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GIS Methodology to Assess Landslide Susceptibility

Application to a River Catchment of Central Italy

Bibliographic Data

ID16840255
AuthorsGabriele Leoni (0000-0002-9538-3272), Fabrizio Barchiesi (Roma Tre University), Fabrizio Catallo (Roma Tre University), F Dramis (0000-0001-5931-2656, Roma Tre University), Giandomenico Fubelli (0000-0002-1430-4836, Roma Tre University), Stella Lucifora (Roma Tre University), Massimo Mattei (0000-0001-7800-8764, Roma Tre University), Guiseppe Pezzo, Giuseppe Pezzo (0000-0003-4851-4193, Roma Tre University), Claudio Puglisi (National Agency for New Technologies, Energy and Sustainable Economic Development)
Year2009
Volume5
Issue1
Pages87-93
Publication date2009-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Maps (JOURNAL)
Journal identifiersISSN: 1744-5647 • E-ISSN: 1744-5647
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.4113/jom.2009.1041
OpenAlexW2016948710
LanguageEN
Citations received3
References cited3

Please click here to download the map associated with this article. This paper illustrates a geographic information system (GIS) supported methodology for the assessment of landslide susceptibility. The methodology involves four operational steps: survey, site analysis, macroarea analysis and susceptibility analysis. The Survey includes the production (or acquisition) of a large-scale litho-technical map, a large-scale geomorphological map, a detailed inventory of past and present landslide events, and a high resolution DTM (Digital Terrain Model. Site analysis leads to the definition of discriminating parameters (commonly, lithological and morphometric conditions necessary but not sufficient to trigger a landslide of a given type) and predisposing factors (conditions that worsen slope stability but are not sufficient to trigger a landslide of a given type in the absence of discriminating parameters). The different predisposing factors are subdivided into classes, whose intervals are established by descriptive, statistical analysis of landslide inventory data. A numerical index, based on the frequency of landslide occurrence, quantifies the contribution of each class to slope instability. Macro-area analysis includes the generation of Litho-Morphometric Units (LMU) by overlaying discriminating parameters, manual drawing of LMU envelopes (macro-areas), generation of predisposing factor maps from the spatial distribution of predisposing factors, and heuristic weighting of predisposing factor indices. Susceptibility analysis includes the generation of Homogeneous Territorial Units (HTU) by overlaying macroareas and predisposing factor maps, and the application of a susceptibility function to the different HTU. The resulting values are normalized before the generation of the landslide susceptibility maps. The methodology has been applied to the Fiumicino River catchment, located in the western side of Latium Apennine (Central Italy) between 200 and 1300 m a.s.l. and developed on Late Miocene calcarenites, sandstones with clay intercalations, and marls. The resulting landslide susceptibility maps will be employed in environmental management. They also represent the preliminary step for the assessment of landslide hazard and risk

Cartography · Geographic information system · Geography · Geomorphology · Landslide · Macro · Terrain · Weighting · Computer Science · Cryospheric studies and observations · Geotechnical Engineering and Analysis · Landslides and related hazards · Geology

  • Mass Movement Processes and Landforms

    Open Access•F Dramis•International Encyclopedia of…•2017

  • Thematic Maps for Land-Use Planning and Policy Decisions in the Calaggio Stream Catchment Area

    Open Access•Antonio Di Lisio, Filippo Russo•Journal of Maps•2010

  • Landslide susceptibility of the Prato–Pistoia–Lucca provinces, Tuscany, Italy

    Open Access•Samuele Segoni, Veronica Tofani et al.•Journal of Maps•2016

  • Landslide hazard evaluation

    Open Access•Fausto Guzzetti, Alberto Carrara et al.•Geomorphology•1999

Unique citing works3
Citations per year0.19
Citation span2010 - 2017 (8)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 3

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