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

Abstract

Abstract: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 m 3 .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.

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

“…This topic has been described by several authors (Dewitte et al, 2008;Turner and Lucieer, 2013;Travelletti et al, 2012;Lucieer et al 2014a;Turner et al, 2015;Marek et al, 2015;Lindner et al, 2016;Peppa et al, 2017). In these works, numerous techniques based on the multi-temporal comparison of RPAS data sets for the definition of the evolution of landslides have been presented and discussed.…”

“…Westoby et al (2012) emphasized the advantages of RPASs concerning terrestrial laser scanners, which can suffer from line-of-sight issues, and airborne lidar, which are often cost-prohibitive for individual landslide studies. Turner et al (2015) stressed the importance of a good co-registration of multi-temporal DSMs for good results that could decrease in accuracy. The use of benchmarks in areas not affected by morphological changes can be used for a correct calibration of rotational and translation parameters.…”

Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition

“…This landslide affected approximately 250 m of the highway, destroyed two houses, caused the evacuation of 10 others, and delayed the opening of the highway for several months [71]. as, soil erosion [59,60], landslides or rocky surfaces inventory [56,61], landslide detection [62], landslide dynamics and monitoring [57,[63][64][65][66][67], and natural disaster monitoring and evaluation [68,69]. A comprehensive review of remote sensing applications based on UAVs equipped with specific sensor-based technologies has been accomplished to varying degrees across a range of applications.…”

Preliminary results from active landslide monitoring using multidisciplinary surveys

“…Several recent studies have also demonstrated the power of Structure from Motion algorithms for landslide mapping and monitoring (Niethammer, Rothmund, Schwaderer, Zeman, & Joswig, 2011;Akca, 2013;Lucieer et al, 2014;Nikolakopoulos et al, 2015a;Turner, Lucieer, & De Jong, 2015). Different studies demonstrating the use of UAV data for landslide monitoring have been published (Lin, Tao, Wang, & Huang, 2010;Rau, Jhan, Lob, & Linb, 2011;Turner et al, 2015).…”

“…Different studies demonstrating the use of UAV data for landslide monitoring have been published (Lin, Tao, Wang, & Huang, 2010;Rau, Jhan, Lob, & Linb, 2011;Turner et al, 2015).…”