A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

Abstract

On December 3, 2013, a large complex landslide was triggered SW of the town of Montescaglioso (Southern Italy), causing the destruction of roads, commercial buildings and private dwellings, as well as several direct and indirect economic losses. A set of interferometric ground measurements acquired by the Cosmo-SkyMed satellite constellation and processed by means of the SqueeSAR algorithm was used to study the pre-event slope displacements in the entire Montescaglioso municipal area. Data span from January 30, 2012, to December 2, 2013, and show average line-of-sight velocities of 1-10 mm/year in the slope sector ultimately affected by the collapse. In retrospect, a time series analysis of the radar targets was performed in order to identify and characterize all the slope instabilities in proximity of the town. This was based on the setup of characteristic thresholds of displacement. The procedure permitted to locate several areas which recurrently exceeded these previously established thresholds, in consistency with the amount of precipitation. In particular, the major source of potential hazard in the area was indeed found where the December 3, 2013, landslide eventually occurred. The results of this quick data processing technique were validated through comparison with two independently developed landslide maps. This simple method, which is not supposed to diminish the importance of geomorphologic field surveys, could improve both the accuracy and the update rate of landslide susceptibility maps.Not relying on arbitrary or empirically derived approaches, it has the advantage of computing statistically based thresholds specific for each time series. By indicating the slope sectors in higher need of deeper in situ investigation, more support could be provided to administrative bodies for the processes of risk assessment and management.

Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation

“…The landslide deformation field was quite consistent among the different datasets and the different data processing techniques used in this paper, thus demonstrating the reliability of the measurement technique. Furthermore, by selecting a correlation threshold of 0.9, the results are similar to those available in the literature [38,39,[41][42][43]55,[73][74][75][76], as well as the evidence inferred from field inspections. Figure 16 and Table 5 show the comparative results between the analyses performed using the COSI-Corr and GOM Correlate software for the same dataset.…”

“…along the left bank of the Bradano River. Based on the peculiar concave shape of the Montescaglioso relief, which illustrates an actively changing morphology, several types of ground evidence can be detected, such as inactive ancient landslide bodies, scarps and relicts, and blocks [23,38,39,[41][42][43]55].…”

“…The last phase of the movement (occurring on the night between 3 and 4 December 2013) was typified by a retrogressive style that caused a northward replacement of the landslide area. According to the landslide classification introduced by the authors of [56] and highlighted by the authors of [38,39,42], the slope instability has been considered a rapid complex earth slide [1.8 m/h ≤ velocity <3 m/min]. Indeed, most of the movement occurred within a period of approximately 15-20 min, with peaks in velocity of approximately 0.75 m/min corresponding with certain sectors.…”

“…The last phase of the movement (occurring on the night between 3 and 4 December 2013) was typified by a retrogressive style that caused a northward replacement of the landslide area. According to the landslide classification introduced by the authors of [56] and highlighted by the authors of [38,39,42], the slope instability has been considered a rapid complex earth slide [ In the frame of this work, a specific field survey aimed at better constraining the deformational pattern and mapping the main geomorphological features of the slope was performed in July 2016. The main focus during the field survey was to observe and describe those geomorphological features caused by recent and previous slope instability processes.…”

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

“…InSAR data are now commonly used for a variety of purposes, such as landslide detection and mapping (Herrera et al 2011;Lu et al 2012;Cigna et al 2013;Raspini et al 2013;Bardi et al, 2016), monitoring and modelling (Berardino et al 2003;Hilley et al 2004;Tofani et al 2013;Komac et al 2015;Carlà et al 2016), hazard and risk assessment (Lu et al 2014) and, through time series analysis, for the identification of changes in deformation rates (Frodella et al 2016) and seasonal trends (Tomás et al 2016).…”