Southeastern Section - 63rd Annual Meeting (10–11 April 2014)

Paper No. 2
Presentation Time: 1:20 PM

NEW APPLICATIONS FOR INTERFEROMETRIC SYNTHETIC APERTURE RADAR [INSAR]: INTERPRETATION OF PERSISTENT, DISTRIBUTED, AND TEMPORARY SCATTERERS FOR GEOHAZARD AND INFRASTRUCTURE MONITORING AND EVALUATION


BRUCKNO, Brian S.1, HOPPE, Edward2, VACCARI, Andrea3, ACTON, Scott3, CAMPBELL, Elizabeth4 and LEAMAN, Eric5, (1)Virginia Department of Transportation, Materials, 811 Commerce Rd, Staunton, VA 24401, (2)Virginia Center for Transportation Innovation & Research, 530 Edgemont Road, Charlottesville, VA 22903, (3)University of Virginia, Department of Electrical and Computer Engineering, P.O. Box 400743, Charlottesville, VA 22904, (4)Virginia Department of Transportation, 1401 E. Broad St, Richmond, VA 23219, (5)James Madison University, Department of Engineering, 801 Carrier Drive, MSC 4113, Harrisonburg, VA 28807, brian.bruckno@vdot.virginia.gov

As part of the USDOT-funded research program RITA-RS-11-H-UVA, “Sinkhole Detection and Bridge/Landslide Monitoring for Transportation Infrastructure by Automated Analysis of Interferometric Synthetic Aperture Radar [InSAR] Images,” the authors validated new interpretations of InSAR data for early detection of geological hazards and incipient infrastructure failures, targeting sinkhole development, distressed bridges, and rock slope characterization. The authors acquired over one million InSAR data points (persistent, distributed, and temporary “scatterers”) within a 40 x 40 km Area of Interest in the Valley and Ridge Province of Virginia. By ingesting the various scatterers into a GIS dataframe and georeferencing their locations to published maps of sinkholes, locations of repaired sinkholes, and karst terranes, the authors were able to correlate kinematic differences in scatterer behavior with respect to their proximity to karst geohazards, and to identify unmapped sinkholes. Additionally, the authors used displacement time-series developed from the dataset to screen for compromised geotechnical assets and infrastructure. The field inspection of previously-unidentified distressed bridges and other deteriorating assets yielded a positive correlation, strongly validating the methodology implemented. Lastly, the authors correlated the InSAR data characteristics with kinematic analyses of rock slopes using point-clouds generated by digital photogrammetry and LiDAR, and correlated the data to qualitative rock slope behavior. The addition of temporary scatterers (a novel data analysis technique) as support to the data obtained by the established persistent and distributed scatterers greatly enriched the value of the InSAR dataset as a whole.

Disclaimer: The views, opinions, findings and conclusions reflected in this paper are the responsibility of the authors only and do not represent the official policy or position of the US DOT/RITA, or any State or other entity.

Handouts
  • Bruckno_InSAR_GSA_2014_Blacksburg.pptx (16.4 MB)