Complete three-dimensional coseismic displacements due to the 2021 Maduo earthquake in Qinghai Province, China from Sentinel-1 and ALOS-2 SAR images

Abstract

On 22nd May 2021 (local time), an earthquake of M s 7.4 struck Maduo county in Qinghai Province, China. This was the largest earthquake in China since the 2008 Wenchuan earthquake. In this study, ascending/descending Sentinel-1 and advanced land observation satellite-2 (ALOS-2) synthetic aperture radar (SAR) images were used to derive the three-dimensional (3-D) coseismic displacements of this earthquake. We used the differential interferometric SAR (InSAR, DInSAR), pixel offset-tracking (POT), multiple aperture InSAR (MAI), and burst overlap interferometry (BOI) methods to derive the displacement observations along the line-of-sight (LOS) and azimuth directions. To accurately mitigate the effect of ionospheric delay on the ALOS-2 DInSAR observations, a polynomial fitting method was proposed to optimize range-spectrum-split-derived ionospheric phases. In addition, the 3-D displacement field was obtained by a strain model and variance component estimation (SM-VCE) method based on the high-quality SAR displacement observations. Results indicated that a left-lateral fault slip with the largest horizontal displacement of up to 2.4 m dominated this earthquake, and the small-magnitude vertical displacement with an alternating uplift/subsidence pattern along the fault trace was more concentrated in the near-fault regions. Comparison with the global navigation satellite system data indicated that the SM-VCE method can significantly improve the accuracy of the displacements compared to the classical weighted least squares method, and the incorporation of the BOI displacements can substantially benefit the accuracy of north-south displacement. In addition to the displacements, three coseismic strain invariants calculated based on the strain model parameters were also investigated. It was found that the eastern and western parts of the faults suffered more significant strains compared with the epicenter region.

Three-Dimensional Surface Displacements of the 8 January 2022 Mw6.7 Menyuan Earthquake, China from Sentinel-1 and ALOS-2 SAR Observations

“…In this paper, we empirically determined a window size of 40 pixels × 40 pixels, which corresponds to about 2 km × 2 km with the observations' spatial resolution of about 50 m × 50 m. In such a spatial scale of this case study, the displacement gradients can be regarded as constants, and the spatially high-frequency noises in POT observations can also be well suppressed [21].…”

“…Therefore, the WLS-obtained 3D displacements generally have a lower accuracy. Compared with the WLS method, a method for measuring 3D surface displacements with InSAR based on a strain model (SM) and variance component estimation (VCE) (SM-VCE method) [18], which was developed by our team, has proven to be superior in estimating 3D displacements [19][20][21]. The superiority lies in the fact that (1) the SM is applied to describe the correlation of 3D displacements between adjacent points and to establish the relationship between the 3D displacements at a target point and SAR observations at surrounding points, and (2) the well-known VCE algorithm is used to accurately determine the weights of SAR observations in an a posteriori manner.…”

“…The DInSAR, POT, MAI, and/or BOI methods were applied here to obtain the displacement observations from the aforementioned SAR data, and the details of the data processing procedure can be found in [21]. As for the ALOS-2 MAI displacement observation, we conducted a directional filtering and interpolation procedure to mitigate the possible ionospheric noise [24].…”

“…The three strain invariants [21] comprise dilatation, differential rotation, and maximum shear, which are calculated from the 3D displacement gradients, and are independent of any shift and rotation of the coordinate systems [25]. Compared with the displacement fields, the strain fields can provide some unique view about the surface deformations, and they have been widely used for analyzing the inter-seismic deformations on the basis of sparse GNSS (global navigation satellite system) data [31][32][33].…”

“…For example, with respect to the inter-seismic deformations, zones with higher magnitude of the strain invariants indicate a greater potential for stress accumulation and seismic risk [33]. For the high-spatialresolution co-seismic displacements, it is also practical to calculate the strain invariants and to assist the analysis of co-seismic behavior [34][35][36][37] (details about the calculation can be found in [21]). One point that should be noted is that, for the inter-seismic deformations, the deformations are generally continuously occurring; thus, the strain analysis can benefit the assessment of seismic risk.…”