In Situ Change Analysis and Monitoring through Terrestrial Laser Scanning

In addition to inherent degradation with time, geologic hazards such as coastal erosion, landslides, and seismic activity constantly threaten public infrastructure. Repeat surveys using terrestrial laser scanning [TLS, ground-based light detection and ranging (LIDAR)] enable rapid, time-series, three-dimensional (3D) data acquisition to map, see, analyze, and understand the influence of such processes. Previously, change detection and analysis between scan surveys has been conducted during postprocessing upon return to the office, limiting the effectiveness and efficiency of the field investigation. A newly developed methodology quickly georeferences scans upon field acquisition and immediately performs change detection using a novel algorithm to compare acquired scans to baseline models directly in the field. Implementation and testing of the change analysis algorithm was performed on objects moved in a laboratory setting, on displaced piles at an outdoor geotechnical testing facility, and on site at an active landslide. The developed methodology and algorithm successfully detected and quantified varying degrees of change and showed significant time savings compared to traditional postprocessing techniques and common change analysis approaches.

[1]  Marco Scaioni,et al.  APPLICATION OF TLS FOR CHANGE DETECTION IN ROCK FACES , 2009 .

[2]  G. Priest,et al.  Johnson Creek Landslide research project, Lincoln County, Oregon : final report to the Oregon Department of Transportation. , 2008 .

[3]  S. Filin,et al.  CHANGE DETECTION VIA TERRESTRIAL LASER SCANNING , 2007 .

[4]  William Ribarsky,et al.  Visual analysis for live LIDAR battlefield change detection , 2008, SPIE Defense + Commercial Sensing.

[5]  Falko Kuester,et al.  Terrestrial Laser Scanning of Extended Cliff Sections in Dynamic Environments: Parameter Analysis , 2009 .

[6]  Antonio Galgaro,et al.  Terrestrial laser scanner to detect landslide displacement fields: a new approach , 2007 .

[7]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Michael J. Olsen,et al.  To Level or Not to Level: Laser Scanner Inclination Sensor Stability and Application , 2012 .

[9]  Marco Scaioni,et al.  Automatic Detection of Changes and Deformation In Rock Faces By Terrestrial Laser Scanning , 2010 .

[10]  Burcu Akinci,et al.  Efficient and Effective Quality Assessment of As-Is Building Information Models and 3D Laser-Scanned Data , 2011 .

[11]  Falko Kuester,et al.  New Automated Point-Cloud Alignment for Ground-Based Light Detection and Ranging Data of Long Coastal Sections , 2011 .

[12]  Burcu Akinci,et al.  Assessment of the quality of as-is building information models generated from point clouds using deviation analysis , 2011, Electronic Imaging.

[13]  Armin Gruen,et al.  Quality assessment of 3D building data , 2010 .

[14]  Michael J. Olsen,et al.  Movement and Erosion Quantification of the Johnson Creek, Oregon, Landslide through 3D Laser Scanning , 2012 .