Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)

In this study, we used an Unmanned Aerial Vehicle (UAV) to collect a time series of high-resolution images over four years at seven epochs to assess landslide dynamics. Structure from Motion (SfM) was applied to create Digital Surface Models (DSMs) of the landslide surface with an accuracy of 4–5 cm...

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Main Authors: Darren Turner, Arko Lucieer, Steven M. de Jong
Format: Article
Language:English
Published: MDPI AG 2015-02-01
Series:Remote Sensing
Subjects:
UAV
Online Access:http://www.mdpi.com/2072-4292/7/2/1736
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spelling doaj-d1b572dc824b4821a9a58668c334f1422020-11-24T21:42:12ZengMDPI AGRemote Sensing2072-42922015-02-01721736175710.3390/rs70201736rs70201736Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)Darren Turner0Arko Lucieer1Steven M. de Jong2School of Land and Food, University of Tasmania, Hobart, TAS 7001, AustraliaSchool of Land and Food, University of Tasmania, Hobart, TAS 7001, AustraliaDepartment of Physical Geography, Utrecht University, P.O. Box 80115, Utrecht 3508 TC, The NetherlandsIn this study, we used an Unmanned Aerial Vehicle (UAV) to collect a time series of high-resolution images over four years at seven epochs to assess landslide dynamics. Structure from Motion (SfM) was applied to create Digital Surface Models (DSMs) of the landslide surface with an accuracy of 4–5 cm in the horizontal and 3–4 cm in the vertical direction. The accuracy of the co-registration of subsequent DSMs was checked and corrected based on comparing non-active areas of the landslide, which minimized alignment errors to a mean of 0.07 m. Variables such as landslide area and the leading edge slope were measured and temporal patterns were discovered. Volumetric changes of particular areas of the landslide were measured over the time series. Surface movement of the landslide was tracked and quantified with the COSI-Corr image correlation algorithm but without ground validation. Historical aerial photographs were used to create a baseline DSM, and the total displacement of the landslide was found to be approximately 6630 m3. This study has demonstrated a robust and repeatable algorithm that allows a landslide’s dynamics to be mapped and monitored with a UAV over a relatively long time series.http://www.mdpi.com/2072-4292/7/2/1736landslideUAVCosi-corrdigital elevation model (DEM)
collection DOAJ
language English
format Article
sources DOAJ
author Darren Turner
Arko Lucieer
Steven M. de Jong
spellingShingle Darren Turner
Arko Lucieer
Steven M. de Jong
Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
Remote Sensing
landslide
UAV
Cosi-corr
digital elevation model (DEM)
author_facet Darren Turner
Arko Lucieer
Steven M. de Jong
author_sort Darren Turner
title Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
title_short Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
title_full Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
title_fullStr Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
title_full_unstemmed Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
title_sort time series analysis of landslide dynamics using an unmanned aerial vehicle (uav)
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2015-02-01
description In this study, we used an Unmanned Aerial Vehicle (UAV) to collect a time series of high-resolution images over four years at seven epochs to assess landslide dynamics. Structure from Motion (SfM) was applied to create Digital Surface Models (DSMs) of the landslide surface with an accuracy of 4–5 cm in the horizontal and 3–4 cm in the vertical direction. The accuracy of the co-registration of subsequent DSMs was checked and corrected based on comparing non-active areas of the landslide, which minimized alignment errors to a mean of 0.07 m. Variables such as landslide area and the leading edge slope were measured and temporal patterns were discovered. Volumetric changes of particular areas of the landslide were measured over the time series. Surface movement of the landslide was tracked and quantified with the COSI-Corr image correlation algorithm but without ground validation. Historical aerial photographs were used to create a baseline DSM, and the total displacement of the landslide was found to be approximately 6630 m3. This study has demonstrated a robust and repeatable algorithm that allows a landslide’s dynamics to be mapped and monitored with a UAV over a relatively long time series.
topic landslide
UAV
Cosi-corr
digital elevation model (DEM)
url http://www.mdpi.com/2072-4292/7/2/1736
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AT arkolucieer timeseriesanalysisoflandslidedynamicsusinganunmannedaerialvehicleuav
AT stevenmdejong timeseriesanalysisoflandslidedynamicsusinganunmannedaerialvehicleuav
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