Comprehensive Monitoring of the Active and Fast-moving Landslide of Pissouri village, Cyprus: Integrating SAR, GNSS, Rainfall and Laser Scanner Data

Pissouri village, located in Limassol, Cyprus, has been experiencing an active and fast-moving landslide, resulting in significantly accelerated displacement rates in recent years. The devastating consequences of the landslide include the continuous evacuation of houses, severe damage to properties, and transformations of the wider landscape. To improve national disaster preparedness and resilience to geological threats, the Cyprus University of Technology Laboratory of Geodesy established CyCLOPS (Cyprus Continuously Operating Natural Hazards Monitoring and Prevention System) in 2021, focusing on Pissouri as a critical case study. Since 2022, a number of ten geodetic-grade GNSS receivers have been installed in the broader area to enable continuous monitoring of the landslide.

This study presents an integration of multi-sensor data to investigate displacement rates and advance the understanding of landslide dynamics, utilizing the CyCLOPS strategic infrastructure. Sentinel-1 acquisitions in ascending and descending mode, covering the period from August 2022 to August 2024, were processed using GAMMA software. The data reveal significantly increased displacement patterns compared to earlier analyses, which detected only millimeters of movement per year. Concurrently, GNSS monitoring was performed using CyCLOPS equipment, indicating notable local movements and providing continuous ground-truth measurements. Additionally, rainfall data from the Cyprus Meteorological Department stations were integrated into a GIS framework, correlating intense precipitation events with rapid displacement trends. Two novel additions to this monitoring effort include: (a) the installation of a rain gauge within the study area to improve the reliability and accuracy of precipitation data, and (b) the use of Laser Scanning technology to detect and map structural cracks and landscape changes within the affected zone. These approaches provide localized insights into the landslide’s impact.

This comprehensive multi-sensor approach offers a robust framework for understanding and monitoring active landslides. The findings underscore the critical role of data integration and the use of a multi-sensor strategy in assessing displacement rates, correlating environmental triggers, and accurately evaluating hazards. Collectively, these measures support improved hazard mitigation strategies and enhance resilience.

Acknowledgments: The authors would like to acknowledge the "CyCLOPS+" (RIF/SMALL SCALE INFRASTRUCTURES/1222/0082) project, which is co-financed by the European Regional and Development Fund and the Republic of Cyprus through the Research and Innovation Foundation in the framework of the Cohesion Policy Programme "THALIA 2021-2027" and by national resources. The authors would like to acknowledge the ‘CyCLOPS’ (RIF/INFRASTRUCTURES/1216/0050) project, which was funded by the European Regional and Development Fund and the Republic of Cyprus through the Research and Innovation Foundation in the framework of the RESTART 2016-2020 program.