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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 13, issue 6 | Copyright

Special issue: New developments and applications in early warning, monitoring...

Nat. Hazards Earth Syst. Sci., 13, 1527-1549, 2013
https://doi.org/10.5194/nhess-13-1527-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 18 Jun 2013

Research article | 18 Jun 2013

The combination of DInSAR and facility damage data for the updating of slow-moving landslide inventory maps at medium scale

L. Cascini1, D. Peduto1, G. Pisciotta2, L. Arena1, S. Ferlisi1, and G. Fornaro3 L. Cascini et al.
  • 1Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano (Salerno), Italy
  • 2Via Ventaglieri, 77, 80135 Naples, Italy
  • 3Institute for Electromagnetic Sensing of the Environment (IREA–CNR), Via Diocleziano 328, 80124 Naples, Italy

Abstract. Testing innovative procedures and techniques to update landslide inventory maps is a timely topic widely discussed in the scientific literature. In this regard remote sensing techniques – such as the Synthetic Aperture Radar Differential Interferometry (DInSAR) – can provide a valuable contribution to studies concerning slow-moving landslides in different geological contexts all over the world. In this paper, DInSAR data are firstly analysed via an innovative approach aimed at enhancing both the exploitation and the interpretation of remote sensing information; then, they are complemented with the results of an accurate analysis of survey-recorded damage to facilities due to slow-moving landslides. In particular, after being separately analysed to provide independent landslide movement indicators, the two datasets are combined in a DInSAR-Damage matrix which can be used to update the state of activity of slow-moving landslides. Moreover, together with the information provided by geomorphological maps, the two datasets are proven to be useful in detecting unmapped phenomena. The potentialities of the adopted procedure are tested in an area of southern Italy where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria.

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