Classification of Levees Using Polarimetric Synthetic Aperture Radar (SAR) Imagery

Dabbiru, L., & Aanstoos, J.V. (2010). Classification of Levees Using Polarimetric Synthetic Aperture Radar (SAR) Imagery. Proc. 2010 39th IEEE Applied Imagery Pattern Recognition Workshop. Washington, DC: IEEE.

The recent catastrophe caused by hurricane Katrina emphasizes the importance of timely examination of levees to improve the condition of those that are prone to failure during floods. On-site inspection of levees is costly and time-consuming, so there is a need to develop efficient techniques based on remote sensing technologies to identify levees that are more vulnerable to failure under flood loading. This research uses NASA JPL’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) backscatter data for classification and analysis of earthen levees. The purpose of this research is to detect the problem areas along the levee such as through-seepage, sand boils and slough slides. Since UAVSAR is a quad-polarized L-band (λ = 25 cm) radar, the radar signals penetrate into the soil which aids in detecting soil moisture variations. Both supervised and unsupervised classification techniques are used and these techniques are based on the polarimetric decomposition parameters: entropy (H), anisotropy (A) and alpha (α). A 3x3 coherency matrix is calculated for each pixel of the radar’s multi look cross-product (MLC) backscatter data using ESA’s Polsarpro software and is used to retrieve H, A and α parameters. Different scattering mechanisms like surface scattering, dihedral scattering and volume scattering are observed to distinguish different targets along the levee.