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Regional-scale landslide inventory, central-western sector of the Basilicata region (Southern Apennines, Italy)

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  • Maurizio Lazzari
  • Dario Gioia

Abstract

A detailed landslide inventory map has been drawn for a large sector of the axial-outer zone of the Southern Italian Apennines using photo-aerial interpretation and field survey. Our results reveal a landscape greatly affected by landslide phenomena, which involve about 7% of the entire area. DEM analysis allowed us to assess the influence of landslide processes on the geomorphological evolution and investigate the main predisposing factors, which promote the initiation and evolution of mass movements. In order to understand the influence of lithological and topographic factors on slope processes, an evaluation of the landslide susceptibility has been carried out using the SINMAP model. A statistical comparison between the stability index map and landslides highlights a good prediction ability of the susceptibility assessment. Apart from the implications for mass movement processes and relief evolution, the acquired data can represent a basic contribution to land management and hazard assessment as well as the gathering of basic information on landslide susceptibility of this sector of the southern Apennine chain.

Suggested Citation

  • Maurizio Lazzari & Dario Gioia, 2016. "Regional-scale landslide inventory, central-western sector of the Basilicata region (Southern Apennines, Italy)," Journal of Maps, Taylor & Francis Journals, vol. 12(5), pages 852-859, October.
    • Handle: RePEc:taf:tjomxx:v:12:y:2016:i:5:p:852-859
    DOI: 10.1080/17445647.2015.1091749
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    Cited by:

    1. Luigi Spalluto & Antonio Fiore & Maria Nilla Miccoli & Mario Parise, 2021. "Activity maps of multi-source mudslides from the Daunia Apennines (Apulia, southern Italy)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 277-301, March.
    2. Sheng Ma & Jian Chen & Saier Wu & Yurou Li, 2023. "Landslide Susceptibility Prediction Using Machine Learning Methods: A Case Study of Landslides in the Yinghu Lake Basin in Shaanxi," Sustainability, MDPI, vol. 15(22), pages 1-26, November.

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