Abstract:

To address the high computational burden and low efficiency of time-series InSAR as well as the inadequate accuracy of traditional D-InSAR methods, we propose a TD-InSAR approach using continuous image pairs. This method enables rapid analysis of land surface deformation along long-distance water diversion and transfer projects through the HyP3 cloud computing platform. We validated the accuracy of the TD-InSAR land surface deformation detection by applying it to the Pearl River Delta Water Resources Allocation Project and comparing the results with traditional PS-InSAR monitoring data. Results demonstrate that TD-InSAR’s land surface deformation rate closely aligns with the trends observed in PS-InSAR, with a determination coefficient R² greater than 0.7. Furthermore, TD-InSAR improves accuracy by 52.6% compared to traditional D-InSAR methods. The cloud computing-based TD-InSAR approach significantly reduces the computational burden of time-series InSAR analysis, enhances time efficiency, and is well-suited for large-scale, rapid survey of land surface deformation.

Key words: land surface deformation monitoring, interferometric synthetic aperture radar(InSAR), water diversion and transfer project, HyP3 cloud computing platform, rapid survey of land surface deformation