Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR Techniques

In the InSAR solution, uneven distribution of permanent scatterer candidates (PSCs) or slowly decoherent filtering phase (SDFP) pixel density in a region variable radar reflection feature can cause local low accuracy single interferometry. PSCs with higher-order coherence Permanent Scatter (PS-InSAR) are generally distributed those point targets urban built-up areas, and SDFP pixels Small Baseline Subset (SBAS-InSAR) countryside vegetation areas. According to respective reliability PS-InSAR SBAS-InSAR for different features, new land subsidence monitoring method is proposed, which combines PS-SBAS by data fusion interferometry regions. Density-based spatial clustering applications noise (DBSCAN) analysis carried out on processing zone features acquiring boundary fusion. The vector retained dense coherence, used sparse coherence. vertical displacements from integrated obtain optimal subsidence. verification case 38 SAR images acquired Sentinel-1A Suzhou city indicates that proposed automatically choose matched technique according variability improve using method. combined field more representative overall characteristics than PS-InSAR-only SBAS-InSAR-only results, it better suited assessment impact over study area. research results this paper provide useful comprehensive reference planning help decrease Suzhou.