Investigating snowpack volumes and icing dynamics in the moraine of an Arctic catchment using UAV photogrammetry

International audience Methods for assessing the contribution of the proglacial moraine into the water budget of an Arctic glacier are investigated. High spatial resolution elevation models at different seasons are needed to estimate the volume of ice and snow accumulated during winter in this part...

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Bibliographic Details
Main Authors: Bernard, Eric, Friedt, Jean, Tolle, Florian, Griselin, Madeleine, Marlin, Christelle, Prokop, Alexander
Other Authors: Théoriser et modéliser pour aménager (UMR 6049) (ThéMA), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC)-Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC)-Centre National de la Recherche Scientifique (CNRS)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2017
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Online Access:https://hal.archives-ouvertes.fr/hal-02392691
Description
Summary:International audience Methods for assessing the contribution of the proglacial moraine into the water budget of an Arctic glacier are investigated. High spatial resolution elevation models at different seasons are needed to estimate the volume of ice and snow accumulated during winter in this part of the catchment basin and released into rivers during the melting season. Lidar currently provides the highest resolution for the generation of digital elevation models (DEMs). This paper considers the complementary use of a commercial off-the-shelf DJI Phantom 3 Professional unmanned aerial vehicle (UAV) for acquiring aerial photography, combined with structure-from-motion (SfM) analysis, for DEM computation. DEM differences between datasets acquired in April (maximum snow accumulation) and September (minimum snow cover) yield a volume difference attributed either to snow cover or icing formation. Repeated measurements over a short period highlight the processes of snow-cover storage in the moraine and melting dynamics.