UAV applications to assess short-term dynamics of slow-moving landslides under dense forest cover

Abstract

<p>The paper focuses on presenting a methodology that can be used to rapidly assess and map kinematics of landslides when these occur in areas with dense vegetation cover. The method is based on using aerial imagery collected with UAV (Unmanned Aerial Vehicle) and their derived products obtained by applying the Structure from Motion (SfM) technique. The landslide occurred on May 3, 2021, and is located in the Livadea village, Curvature Subcarpathians (Romania). It affected several houses from the vicinity, and the people were relocated because of the high probability of landslide reactivation. To mitigate the consequences of this landslide, a preliminary investigation, based on three UAV surveys and field geological-geomorphological surveys, was carried out to delineate active parts of the landslide and to define evacuation measures. Three UAV flights (May 6, May 25 and July 10) were performed using DJI Phantom 4 and Phantom 4 RTK drones. Because it is a heavily forested area, a semi-automated processing of the landslide kinematics and change detection analysis were not possible. The landslide displacement rates and the changes in terrain morphology between flights were assessed by manual interpolating of collected landmarks on all three UAV flights. Tilted trees were used to estimate the landslide direction and evolution. The results show an average displacement of 9.55 m (minimum 1.2 m, maximum 20.6 m) between the first and the second flight and an average of 19.27 m (minimum 1.98 m and maximum 46.3 m) between the second and the third flight, respectively. This approach proved quick and efficient for rapid landslide investigations when fast response and measures are necessary to reduce landslide consequences.</p><p>Acknowledgement</p><p>This work was supported by a grant of the Romanian Ministry of Education and Research, CCCDI - UEFISCDI, project number PN-III-P2-2.1-PED-2019-5152, within PNCDI III (project coordinator Ionuț Șandric, https://slidemap.gmrsg.ro) and by the project PN19450103 / Core Program (project coordinator Viorel Ilinca).</p>

Lithological classification by PCA-QPSO-LSSVM method with thermal infrared hyper-spectral data

“…In recent years, unmanned aerial vehicle (UAV) technology has made breakthroughs and has been widely used in the geological field 75 – 77 For inaccessible field areas, the DJI Phantom 4 RTK (DJI-P4RTK) UAV can be used to obtain ultra-high spatial resolution images, and the entire process is not restricted by geographical conditions 78 , 79 . In addition, satellite data of the study area in the same temporal phase, such as Aster and WorldView-3, can be acquired 65 , 80 …”