LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Giant landslide displacement analysis using a point cloud set conflict technique: a case in Xishancun landslide, Sichuan, China

Photo from wikipedia

ABSTRACT Landslides, threatening millions of human lives, are geological phenomena on earth, occurred frequently. An increasing number of techniques are being used to monitor landslide deformation. Among these, Light Detection… Click to show full abstract

ABSTRACT Landslides, threatening millions of human lives, are geological phenomena on earth, occurred frequently. An increasing number of techniques are being used to monitor landslide deformation. Among these, Light Detection and Ranging (LiDAR) stands out for its high efficiency and accuracy in displacement detection, particularly for giant landslides. In this work, we collected two temporal datasets of terrain laser scanning and proposed a flowchart for giant landslide displacement analysis using the point cloud set conflict(PCSC) technique. First, the terrestrial points were obtained by performing registration and off-terrain point filtering. Second, the landslide displacement field was acquired using the proposed method based on its surface roughness. The displacement results from our established methodological system are comparable with the ones of Interferometric Synthetic Aperture Radar (InSAR)-derived deformations. The differences estimated from two systems are at the centimetre level. Cross-analysis on the trigger factor with landslide occurred mechanism could be achieved based on the results as well. Therefore, this work provides a novel system to analyse the displacement of a giant landslide in the future study.

Keywords: landslide; analysis; landslide displacement; giant landslide; displacement; point

Journal Title: International Journal of Remote Sensing
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.