Innovative Techniques for the Detection and Characterization of the Kinematics of Slow-Moving Landslides

  • Ping Lu
  • Alexander Daehne
  • Julien Travelletti
  • Nicola Casagli
  • Alessandro Corsini
  • Jean-Philippe Malet
Part of the Advances in Natural and Technological Hazards Research book series (NTHR, volume 34)


Remote sensing has been proven useful for landslide studies. However, conventional remote sensing techniques based on aerial photographs and optical imageries seem to be more suitable for detecting and characterizing rapid-moving landslides. This section introduces several innovative remote sensing techniques aiming at the characterization of the kinematics (e.g. displacement pattern, deformation, strain) of slow- to moderate-moving landslides. These methods include Persistent Scatterers Interferometry (PSI), automatic surveying using total station integrated with GPS, Ground-Based Synthetic Aperture Radar Interferometry (GB-InSAR), image correlation of catalogues of optical photographs (TOP) and Terrestrial Laser Scanner (TLS) point clouds. Three case studies, including the Arno river basin (Italy), the Valoria landslide (Italy) and the Super-Sauze landslide (France) are presented in order to highlight the usefulness of these techniques.


Point Cloud Total Station Terrestrial Laser Scanner Correlation Window Persistent Scatterer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Airborne Laser Scanner


Coherent Pixels Technique


Differential InSAR


Early Warning


Ground-based Synthetic Aperture Radar Interferometry


Interferometric Point Target Analysis




Persistent Scatterers


Persistent Scatterers Interferometry


SAR Interferometry


Small Baseline Subset


Stable Point Network


Stanford Method for Persistent Scatterers


Terrestrial Laser Scanner


Terrestrial Optical Photogrammetry


Digital Elevation Model


Global Positioning System


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Ping Lu
    • 1
  • Alexander Daehne
    • 2
    • 3
  • Julien Travelletti
    • 4
    • 5
  • Nicola Casagli
    • 1
  • Alessandro Corsini
    • 2
    • 3
  • Jean-Philippe Malet
    • 4
    • 5
  1. 1.Department of Earth SciencesUniversity of FirenzeFlorenceItaly
  2. 2.Department of Earth SciencesUniversity of Modena and Reggio Emilia UniversityModenaItaly
  3. 3.Department of GeosciencesUniversity of Missouri – Kansas CityKansas CityUSA
  4. 4.Institut de Physique du Globe de Strasbourg, CNRS UMR 7516Université de Strasbourg/EOSTStrasbourg CedexFrance
  5. 5.BEG, Bureau d’Etudes Géologiques SAAprozSwitzerland

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