Time Series Deformation Monitoring over Large Infrastructures around Dongting Lake Using X‐Band PSI with a Combined Thermal Expansion and Seasonal Model

Abstract

The long-term spatial-temporal deformation monitoring of densely distributed infrastructures near the lake area is of great significance to understand the urban health status and prevent the potential traffic safety problems. In this paper, the permanent scatterer interferometry (PSI) technology with TerraSAR-X imagery over the area around Dongting Lake was utilized to generate the long-term spatial-temporal deformation. Since the X-band SAR interferometric phases are highly influenced by the thermal dilation of the observed objects, and the deformation of large infrastructures are highly related to external temperature, a combined deformation model considering the thermal expansion and the seasonal environmental factors was proposed to model the temporal variations of the deformation. The time series deformation and the thermal dilation parameter over the area were obtained, and a comparative study with the traditional linear model was conducted. The Dongting Lake Bridge and the typical feature points distributed around the lake were analyzed in details. In order to compensate for the unavailability of external in situ measurements over the area, phase residuals and the subsidence generated through Differential Interferometric Synthetic Aperture Radar (D-InSAR) were utilized to verify the accuracy of the obtained deformation time series. Experiment results suggested that the proposed model is suitable and suggested for the selected study site. The root mean square error (RMSE) of the residual phase was estimated as 0.32 rad, and the RMSE compared with D-InSAR derived deformation was ±1.1 mm.

Residue Classification-Based Robust Phase Unwrapping in High-Noise Region

“…When the unit-price of freight is 1, the length of the path is equal to the freight. Let ω 1 = ω 2 = 1 in formula (6), and the value of k is 0 or 1, and the formula (3) is incorporated into the formula (7); then, the formulas (8) and ( 9) are obtained:…”

“…Therefore, the requirements for early warning of natural disasters and emergency responses after disasters are more stringent. Synthetic aperture radar interferometry (InSAR) [1][2][3] is a powerful and well-established remote-sensing technique used to measure many important geophysical parameters, e.g., surface height of topography [4] or ground deformation [5][6][7][8], which plays an important role in early warning of natural disasters and emergency responses after disasters. Phase unwrapping (PU) is one of the key steps of InSAR [9].…”

Determination of periodic deformation from InSAR results using the FFT time series analysis method in Gediz Graben

“…Therefore, while estimating the velocities of PS points, it is necessary to distinguish the periodic and trend components and then estimate the velocity values free from periodic effects. There are a limited number of studies using different deformation models with different methods in monitoring deformations with the PSInSAR method (Li et al 2015 ; Morishita and Hanssen 2015 ; Wang et al 2017 ; Ilieva et al 2019 ; Bao et al 2021 ; Hu et al 2021 ). However, these studies did not use the FFT time series analysis method.…”

Landslide Assessment and Monitoring along the Jinsha River, Southwest China, by Combining InSAR and GPS Techniques

“…The time series InSAR (TS-InSAR) techniques are extensively used for landslide investigation and identification [12], landslide monitoring and mapping [13,14], and stability assessment of landslides [15,16]. Persistent scatterer interferometry (PSI) and distributed scatterer interferometry (DSI) are two main categories of TS-InSAR [17].…”