be easily extended in remote and dangerous areas.</p> <p>The proper geometrical configuration between camera and stake, highlighting the main characteristics which each single component must have, has been proposed. Root mean square errors (RMSEs) and Nash–Sutcliffe efficiencies (NSEs) were calculated for all three case studies comparing with estimates from both the FMIPROT and visual inspection of images directly. The NSE values were 0.917, 0.963 and 0.916, while RMSEs were 0.039, 0.052 and 0.108 m for Sodankylä, Gressoney and Careser, respectively. In terms of accuracy, the Sodankylä case study gave better results. The worst performances occurred at Careser Dam located at 2600 m a.s.l., where extreme weather conditions and a low temporal resolution of the camera occur, strongly affecting the clarity of the images.</p>https://tc.copernicus.org/articles/15/369/2021/tc-15-369-2021.pdf |
| spellingShingle | M. Bongio A. N. Arslan C. M. Tanis C. De Michele Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies The Cryosphere |
| title | Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies |
| title_full | Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies |
| title_fullStr | Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies |
| title_full_unstemmed | Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies |
| title_short | Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies |
| title_sort | snow depth time series retrieval by time lapse photography finnish and italian case studies |
| url | https://tc.copernicus.org/articles/15/369/2021/tc-15-369-2021.pdf |
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