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Remote Sensing Meteorological and DInSAR Historical Data to Analyse the Kinematic Behaviour of Slow-Moving Landslides at Municipal Scale

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Geotechnical Engineering in the Digital and Technological Innovation Era (CNRIG 2023)

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Abstract

The present study aims to investigate the kinematic behaviour of slow-moving landslides affecting urban areas at municipal scale, based on remote sensing meteorological and displacement (DInSAR) historical data. The long-term influence of weather patterns on landslide dynamics and their potential variation under the effect of ongoing climate change is taken into account through the reanalysis of the main weather and soil water variables derived by the freely available datasets provided by CERRA within the Copernicus Climate Change Service (C3S). The above-mentioned data are jointly analysed with widespread ground surface displacements data gathered from the processing of very-high resolution Synthetic Aperture Radar (SAR) images acquired by COSMO-SkyMed constellation via Differential Interferometry (DInSAR) techniques. The link between the main weather and soil water variables with the ground deformations sensed from the space was investigated in the territory of Vaglio Basilicata, a municipality in the Basilicata region (southern Italy) widely affected by slow-moving landslides interacting with the built-up environment and, specifically, infrastructure networks. The preliminary results achieved could be valuably used as input to outline a proper procedure aimed at the dynamic evaluation of the infrastructure risk associated with weather-induced reactivations and/or accelerations of slow-moving landslides.

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Acknowledgements

This research has been supported by MIUR PON R&I 2014–2020 Program (project MITIGO, ARS01_00964). The authors wish to acknowledge project partner e-GEOS for processing the COSMO-SkyMed data. CERRA data was downloaded from the Copernicus Climate Change Service (C3S) Climate Data Store. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

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Authors and Affiliations

  1. Department of Civil Engineering, University of Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Gianfranco Nicodemo, Gaetano Pecoraro, Davide Luongo, Dario Peduto & Michele Calvello

  2. Regional Models and Geo-Hydrological Impacts (REMHI) Division, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, via T. A. Edison, 81100, Caserta, Italy

    Guido Rianna & Alfredo Reder

Authors
  1. Gianfranco Nicodemo
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  2. Gaetano Pecoraro
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  3. Guido Rianna
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  4. Alfredo Reder
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  5. Davide Luongo
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  6. Dario Peduto
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  7. Michele Calvello
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Correspondence to Gianfranco Nicodemo .

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Editors and Affiliations

  1. Office GC D1 402, EPFL-ENAC-LMS, Lausanne, Switzerland

    Alessio Ferrari

  2. University of Palermo, Palermo, Italy

    Marco Rosone

  3. University of Palermo, Palermo, Italy

    Maurizio Ziccarelli

  4. Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, Bologna, Italy

    Guido Gottardi

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Nicodemo, G. et al. (2023). Remote Sensing Meteorological and DInSAR Historical Data to Analyse the Kinematic Behaviour of Slow-Moving Landslides at Municipal Scale. In: Ferrari, A., Rosone, M., Ziccarelli, M., Gottardi, G. (eds) Geotechnical Engineering in the Digital and Technological Innovation Era. CNRIG 2023. Springer Series in Geomechanics and Geoengineering. Springer, Cham. https://doi.org/10.1007/978-3-031-34761-0_30

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  • DOI: https://doi.org/10.1007/978-3-031-34761-0_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34760-3

  • Online ISBN: 978-3-031-34761-0

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