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UAV, GNSS, and InSAR Data Analyses for Landslide Monitoring in a Mountainous Village in Western Greece
- Source :
- Remote Sensing, Vol 15, Iss 11, p 2870 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- Areas in Western Greece are particularly prone to landslides. Usually triggered by earthquakes or intense rainfalls, they cause damage to infrastructure (roads, bridges, etc.) and human properties. Hence, there is an urgent need for the implementation of monitoring and landslide prevention methodologies. In the last years, Unmanned Aerial Vehicles (UAVs), Global Navigation Satellite Systems (GNSS), and Interferometric SAR (InSAR) techniques have been applied for landslide mapping and monitoring. The current study focuses on the systematic and long-term analysis of a landslide that occurred in Ano Kerassovo village, within the region of Western Greece. To precisely measure the current evolution of the landslide, we performed repetitive UAV campaigns in conjunction with corresponding GNSS surveys, covering a time period between February 2021 and April 2023. The identification of surface modification was based on a change detection approach between the generated point clouds. The results are validated through GNSS measurements and field observations. Added to this, we collected archived Persistent Scatterer Interferometry (PSI) measurements derived from the European Ground Motion Service (EGMS) to extend the observation period and gain a more complete understanding of the phenomenon. It is proven that archived PSI measurements can be used as an indicator of possible landslide initialization points and for small-scale large coverage investigations, while UAVs and GNSS data can precisely identify the microscale deformations (centimeter scale).
- Subjects :
- landslides
monitoring
UAV
GNSS
PSI
analysis
Science
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 15
- Issue :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.71dbe8fb16364bb1aeff794565be2d88
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs15112870