Screening of Earthen Levees Using Synthetic Aperture Radar

Aanstoos, J.V., O'Hara C., Prasad, S., Dabbiru, L., Nobrega, R. A. A., & Lee, M. (2009). Screening of Earthen Levees Using Synthetic Aperture Radar. 2009 Fall Meeting. San Francisco, CA, USA: American Geophysical Union.

Earthen levees protect large areas of populated and cultivated land in the US from flooding. As shown recently with hurricanes Katrina and Ike and the recent floods in the Midwest, the potential loss of life and property associated with the catastrophic failure of levees can be extremely large. Over the entire US, there are over 100,000 miles of levee structures of varying designs and conditions. Currently, there are limited processes in place to prioritize the monitoring of large numbers of dam and levee structures. Levee managers and federal agencies need to assess levee health rapidly with robust techniques that identify, classify and prioritize levee vulnerabilities with lower costs than traditional soil-boring programs, which can cost many of millions of dollars and provide information about the subsurface only in the immediate vicinity of a small-diameter borehole. This paper reports preliminary results of a project studying the use of airborne synthetic aperture radar (SAR) as an aid to the levee screening process. The SAR sensor being studied is the NASA UAVSAR (Unmanned Aerial Vehicle SAR), a fully polarimetric L-band SAR which is specifically designed to acquire airborne repeat track SAR data for differential interferometric measurements. The instrument is capable of sub-meter ground sample distance. NASA has imaged with this instrument 230 km of levees along the lower Mississippi River for use in this study. SAR interferometric mode is capable of identifying vertical displacements on the order of a few millimeters. Its multipolarization measurements can penetrate soil to as much as one meter depth. Thus it is valuable in detecting changes in levees that will be key inputs to a levee vulnerability classification system. Once vulnerable levee reaches have been identified, further actions such as more detailed examination or repairs can be focused on these higher-priority sections. We report on the use of various feature detection algorithms being applied to the polarimetry data, including entropy-anisotropy decomposition and methods based on the Grey Level Co-occurrence Matrix (GLCM). The features detected are compared with various ground truth data including soil type maps, soil conductivity measurements, and on site visual inspections.