Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring

Remote Sensing

Veronica Tofani¹  Federico Raspini²  Filippo Catani² 

[1] Department of Earth Sciences, University of Firenze, Via La Pira, 4, I-50121 Firenze, Italy;

关键词: landslide;    SAR;    PSI;    monitoring;    northern Apennines;   

DOI  :  10.3390/rs5031045

来源: mdpi

【 摘 要 】

The measurement of landslide superficial displacement often represents the most effective method for defining its behavior, allowing one to observe the relationship with triggering factors and to assess the effectiveness of the mitigation measures. Persistent Scatterer Interferometry (PSI) represents a powerful tool to measure landslide displacement, as it offers a synoptic view that can be repeated at different time intervals and at various scales. In many cases, PSI data are integrated with in situ monitoring instrumentation, since the joint use of satellite and ground-based data facilitates the geological interpretation of a landslide and allows a better understanding of landslide geometry and kinematics. In this work, PSI interferometry and conventional ground-based monitoring techniques have been used to characterize and to monitor the Santo Stefano d’Aveto landslide located in the Northern Apennines, Italy. This landslide can be defined as an earth rotational slide. PSI analysis has contributed to a more in-depth investigation of the phenomenon. In particular, PSI measurements have allowed better redefining of the boundaries of the landslide and the state of activity, while the time series analysis has permitted better understanding of the deformation pattern and its relation with the causes of the landslide itself. The integration of ground-based monitoring data and PSI data have provided sound results for landslide characterization. The punctual information deriving from inclinometers can help in defining the actual location of the sliding surface and the involved volumes, while the measuring of pore water pressure conditions or water table level can suggest a correlation between the deformation patterns and the triggering factors.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.