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Open AccessArticle

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

1
Department of Civil Engineering, University of Alicante, 03690 Alicante, Spain
2
Department of Civil, Architectural and Environmental Engineering, Federico II University of Napoli, 80125 Napoli, Italy
3
SINTEMA Engineering, viale Kennedy 5, 80125 Napoli, Italy
4
Department of Earth, Environmental and Resources Sciences, Federico II University of Napoli, 80125 Napoli, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1878; https://doi.org/10.3390/rs11161878
Received: 13 June 2019 / Revised: 7 August 2019 / Accepted: 9 August 2019 / Published: 12 August 2019
(This article belongs to the Special Issue Fusion of InSAR Data and other Sources for Infrastructure Monitoring)
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. View Full-Text
Keywords: DInSAR; multi-source integration; rotational landslide; structural damage; bridge DInSAR; multi-source integration; rotational landslide; structural damage; bridge
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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.

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