Reduction of Atmospheric Effects on InSAR Observations Through Incorporation of GACOS and PCA Into Small Baseline Subset InSAR

Zhang, Xuesong; Li, Zhenhong; Liu, Zhenjiang

doi:10.1109/tgrs.2023.3281783

Cited by 9 publications

(6 citation statements)

References 65 publications

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“…With the continuous depth of scientific and technological research in countries around the world, coupled with the impact of Yang's double-sewing interference experiment, in the late 1960s, improved intervention technology was introduced, through the joint intervention processing of two SAR images from different periods in the same region, from which the corresponding pixel intervention phase signal was extracted. Thus, the establishment of DEM in the region to three-dimensional surface visualization [12] was achieved, forming the relevant concept of InSAR [13]. InSAR technology has begun to gain traction and has achieved greater development.…”

Section: Related Workmentioning

confidence: 99%

Prediction of the Deformation of Heritage Building Communities under the Integration of Attention Mechanisms and SBAS Technology

Ma,

2023

Electronics

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The protection of heritage building communities is of important historical significance, the occurrence of a landslide is related to the safety and stability of the heritage building, and ground monitoring and forecasting are the key steps for the early warning and timely restoration of the heritage building. This study utilizes remote sensing technology to monitor the ground of a cultural heritage building, and employs a Long Short-Term Memory (LSTM) network for prediction. Firstly, we conducted ground subsidence monitoring within a specific time series of the study area using heritage remote sensing images and SBAS-InSAR technology. Following the subsidence monitoring, and incorporating an attention mechanism, we effectively localized and extracted features of heritage building clusters within the region. This approach efficiently addresses the challenge of feature identification resulting from the dense distribution of buildings and the similarity between various objects. The results indicate that the maximum subsidence rate in the research area reached −60 mm/year, reached a maximum uplift rate of 45 mm/year, and that the maximum cumulative subsidence reached −65 mm. Secondly, for the multi-level, multi-scale, and class-specific objects in remote sensing images, the LSTM network enables adaptive contextual information during deep and shallow feature extraction. This allows for better contextual modeling and the correlation between predicted and actual results reaches a 0.95 correlation, demonstrating the accurate predictive performance of the LSTM network. In conclusion, both LSTM and SBAS technologies play a crucial role in decision-making for heritage buildings, facilitating effective early warning and disaster mitigation.

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Section: Related Workmentioning

confidence: 99%

Prediction of the Deformation of Heritage Building Communities under the Integration of Attention Mechanisms and SBAS Technology

Ma,

2023

Electronics

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“…Before down-sampling, we use ERA5 model-based APS prediction to reduce APS effects in the original InSAR datasets [27,39]. For residual long-wavelength signals (mainly orbital errors) in the interferograms, we apply a three-parameter linear best-fitting plane for reducing those parts after removing the epicentral area.…”

Section: A Case Study On the 2020 Mw 57 Dingjie Earthquakementioning

confidence: 99%

“…Xu et al [37,38] applied the method to subsidence rate calculations at the Cerro Prieto Geothermal Field (CPGF), in which they revealed that the CSS approach could also seize phase discontinuities across adjacent bursts due to misalignment for Sentinel-1 interferometry. The potential of the CSS method is being recognized and ingested into time series analysis [39][40][41]. In practice, nonlinear deformation (e.g., a sudden surface change due to an earthquake or landslide) processes are common on Earth.…”

Section: Introductionmentioning

confidence: 99%

Performance of Common Scene Stacking Atmospheric Correction on Nonlinear InSAR Deformation Retrieval

Zhang,

Feng,

et al. 2023

Remote Sensing

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Atmospheric Phase Screen (APS) is a major noise that suppresses the accuracy of InSAR deformation time series products. Several correction methods have been developed to perform APS reduction in the InSAR analysis, in which an algorithm called Common Scene Stacking (CSS) method draws wide attention in the community as the method was supposed to effectively separate atmospheric contributions without any external data. CSS was initially proposed for solving linearly interseismic deformation. Whether CSS can be applied in nonlinear deformation cases remains unsolved. In this study, we first conduct a series of data simulations including variable elastic deformation components and also propose an iterative strategy to address the inherent weak edge constraint issues in CSS under different deformation conditions. The results show that signal-to-noise ratio (SNR) is a key parameter affecting the performance of CSS in APS separation. For example, the recovery rate of deformation can generally be greater than 80% from datasets with SNR greater than 10 dB. Our results imply that CSS can favor further improvement of InSAR measurement accuracy. The proposed method in this study was applied to assessing deformation history across the 2020 Mw 5.7 Dingjie earthquake, in which logarithmic postseismic deformation history and coseismic contribution can be successfully retrieved once.

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“…The electromagnetic waves emitted by the sensor can cause phase delays during atmospheric propagation, and a 20% change in the relative humidity of water vapor in the atmosphere can lead to deformations on a centimeter scale [12]. The near-surface atmosphere, where water vapor is present, has a relatively mixed composition, including a terrain-dependent atmosphere in the vertical direction and a terrain-independent atmosphere in the horizontal direction, i.e., atmospheric turbulence [13].…”

Section: Introductionmentioning

confidence: 99%

Refined InSAR Mapping Based on Improved Tropospheric Delay Correction Method for Automatic Identification of Wide-Area Potential Landslides

Li,

Wang,

Zhang

et al. 2024

Remote Sensing

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Slow-moving landslides often occur in areas of high relief, which are significantly affected by tropospheric delay. In general, tropospheric delay correction methods in the synthetic-aperture radar interferometry (InSAR) field can be broadly divided into those based on external auxiliary information and those based on traditional empirical models. External auxiliary information is hindered by the low spatial–temporal resolution. Traditional empirical models can be adaptable for the spatial heterogeneity of tropospheric delay, but are limited by preset window sizes and models. In this regard, this paper proposes an improved tropospheric delay correction method based on the multivariable move-window variation model (MMVM) to adaptively determine the window size and the empirical model. Considering topography and surface deformation, the MMVM uses multivariate variogram models with iterative weight to determine the window size and model, and uses the Levenberg–Marquardt (LM) algorithm to enhance convergence speed and robustness. The high-precision surface deformation is then derived. Combined with hotspot analysis (HSA), wide-area potential landslides can be automatically identified. The reservoir area of the Baihetan hydropower station in the lower reaches of the Jinsha River was selected as the study area, using 118 Sentinel-1A images to compare with four methods in three aspects: corrected interferograms, derived deformation rate, and stability of time-series deformation. In terms of mean standard deviation, the MMVM achieved the lowest value for the unwrapped phase in the non-deformed areas, representing a reduction of 56.4% compared to the original value. Finally, 32 landslides were identified, 16 of which posed a threat to nearby villages. The experimental results demonstrate the superiority of the proposed method and provide support to disaster investigation departments.

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Reduction of Atmospheric Effects on InSAR Observations Through Incorporation of GACOS and PCA Into Small Baseline Subset InSAR

Cited by 9 publications

References 65 publications

Prediction of the Deformation of Heritage Building Communities under the Integration of Attention Mechanisms and SBAS Technology

Prediction of the Deformation of Heritage Building Communities under the Integration of Attention Mechanisms and SBAS Technology

Performance of Common Scene Stacking Atmospheric Correction on Nonlinear InSAR Deformation Retrieval

Refined InSAR Mapping Based on Improved Tropospheric Delay Correction Method for Automatic Identification of Wide-Area Potential Landslides

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