Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
<p>Advancements in technology have facilitated new opportunities in aerial photogrammetry; one of these is the use of unmanned aerial vehicles (UAVs) to estimate snow depth (SD). Here, a multi-rotor type UAV is used for SD retrievals over an area of 172 000 m<span clas...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-12-01
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| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://www.proc-iahs.net/380/81/2018/piahs-380-81-2018.pdf |
| Summary: | <p>Advancements in technology have facilitated new opportunities in aerial
photogrammetry; one of these is the use of unmanned aerial vehicles (UAVs) to
estimate snow depth (SD). Here, a multi-rotor type UAV is used for SD
retrievals over an area of 172 000 m<span class="inline-formula"><sup>2</sup></span>. Photos with 80 % forward
and 60 % side overlaps were taken by UAV on two different (snow-covered
and snow-free) days. SD estimations were obtained from the difference between
3-D stereo digital surface models (DSMs) produced for both days. Manual SD
measurements were performed on the ground concurrent with UAV flights. The
current study is unique in that the SD retrievals were derived using two
different image acquisition modes. In the first, images were taken as UAV was
continuously flying and in the second UAV had small stops and kept its
position in air fixed as the photos were taken. Root mean square error of UAV
derived SDs is calculated as 2.43 cm in continuous and 1.79 cm in fixed
acquisitions. The results support the hypothesis, based on theoretical
considerations, that fixed-position image acquisitions using multi-rotor
platforms should enable more accurate SD estimates. It is further seen that,
as SDs increased, the errors in SD calculations are reduced.</p> |
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| ISSN: | 2199-8981 2199-899X |