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An Improved Quadtree Sampling Method for InSAR Seismic Deformation Inversion

Session: Modern Geodesy for Observation and Its Modeling of Earthquake Deformation

Type: Oral

Date: 4/19/2021

Presentation Time: 05:15 PM Pacific

Description: 

With the development of interferometric synthetic aperture radar (InSAR), the seismic deformation observation density increases sharply. Data down-sampling can effectively reduce the observation density and the computational cost for subsequent researches. Considering the saliency of the deformation field, we introduce a saliency-based quadtree algorithm for down-sampling (SQS). Three simulation experiments show that SQS can effectively distinguish the near-field and far-field deformation, reduce the amount of observations while keep the detailed information of the main deformation near the fault. SQS can avoid the interference of far-field local deformation better than the traditional quadtree sampling algorithm (QS), thus obtaining better inversion results. We obtain the co-seismic deformation from the ascending and descending Sentinel-1 for the Dingri, Tibet, China earthquake on March 20, 2020, using QS and SQS for sampling and inversion separately. The results show the advantages of SQS in data volume reduction, observation distribution, anti-interference of local deformation, and inversion accuracy. Our preferred solution based on SQS shows that the Dingri earthquake is an earthquake caused by a normal fault slip. The main slip area is 2.0-5.5 km deep with a maximum slip of 0.68 m. The estimated geodetic moment is 3.14 × 10¹⁷ Nm, corresponding to a magnitude of Mw 5.63.

Presenting Author: Hua Gao

Student Presenter: Yes

Authors