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An evaluation DEM accuracy acquired using a small
unmanned aerial vehicle across a riverine environment

Entwistle, NS; Heritage, G

An evaluation DEM accuracy acquired using a small 
unmanned aerial vehicle across a riverine environment Thumbnail


Authors

G Heritage



Abstract

Fluvial systems offer a challenging and varied environment for topographic survey, displaying a rapidly varying morphology, diversevegetation assemblage and varying degree of submergence. Traditionally theodolite or GPS based systems have been used to capture cross-section and break of slope based data which has subsequently been interpolated to generate a topographic surface. Advances in survey technology has resulted in an improved ability to capture larger volumes of data with infrared terrestrial and aerial LiDAR systems capturing high-density (<0.02m) data across terrestrial surfaces but instruments are expensive and cumbersome and fail to survey through water.
The rise of Structure from Motion (SfM) photogrammetry, coupled with unmanned aerial vehicles (UAVs), has potential to rapidly record information needed to derive elevation data at reach scale with sub decimetre density. The approach has the additional advantage over LiDAR of seeing through clear water to capture bed detail, whilst also generating orthorectified photographic mosaics of the survey reach. However, the accuracy of the data has received comparatively little attention. Here we present a survey protocol for UAV deployment and provide a reach scale comparison between a Terrestrial LiDAR Survey (TLS) and SfM UAV survey on the River Sprint near Kendal in England.. Comparative analysis of elevation data between TLS and SfM suggest comparable accuracy and precision across terrestrial surfaces with error lowest over solid surfaces, increasing with vegetation complexity. Submerged SfM data captured bed levels generally to within ±0.2 with only a weak relationship recorded between error and flow depth.

Citation

unmanned aerial vehicle across a riverine environment. International journal of new technology and research, 3(7), 43-48

Journal Article Type Article
Acceptance Date Aug 9, 2017
Publication Date Jul 1, 2017
Deposit Date Aug 21, 2017
Publicly Available Date Aug 22, 2017
Journal International Journal of New Technology and Research
Volume 3
Issue 7
Pages 43-48
Publisher URL https://www.ijntr.org/page/issues/vol/vol-3issue-7
Related Public URLs https://www.ijntr.org/

Files

IJNTR03070038.pdf (1.1 Mb)
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Version
Published in the International Journal of New Technology and Research, 3 (7) , pp. 43-48






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