Northeastern Section - 49th Annual Meeting (23–25 March)

Paper No. 1
Presentation Time: 4:30 PM


BRUCKNO, Brian S.1, HOPPE, Edward2, VACCARI, Andrea3, ACTON, Scott3 and CAMPBELL, Elizabeth4, (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,

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 conducted a validation study of new interpretations of InSAR data for early detection of geohazards and infrastructure failures, targeting sinkhole development, geotechnical assets, and rock slope hazard. The authors acquired over one million InSAR data points (persistent, distributed, and temporary “scatterers”) within a 40x40 km dataframe in the Valley and Ridge of Virginia. The authors then developed a quantitative field-verification method keyed to asset distress and geomorphological observations, ingested the various scatterers into a GIS dataframe, and georeferenced the data to locations of sinkholes, bridges, fills, pipes, and geotechnical assets. The authors identified kinematic differences in scatterer behavior with respect to their proximity to mapped karst geohazards, and used this method to identify previously-unmapped sinkholes. The authors then used displacement time-series of scatterers to screen for patterns suggesting compromised geotechnical assets and deteriorating infrastructure. In the case of both karst geohazards and infrastructure distress, the field validation yielded robust verification. Lastly, the authors correlated the InSAR data with kinematic analysis of rock slopes using point-cloud data generated by digital photogrammetry and LiDAR, and correlated the data to rock slope behavior. The novel use of temporary scatterers, and their interpretation in the light of persistent and distributed scatterers, greatly increased the utility 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.

  • Bruckno_InSAR_GSA_2014_Lancaster.pptx (22.4 MB)
  • Vaccari&al. - 49thGSA-NE.pptx (35.9 MB)