Monitoring Geotechnical Assets along Pipeline Corridors Using Manned and Unmanned Aerial Platform-Based Photogrammetry

The adequate performance of geotechnical assets, such as natural and artificial slopes, embankments, and other geotechnical structures along pipeline corridors, is fundamental to ensure the safe and effective operation of the pipeline. Ideally, the frequent monitoring of the conditions of the geotechnical assets allows detecting potential problems early, making it easier to correct them as part of an asset maintenance program. In practice, however, the extensive and often inaccessible locations of such assets along a pipeline can make the monitoring task very challenging. The authors test the feasibility of using photogrammetric methods from a manned and unmanned aerial vehicle platform, to detect ground movements, as a diagnostic test for monitoring geotechnical assets. Photogrammetric methods based on “structure from motion” algorithms are used to generate three-dimensional point cloud models of the terrain, which can be compared between data acquisitions of the same location at different times, to infer ground movements. Preliminary results from field tests in Alaska show the potential to detect ground displacements on the order of several to a few tens of centimeters. Such information can be used in a geotechnical context to assess slope performance and the potential for collapse, but also to directly monitor pipeline deformation. Additional validation and testing is required for the method to be operational; a brief discussion of current and future work on validation and method evaluation provides a direction for future research in this area.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 933-938
  • Monograph Title: Pipelines 2016: Out of Sight, Out of Mind, Not Out of Risk

Subject/Index Terms

Filing Info

  • Accession Number: 01608452
  • Record Type: Publication
  • ISBN: 9780784479957
  • Files: TRIS, ASCE
  • Created Date: Jul 14 2016 3:04PM