Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge
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Título: | Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge |
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Autor/es: | Pastor Navarro, José Luis | Tomás, Roberto | Lettieri, Luca | Riquelme, Adrián | Cano, Miguel | Infante, Donato | Ramondini, Massimo | Di Martire, Diego |
Grupo/s de investigación o GITE: | Ingeniería del Terreno y sus Estructuras (InTerEs) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ingeniería Civil |
Palabras clave: | DInSAR | Multi-source integration | Rotational landslide | Structural damage | Bridge |
Área/s de conocimiento: | Ingeniería del Terreno |
Fecha de publicación: | 12-ago-2019 |
Editor: | MDPI |
Cita bibliográfica: | 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. doi:10.3390/rs11161878 |
Resumen: | 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. |
Patrocinador/es: | This work has been supported by the University of Alicante under the projects GRE17-11, and the Spanish Ministry of Economy and Competitiveness (MINECO), the State Agency of Research (AEI) and the European Funds for Regional Development (FEDER) under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P, and the Spanish Ministry of Education, Culture and Sport under project PRX17/00439. |
URI: | http://hdl.handle.net/10045/95884 |
ISSN: | 2072-4292 |
DOI: | 10.3390/rs11161878 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.3390/rs11161878 |
Aparece en las colecciones: | INV - INTERES - Artículos de Revistas |
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2019_Pastor_etal_RemoteSens.pdf | 11,17 MB | Adobe PDF | Abrir Vista previa | |
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