Abstract
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.
Highlights
Introduction andWong, 2005; Van dHenyEdercokhloougt yet aaln., d2007; Tofani et a“lD.,el2iv0e1r3a)b. leIn4p.4a”rti(cSualfaerL, EaansadirtDthieslipvSoeryinasbteltdee4om.u4t, in the 2011)report of the EU-funded SafeLand Project,A fundamental step in the landslide risk analysis and, more generally, in the landslide risk management process (Fell et al, 2008a) is represented by landslide inventory mapping which usually includes location, classification, volume, state of activity, date of occurrence and otherSynthetic Aperture Radar Differential Interferometry (DIn-SAR) techniques may represent suitable tools for updating inventory maps dealing with slow-moving landslides, namely mass values range fmroomvemfeewOntmcpmheeynaro−nm1eSunpacwtioehno1s.c6e metyypric−a1l velocity
The main purpose of this paper is to present a new methodology that improves the exploitation of the abovementioned datasets for a study area of southern Italy allowing the updating of slow-moving landslide inventory maps at medium scale (1 : 25 000) with reference to both the state of activity and the detection of unmapped phenomena
In the present paper persistent scatterers interferometry (PSI) data, combined with geomorphological, topographic and optical data in order to detect/map/monitor slow-moving landslides, were jointly analysed with the results of damage surveys to structure/infrastructures recorded within landslide affected areas
Summary
The study area (557 km2) is located in the south-east part of National Basin Authority of Liri-Garigliano and Volturno rivers (NBA LGV) and includes 21 Municipalities and 2 Provinces (Benevento and Avellino) belonging to the Campania region in southern Italy (Fig. 1). This area was selected due to the widespread distribution of slow-moving landslides (covering around 25 % of the total extension) which caused losses to structures/infrastructures interacting with them (Melidoro, 1971; D’Elia et al, 1985; Budetta et al, 1994; SCAI Project, 2004; Guadagno et al, 2006; APAT, 2007; Cascini et al, 2008).
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