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&thinsp;000&thinsp;m<span clas...

Full description

Bibliographic Details
Main Authors: A. E. Tekeli, S. Dönmez
Format: Article
Language:English
Published: Copernicus Publications 2018-12-01
Series:Proceedings of the International Association of Hydrological Sciences
Online Access:https://www.proc-iahs.net/380/81/2018/piahs-380-81-2018.pdf
id doaj-8272650e98d24f5dade2825989a4950e
record_format Article
spelling doaj-8272650e98d24f5dade2825989a4950e2020-11-24T21:13:47ZengCopernicus PublicationsProceedings of the International Association of Hydrological Sciences2199-89812199-899X2018-12-01380818510.5194/piahs-380-81-2018Image acquisition effects on Unmanned Air Vehicle snow depth retrievalsA. E. Tekeli0S. Dönmez1Civil Engineering Department, Çankırı Karatekin University, Çankırı, 18100, TurkeyCivil Engineering Department, Çankırı Karatekin University, Çankırı, 18100, Turkey<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&thinsp;000&thinsp;m<span class="inline-formula"><sup>2</sup></span>. Photos with 80&thinsp;% forward and 60&thinsp;% 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&thinsp;cm in continuous and 1.79&thinsp;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>https://www.proc-iahs.net/380/81/2018/piahs-380-81-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author A. E. Tekeli
S. Dönmez
spellingShingle A. E. Tekeli
S. Dönmez
Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
Proceedings of the International Association of Hydrological Sciences
author_facet A. E. Tekeli
S. Dönmez
author_sort A. E. Tekeli
title Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
title_short Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
title_full Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
title_fullStr Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
title_full_unstemmed Image acquisition effects on Unmanned Air Vehicle snow depth retrievals
title_sort image acquisition effects on unmanned air vehicle snow depth retrievals
publisher Copernicus Publications
series Proceedings of the International Association of Hydrological Sciences
issn 2199-8981
2199-899X
publishDate 2018-12-01
description <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&thinsp;000&thinsp;m<span class="inline-formula"><sup>2</sup></span>. Photos with 80&thinsp;% forward and 60&thinsp;% 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&thinsp;cm in continuous and 1.79&thinsp;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>
url https://www.proc-iahs.net/380/81/2018/piahs-380-81-2018.pdf
work_keys_str_mv AT aetekeli imageacquisitioneffectsonunmannedairvehiclesnowdepthretrievals
AT sdonmez imageacquisitioneffectsonunmannedairvehiclesnowdepthretrievals
_version_ 1716748160495255552