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TitleMethod for measurement of snow depth using time-lapse photography
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AuthorFernandes, R A; Bariciak, T; Prévost, C; Yao, H; Field, T; McConnell, C; Luce, J; Metcalfe, R
SourceGeomatics Canada, Open File 47, 2019, 32 pages, https://doi.org/10.4095/314726 (Open Access)
Year2019
PublisherNatural Resources Canada
Documentopen file
Lang.English
Mediaon-line; digital
File formatpdf (Adobe® Reader®)
Subjectsgeophysics; Nature and Environment; snow; climate; floods; environmental studies; remote sensing; photogrammetric techniques; photography; in-field instrumentation; software; models; methodology; snow depth; monitoring; automation; snow depth stakes; infrastructures; geological hazards; habitats; image processing; algorithms; error analysis
Illustrationsphotographs; digital images; schematic representations; location maps; satellite images; time series; tables; graphs; bar graphs; schematic diagrams
ProgramLand Surface Characterization, Remote Sensing Science
Released2019 06 05
AbstractSnow depth (SD) is an essential climate variable widely used for flood forecasting, water quantity assessments, road and building safety assessment, habitat assessment, and climate studies. Currently, SD is systematically monitored using manual ruler measurements or dedicated instrumentation with a limited spatial footprint (~1m2). Here, an approach for automated SD estimation using images of narrow stakes remotely acquired by a 3Mpixel trail camera is described. The approach relies on the automated application of image processing and machine learning algorithms packaged within a single freely available application deployed on a personal computer or cloud computing environment. The application requires minimal user input to define an initial template image and provides two independent estimates of SD at each stake that can be used to produce an estimate of total uncertainty and sources of error. The system is compared to both manual ruler and ultrasonic instrument SD estimates at an open site and in a deciduous forest. Initial results over a melt period indicate the automated method agreed to within 1cm (RMSE) of manual ruler estimates and to within 3.6cm of ultrasonic estimates; with the latter comparison including spatial variability between measurement locations. The automated system should be considered for further deployment and evaluation over a range of surface and climate conditions.
Summary(Plain Language Summary, not published)
A method for automatic estimation of snow depth from time lapse images of stakes placed in natural landscapes is described and evaluated.
GEOSCAN ID314726