Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1

Abstract

Sentinel-1 data has been widely employed for monitoring large-scale ground deformation with multi-temporal InSAR (MTI). The development of polarimetric MTI (PolMTI) methods has made it possible to combine both VV and VH channels for better ground deformation monitoring with Sentinel-1 data. However, traditional high-efficiency PolMTI methods cannot adaptively optimize both persistent scatterer (PS) and distributed scatterer (DS), while existing adaptive methods have high computational burdens. To address these challenges, we propose an adaptive coherency matrix decomposition method for PolMTI (ADCMD-PolMTI), a novel algorithm that adaptively and effectively optimizes phase of both PS and DS pixels. Applied to Southern California, ADCMD-PolMTI markedly improves interferometric phase quality and achieves a 494% increase in high-quality pixel density compared to the single-polarimetric VV method. Additionally, it demonstrates enhanced ground deformation monitoring accuracy, as evidenced by a lower average RMSE compared to the VV and minimum mean square error (MMSE) methods when comparing against GPS data. While achieving a nearly equivalent number of monitoring pixels as the optimal exhaustive search polarimetric optimization (ESPO) algorithm, ADCMD-PolMTI operates 235 and 13 times faster for PSs and DSs, respectively. With its good adaptive optimization capabilities and computational efficiency, ADCMD-PolMTI offers an advanced solution for large-scale ground deformation monitoring.

Keywords

• Ground deformation monitoring
• InSAR
• multi-temporal InSAR
• polarimetric optimization
• sentinel-1