Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge

Abstract

The integration of data from different sources can be very helpful in understanding the mechanism, the geometry, the kinematic, and the area affected by complex instabilities, especially when the available geotechnical information is limited. In this work, the suitability of different techniques for the study of a deep-seated landslide affecting a bridge in Alcoy (Spain) is evaluated. This infrastructure presents such severe damage that has rendered the bridge unusable, which prevents normal access to an important industrial area. Differential SAR Interferometry (DInSAR) and terrestrial Light Detection and Ranging (LiDAR) remote sensing techniques have been combined with ground displacement monitoring techniques, such as inclinometers and conventional geological and geotechnical investigation, electrical-seismic tomography, damage, and topographic surveys, to determine the boundaries, mechanism, and kinematics of the landslide. The successful case study that is illustrated in this work highlights the potential and the need for integrating multi-source data for the optimal management of complex landslides and the effective design of remedial measurements.

An Improved R-Index Model for Terrain Visibility Analysis for Landslide Monitoring with InSAR

“…Thus, the effects of the orientation (i.e., incidence angle and azimuth) of the satellite LOS and the resolution of the DEM (of the local terrain) on the terrain visibility are discussed in this section. Note that although the effects of the influencing parameters on the terrain visibility have been addressed previously [23,26,27,31,39], the results presented in this section could be taken as a meaningful supplement to the existing studies.…”

“…Rather, if the SAR images acquired by the descending ALOS PALSAR and those by the ascending ALOS PALSAR are integrated, 89.01% of the total area (i.e., 3648.37 km 2 ) in Fengjie would be categorized into the area with good visibility, and 1360 landslides (i.e., 87.74% of the historical landslides) would be located in the regions with good visibility. In other words, to overcome the problem of poor visibility caused by the application of a single set of SAR images, a combined use of the ascending and descending SAR images can provide a promising solution [39].…”

Assessment of the Contribution of Polarimetric Persistent Scatterer Interferometry on Sentinel-1 Data

“…The area of Alcoy is characterised by the occurrence of frequent landslides caused by rainfall, anthropogenic activities, and earthquakes occurred in the past. The construction of recent buildings as well as the Alicante-Valencia A-7 highway has also lead to some settlements [30]- [32].…”

Semi-real time systems for subsidence monitoring in areas affected by underground mining: the example of the Nuraxi-Figus coal district (Sardinia, Italy)

“…Due to these limitations, remote sensing can be a costeffective technique. Specifically, among the different types of remote sensing techniques, the Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR- Franceschetti et al 1992) proved to be a very powerful tool, being sensitive to sub-centimetric ground movements (Colesanti et al 2006) and/or terrain displacements, induced by landslides (Wasowski and Bovenga 2022;Scifoni et al 2016;Pappalardo et al 2018;Giardina et al 2019;Guerriero et al 2019), earthquakes (De Novellis et al 2018;Zhao et al 2021), volcanoes (Foumelis et al 2016Casu et al 2019) and valid to detect harm to structures and infrastructures (Milillo et al 2018;Ullo et al 2019;Pastor et al 2019;Miano et al 2021). In the last three decades, A-DinSAR has been applied also in mining areas to detect subsidence due to underground activity (Yue et al 2011;Du et al 2016;Ammirati et al 2020;Pawluszek et al 2020;Chen et al 2021), monitoring the stability of tailings dam (Necsoiu et al 2015;Gama et al 2019;Ammirati et al 2021), and to identify surface movements in open-pit mines (Paradella et al 2015;Carlà et al 2018).…”