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

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dc.contributor.authorGábrlík, Petrcs
dc.contributor.authorJanata, Přemyslcs
dc.contributor.authorŽalud, Luděkcs
dc.contributor.authorHarčarik, Josefcs
dc.coverage.issue8cs
dc.coverage.volume19cs
dc.date.accessioned2020-08-05T14:57:14Z
dc.date.available2020-08-05T14:57:14Z
dc.date.issued2019-04-25cs
dc.description.abstractThis 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.en
dc.formattextcs
dc.format.extent1-23cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationSENSORS. 2019, vol. 19, issue 8, p. 1-23.en
dc.identifier.doi10.3390/s19081945cs
dc.identifier.issn1424-8220cs
dc.identifier.other156674cs
dc.identifier.urihttp://hdl.handle.net/11012/173208
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofSENSORScs
dc.relation.urihttps://www.mdpi.com/1424-8220/19/8/1945cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1424-8220/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectsnow mappingen
dc.subjectUASen
dc.subjectphotogrammetryen
dc.subjectremote sensingen
dc.subjectdirect georeferencingen
dc.subjectsnow fielden
dc.subjectsnow-covered areaen
dc.subjectsnow depthen
dc.titleTowards Automatic UAS-Based Snow-Field Monitoring for Microclimate Researchen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-156674en
sync.item.dbtypeVAVen
sync.item.insts2020.08.05 16:57:14en
sync.item.modts2020.08.05 16:15:29en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika pro materiálové vědycs
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav automatizace a měřicí technikycs
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