Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge
AbstractThe 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. View Full-Text
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Pastor, J.L.; Tomás, R.; Lettieri, L.; Riquelme, A.; Cano, M.; Infante, D.; Ramondini, M.; Di Martire, D. Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge. Remote Sens. 2019, 11, 1878.
Pastor JL, Tomás R, Lettieri L, Riquelme A, Cano M, Infante D, Ramondini M, Di Martire D. Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge. Remote Sensing. 2019; 11(16):1878.Chicago/Turabian Style
Pastor, José L.; Tomás, Roberto; Lettieri, Luca; Riquelme, Adrián; Cano, Miguel; Infante, Donato; Ramondini, Massimo; Di Martire, Diego. 2019. "Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge." Remote Sens. 11, no. 16: 1878.
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