To perform better monitoring of infrastructure stability in urban and suburban regions, we propose an improved method based on the combined analysis of persistent scatterer (PS) and distributed scatterer (DS). Previous work [13] is extended to explore the DS measurements by exploiting an adaptive homogeneous filter and the capon-based estimator. In this paper, PSs are detected as reference points in the first-tier network. Parameters along network arcs are estimated through the integrated use of beam-forming and an M-estimator. In the second-tier network, we design an adaptive homogeneous filter to cluster statistically homogeneous pixels. DS candidates are then connected to their nearest PS references, establishing the DS network. We estimate DS parameters by using capon beamforming. As the proposed method can provide more complete deformation details of low-coherence targets, it is more effective in stability monitoring. Results from 28 C-band ENVISAT-ASAR scenes of the Hong Kong International Airport are presented in this paper.

To acquire a 3-D deformation of Kilauea's south flank, measurements from GPS and differential interferometric synthetic aperture radar (DInSAR) were integrated based on ant colony optimization. Constraints from GPS and DInSAR measurements were used to establish an energy function based on the Gibbs equation. In this letter, projection vectors used in the energy function were refined depending on the elevation and location of each ground pixel. To achieve stable and fast convergence of the algorithm, the proposed method was tested with different parameters. An ant colony size of 80 with 20 generation loops was designed to derive the 3-D deformation by solving the energy function. Both the ascending and descending interferometric pairs, as well as the GPS observations, of Kilauea volcano, Hawaii, were used in this letter. The results show good consistency with the GPS checkpoints. Root mean squares of 1.40, 1.88, and 2.2 cm were achieved in the directions of north-south, east-west, and zenith, respectively. The derived 3-D deformation maps will allow a better understanding of the source geometry associated with volcanic and seismic activities that result in surface deformation.

The improved spatial resolution of Synthetic Aperture Radar (SAR) images from newly launched sensors has promoted a more frequent use of distributed scatterer (DS) interferometry (DSI) in urban monitoring, pursuing sufficient and detailed measurements. However, the commonly used statistical methods for homogeneous pixel clustering by exploring amplitude information are firstly, computationally intensive; furthermore, their necessity when applied to high-coherent built scenarios is little discussed in the literature. This paper explores the potential of using phase information for the detection of homogeneous pixels on built surfaces. We propose a simple phase-correlated pixel (PCP) clustering and introduce a coherence-weighted phase link (WPL), i.e., PCPWPL, to pursue a faster processing of interferogram phase denoising. Rather than relying on the statistical tests of amplitude characteristics, we exploit vector correlation in the complex domain to identify PCPs with similar phase observations, thus, avoiding the intensive hypothesis test. A coherence-weighted phase linking is applied for DS phase reconstruction. The estimation of geophysical parameters, e.g., deformation, is completed using an integrated network of persistent scatterers (PS) and DS. Efficiency of the proposed method is fairly illustrated by both synthetic and real data experiments. Pros and cons of the proposed PCPWPL were analyzed with the comparison to a conventional amplitude-based strategy using an X-band CosmoSkyMed dataset. It is demonstrated that the use of phase correlation is sufficient for DS monitoring in built scenarios, with equivalent measurement quantity and cheaper computational cost.