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Open AccessArticle

Towards Automatic UAS-Based Snow-Field Monitoring for Microclimate Research

1
Central European Institute of Technology, Brno University of Technology, Purkynova 123, 612 00 Brno, Czech Republic
2
The Krkonose Mountains National Park Administration, Dobrovskeho 3, 543 01 Vrchlabi, Czech Republic
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(8), 1945; https://doi.org/10.3390/s19081945
Received: 11 March 2019 / Revised: 16 April 2019 / Accepted: 23 April 2019 / Published: 25 April 2019
This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and snow-covered area. Unlike similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches. View Full-Text
Keywords: snow mapping; UAS; photogrammetry; remote sensing; direct georeferencing; snow field; snow-covered area; snow depth snow mapping; UAS; photogrammetry; remote sensing; direct georeferencing; snow field; snow-covered area; snow depth
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MDPI and ACS Style

Gabrlik, P.; Janata, P.; Zalud, L.; Harcarik, J. Towards Automatic UAS-Based Snow-Field Monitoring for Microclimate Research. Sensors 2019, 19, 1945. https://doi.org/10.3390/s19081945

AMA Style

Gabrlik P, Janata P, Zalud L, Harcarik J. Towards Automatic UAS-Based Snow-Field Monitoring for Microclimate Research. Sensors. 2019; 19(8):1945. https://doi.org/10.3390/s19081945

Chicago/Turabian Style

Gabrlik, Petr; Janata, Premysl; Zalud, Ludek; Harcarik, Josef. 2019. "Towards Automatic UAS-Based Snow-Field Monitoring for Microclimate Research" Sensors 19, no. 8: 1945. https://doi.org/10.3390/s19081945

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