• Title of article

    Tracking and evolution of complex active landslides by multi-temporal airborne LiDAR data: The Montaguto landslide (Southern Italy)

  • Author/Authors

    Ventura، نويسنده , , Guido and Vilardo، نويسنده , , Giuseppe and Terranova، نويسنده , , Carlo and Sessa، نويسنده , , Eliana Bellucci، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    12
  • From page
    3237
  • To page
    3248
  • Abstract
    A multi-temporal LiDAR study of an active landslide at Montaguto (Italy) is presented. Four LiDAR-derived Digital Terrain Models acquired on May 2006, July 2009, April 2010 and June 2010 are used. The interpretation of selected morphometric parameters (surface roughness, residual topographic surface) and the statistical analysis of the temporal variations of such parameters allowed the reconstruction and tracking of the landslide. The landslide boundary monitoring was achieved and zones of uplift and subsidence, volumes of removed and/or accumulated material, and average rates of vertical and horizontal displacement (retreat rate of the crown and advancement rate of the toe) were estimated. Deformation structures (scarps, cracks, folds) affecting the landslide in different times were also mapped; some of such structures represent precursors of impending instability processes or give information on the mechanism of emplacement. Various types of activity (e.g. rock-fall, flow) and geometry (e.g., channelized flow) are recognized and zones whose topographic features change with time due to artificial drainage and earth handling/removal work were detected. The LiDAR-derived information allows us to decipher the kinematics of the landslide. The results provide new insight on the use of airborne LiDAR in the monitoring strategies of gravity-controlled processes.
  • Keywords
    Monitoring , Morphometric parameters , Spatio-temporal analysis , Topographic changes , Airborne LiDAR , Landslide
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2011
  • Journal title
    Remote Sensing of Environment
  • Record number

    1631219