2026-04-14T03:24:51Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4256442026-01-21T06:27:25Zcom_2072_1033col_2072_452950

Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 Zhang, Leixin Zhao, Feng Wang, Yunjia Mallorquí Franquet, Jordi Joan Wang, Teng Zhang, Yuxuan Hu, Zhongbo Du, Sen Fernández Torres, José Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar Ground deformation monitoring InSAR Multi-temporal InSAR Polarimetric optimization Sentinel-1 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. This work was funded by National Key R&D Program of China (grant number 2022YFE0102600), by the National Natural Science Foundation of China (grant number U22A20598), by China Postdoctoral Science Foundation (grant numbers 2023T160685, 2020M671646), by National Natural Science Foundation of China (grant number 42004011),by Young Elite Scientists Sponsorship Program by CAST (grant number 2023QNRC001-YESS20230599), by Xin-Jiang key research and development program (grant number 2022B03003-1) and in part by the China Scholarship Council (grant number 202306420009). This work was supported by the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development (ERFD) under Project(PID2020-117303GB-C21/AEI/10.13039/501100011033). And this research has be also partially supported by grant G2HOTSPOTS (PID2021-122142OB-I00) from the MCIN/AEI/10.13039/501100011033/FEDER, UE, by the Construction Program of Space-Air-Ground-Well Cooperative Awareness Spatial Information Project (grant num-ber B20046). Peer Reviewed Postprint (published version) 2025 Article https://www.tandfonline.com/doi/full/10.1080/17538947.2024.2447335 http://creativecommons.org/licenses/by-nc/4.0/ Open Access Attribution-NonCommercial 4.0 International