81 / 2023-04-04 10:05:57
An Adaptive Coherency Matrix Decomposition Based Polarimetric Persistent Scatterer Interferometry Algorithm for Dual-polarization Sentinel-1 data
Ground Deformation Monitoring,InSAR,Persistent Scatterer Interferometry,Polarimetric Optimization
Abstract Pending
Leixin Zhang / China University of Mining and Technology;Key Laboratory of Land Environment and Disaster Monitoring, Ministry of Natural Resources,China university of mining and technology
Feng Zhao / China University of Mining and Technology;Key Laboratory of Land Environment and Disaster Monitoring, Ministry of Natural Resources,China university of mining and technology
Sentinel-1 data have been widely employed for monitoring large-scale ground deformation through persistent scatterer interferometry (PSI). However, most studies have only used the VV polarization channel data, failing to take advantage of dual-polarization Sentinel-1 data. The development of polarimetric PSI (PolPSI) methods has made it possible to combine both VV and VH channels to create a new channel, thereby increasing the efficiency and accuracy of the ground deformation monitoring. Traditional high-efficiency PolPSI methods are unable to adaptively optimize persistent scatterers (PSs) and distributed scatterers (DSs) pixels, while currently proposed adaptive methods suffer from high computational burden. To this end, by using dual-polarization Sentinel-1 data, an efficient adaptive coherency matrix decomposition PolPSI (ADCMD-PolPSI) algorithm is proposed in this study. The algorithm firstly separates PS and DS pixels based on the selection results of homogeneous pixels, then employs different phase optimization strategies for different types of pixels. Finally, by combining the optimized PSs and DSs the optimized interferograms are obtained for the ground deformation retrieve. Results in Southern California demonstrate that the proposed ADCMD-PolPSI can effectively improve the interferometric phase quality of the pixels, and, thus, increase the density of high-quality monitoring pixels. Compared to the results obtained using only VV channel data, ADCMD-PolPSI achieves a 494% improvement in the number of high-quality pixels. Additionally, compared to GPS results, the average root-mean-squared error (RMSE) values of ADCMD-PolPSI, the minimum mean square error (MMSE) method (a DS-InSAR method) and VV method are 5.24 mm, 5.33 mm and 5.41 mm respectively. ADCMD-PolPSI presents slightly better performance of ground deformation monitoring accuracy compared to the other two methods.
Important Date
  • Conference Date

    Oct 26

    2023

    to

    Oct 29

    2023

  • Oct 15 2023

    Abstract Submission Deadline

  • Oct 15 2023

    Draft paper submission deadline

  • Nov 13 2023

    Registration deadline

Sponsored By
International Society for Mine Surveying
China Coal Society
China Surveying and Mapping Society
Organized By
中国矿业大学
中国煤炭科工集团有限公司