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TitleAssessment of UAV-based photogrammetry for snow-depth mapping: data collection and processing
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AuthorFernandes, R A; Canisius, F; Leblanc, S G; Maloley, M; Oakes, S; Prévost, C; Schmidt, C
SourceGeomatics Canada, Open File 32, 2017, 50 pages, https://doi.org/10.4095/300553 (Open Access)
Year2017
PublisherNatural Resources Canada
Documentopen file
Lang.English
Mediaon-line; digital
File formatpdf
Subjectsgeophysics; snow; flood plains; mapping techniques; remote sensing; photogrammetric techniques; models; planning; meteorology; vegetation; field methods; unmanned aerial vehicles; algorithms; structure from motion (SFM); digital surface models (DSM); data acquisition; data processing; land cover; geolocation; snow depth stakes; orthoimages
Illustrationslocation maps; aerial photographs; bar graphs; photographs; satellite images; schematic representations; tables; graphs; digital images; 3-D images
ProgramLand Surface Characterization, Remote Sensing Science
Released2017 05 17
Summary(Plain Language Summary, not published)
Rapid snow melt is a major cause of flooding in Southern Canada. Often, the snow melt occurs in upstream areas that can be remote, forested or with rough terrain where there is little or no in-situ monitoring. Here, a method for mapping the snow depth over time using unmanned aerial vehicles is tested at two study areas during the winter of 2016 - Acadia Forest near Fredericton and Gatineau Park near Ottawa. The study sites, materials, methods and data collected are documented. This dataset is suitable for assessing the use of UAV systems for snow depth mapping.
GEOSCAN ID300553