A Novel Approach to Landslide Monitoring Based on Unmanned Aerial System Photogrammetry

Abstract

Landslides represent great dangers that can cause fatalities and huge property damage. To prevent or reduce all possible consequences that landslides cause, it is necessary to know the kinematics of the surface and undersurface sliding masses. Geodetic surveying techniques can be used for landslide monitoring and creating a kinematic model of the landslide. One of the most used surveying techniques for landslide monitoring is the photogrammetric survey by Unmanned Aerial System. The results of the photogrammetric survey are dense point clouds, digital terrain models, and digital orthomosaic maps, where landslide displacements can be determined by comparing these results in two measurement epochs. This paper presents a new data processing method with a novel approach for calculating landslide displacements based on Unmanned Aerial System photogrammetric survey data. The main advantage of the new method is that it does not require the production of dense point clouds, digital terrain models, or digital orthomosaic maps to determine displacements. The applicability and accuracy of the new method were tested in a test field with simulated displacements of known values within the range of 20-40 cm in various directions. The new method successfully determined these displacements with a 3D accuracy of ±1.3 cm.

Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry

“…The theory behind the proposed data processing method is presented in detail in [ 37 , 38 ]. The workflow of the proposed method with three main steps is shown in Figure 1 .…”

“…In the next step, outlier displacement vectors are detected and removed by performing the Leave One Out Cross Validation (LOOCV) process based on the kriging interpolation [ 39 , 40 ]. The detailed process of detecting and removing outlier displacements is described in [ 37 ].…”

“…In [ 37 ], we proposed a new data processing method for the calculation of the landslide displacements from UAS photogrammetric survey data based exclusively on the SfM algorithm steps and resulting sparse point clouds. Using the proposed method, landslide displacements can be determined without using the MVS algorithm and generating dense point clouds, digital elevation model, and digital orthomosaic images.…”

“…The applicability of the proposed method is presented in [ 37 ], where simulated displacements are determined from the UAS survey performed on a test field at a flight altitude of 20 m. In this paper, the continuation of this research is presented using data from UAS surveys performed on the same established test field at greater flight altitudes (50 and 120 m) since they are more realistic altitudes for UAS survey of a landslide. Moreover, UAS surveys were performed by applying two different flight heights to analyze the impact of flight altitude on the accuracy of the determined displacement.…”

Estimating Landslide Surface Displacement by Combining Low-Cost UAV Setup, Topographic Visualization and Computer Vision Techniques

“…Similarly, there is increasing interest in the use of Unmanned Aerial Vehicles (UAV) for landslide studies [10], as UAVs offer several advantages over traditional monitoring methods, including the ability to collect high-resolution imagery, to access difficult-toreach areas, and to collect data frequently and at a lower cost [11,12]. Therefore, it is natural for scholars to adopt and further exploit this technology also for landslide timeseries monitoring [13,14], mapping and characterization [15][16][17] as well as combining their outputs with machine learning [18] and computer vision algorithms [19,20].…”