Point target interferometry as applied to the characterization of localized deformation features

Monitoring of ground deformation is a critical component of geotechnical engineering practice. This study investigated the application of synthetic aperture radar interferometry (InSAR) using point target analysis (IPTA) for detecting and characterizing localized deformation features that are often associated with geotechnical engineering activities. In contrast to discrete point in-situ deformation measurement techniques, InSAR can be used to obtain a broader view of deformation processes at a site.;The objectives of this research were to (1) evaluate the feasibility of using IPTA to detect localized deformation features, (2) investigate the influence of SAR data characteristics on the ability to successfully apply IPTA processing and (3) quantify the dependence of the IPTA-derived deformation estimates on the number of SAR acquisitions used to constrain the analysis. To address these objectives, 52 SAR scenes acquired over Los Angeles, CA, during construction of the Los Angeles Metro Rail Red Line between 1992 and 2000 were used. This site was chosen due to the availability of extensive SAR data and the known occurrence of localized settlements along the Red Line alignment during construction.;Results from IPTA processing of the complete dataset successfully demonstrated the ability to detect the localized deformations associated with the subway construction. Deformation time histories for points along the Red Line alignment exhibited episodic settlements that were not observed for points located away from the alignment.;To address the second objective of this study, IPTA processing was applied to subsets of the 52 SAR acquisitions available for the site. The number of interferometric pairs required for successfully applying point target analysis without patch errors was found to range between 20 and 25. The average baseline of interferograms constituting a dataset was hypothesized to have a dominant influence on the ability to successfully apply IPTA processing to a dataset. However, no clear baseline dependence was identified.;To address the third objective, the variability of the estimated rate of deformation was estimated using the standard deviation from one thousand runs of the IPTA analysis as applied to datasets of varying sizes. Irrespective of the deformation rate of a point target, the variability of the estimated deformation rates was found to vary inversely with the size of the dataset used to constrain the analysis. In addition, the coefficient of variation of deformation rates was observed to decrease with an increase in the size of the dataset used for analysis. Irrespective of the deformation rate of a point target, both the mean and the standard deviation of the associated uncertainty (UG) was observed to decrease with an increase in the size of the dataset used for IPTA analysis.