Advantages of Using UAV Digital Photogrammetry in the Study of Slow-Moving Coastal Landslides

Abstract

The aim of this study is to demonstrate the advantages of using micro drones in the study of large slow-moving landslides, which are widespread along the northwestern coast of Malta. In particular, attention was given to the inventory and analysis of gravity-induced joints and megaclast deposits at four study sites selected due to the presence of remarkable examples of lateral spreads evolving into block slides. The research was carried out by means of Google Earth (GE) image analysis and uncrewed aerial vehicle digital photogrammetry (UAV-DP). UAV-DP outputs enabled the identification and characterization of tens of persistent joints (locally exceeding 150 m) and permitted the size categorization of thousands of blocks. With reference to gravity-induced joints, a favorable agreement was found between existing datasets (mainly based on the integration of GE analysis and field survey) and UAV-DP outputs in terms of the identification of joints and their persistence. Conversely, the use of the UAV-DP technique showed significant advantages in terms of joint aperture determination (even exceeding 1 m) and distribution setting. Regarding the extensive megaclast deposits, UAV-DP enabled the identification of 8943 individuals which, compared with the 5059 individuals identified by GE analysis, showed an increase in the total population of 76%. This is related to the high accuracy of DP-derived orthomosaics and 3D models, which are particularly useful for identifying detached blocks. The inexpensive technique used in this research highlights its potential for being extended to other rocky coastal areas affected by slow-moving landslides.

Evolution of Deep-Seated Gravitational Slope Deformations in Relation with Uplift and Fluvial Capture Processes in Central Eastern Sardinia (Italy)

“…Uncrewed aerial vehicle digital photogrammetry (UAV-DP) is a robust methodology for the investigation of DGSDs and large landslides. In particular, it was used for the recognition of large lateral spreads in Malta and Tunisia [95,96]. We used UAV-DF and light detection and ranging (LiDAR) to extract high-resolution topographic 3D DGSD models and perform detailed morphometric analyses.…”

Analysis of the Geological Controls and Kinematics of the Chgega Landslide (Mateur, Tunisia) Exploiting Photogrammetry and InSAR Technologies

“…Mateos et al [17] reported an average velocity of the same order of magnitude (5.2 mm/yr) in a large lateral spreading along the North coast of Majorca (Spain). Extensive lateral spreading and block sliding processes in a geological setting comparable to the Chgega landslide have been under investigation since 2006 in the North part of Malta [8,9,[64][65][66]. In this area, long-term differential GNSS monitoring outputs carried out gave displacement rates between 0.8 and 2.4 cm/yr in a limestone plateau affected by lateral spreads and downslope blocks moved from block slides [64].…”

Geodetic and UAV Monitoring in the Sustainable Management of Shallow Landslides and Erosion of a Susceptible Urban Environment

“…UAVs, commonly called drones, provide indispensable help, efficiency in terms of speed and precision, as well as cost savings especially in inaccessible or difficult to navigate locations. UAVs are rising among many industries and have become very popular in numerous interdisciplinary researches, but for survey engineering they represent a quantum leap [36,37]. Several studies have demonstrated the usefulness and reliability of structure from motion (SfM) software and their implementation in landslide monitoring.…”