Optimized Method for Selecting Common Master Image in PS-DINSAR

Liu, Xiangtong; Cao, Qing; Wang, Shengping; Anastasia, Chernyatyeva

doi:10.25103/jestr.111.25

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…Precise orbit ephemerides (POD) with a positioning accuracy of 5 cm are applied in this case. The master image has the lowest sum of the time and vertical spatial baseline, noise removal and Doppler central spectrum difference [31]. The remaining images are the slave images.…”

Section: The Acquisition Of the Sar Datamentioning

confidence: 99%

An Evaluation of Tropospheric Correction Models for InSAR in Ground Deformation Monitoring: A Case Study in Zhejiang Province, China

Yu,

Li,

et al. 2024

Sustainability

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Interferometric Synthetic Aperture Radar (InSAR) is a powerful and cost-effective technology to monitor ground deformation. Its accuracy is highly influenced by the atmospheric characteristic of the monitoring area. Separating the true ground deformation from atmospheric signals remains one of the major challenges in the application of InSAR. In this paper, the phase-based linear model, high-spatial resolution weather model (MERRA-2 and GACOS) and combination of the MERRA-2 and phase-based linear model are selected, and their performances in reducing the tropospheric delay are assessed based on the detrending standard deviation (DStd) of all Persistent Scattered (PS) points. A framework for the assessment is proposed and applied to a selected region of Shaoxing, Zhejiang Province, China. A total of 26 Sentinel-1A images are used and processed by the method of PS-InSAR. It is found that the phase-based linear model outperforms the other models by at least 6.6% if the whole monitoring time span of the SAR images in the study area is considered. The proper tropospheric correction model in different seasons is not the same. The phase-based linear model is robust against the variations in the atmospheric characteristics of the four seasons.

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Section: The Acquisition Of the Sar Datamentioning

confidence: 99%

An Evaluation of Tropospheric Correction Models for InSAR in Ground Deformation Monitoring: A Case Study in Zhejiang Province, China

Yu,

Li,

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Precise orbit ephemerides (POD) with a positioning accuracy of 5 cm are applied in this case. The master image has the least sum of the time and vertical spatial baseline, noise removal and Doppler central spectrum difference (Liu et al, 2018). The remaining images are the slave images.…”

Section: Acquisition Of the Sar Datamentioning

confidence: 99%

Assessing Tropospheric Correction Models for InSAR Used to Monitor Ground Deformation: A Case Study in Zhejiang Province, China

Sun

et al. 2022

Preprint

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Interferometric Synthetic Aperture Radar (InSAR) is a powerful and cost-effective technology to monitor ground deformation. Its accuracy is highly influenced by the atmospheric characteristic of the monitoring area. Separating the true ground deformation from atmospheric signals remains one of the major challenges in the application of InSAR. In this paper, the phase-based linear model, high spatial-resolution weather model (MERRA-2 and GACOS) and combination of MERRA-2 and phase-based linear model selected, and their performances in reducing the Tropospheric delay are assessed based on detrending standard deviation (DStd) of all Persistent Scattered (PS) points. A framework for the assessment is proposed and applied to a selected region of Shaoxing, Zhejiang Province, China. 26 Sentinel-1A images are used and processed by the method of PS-InSAR. It is found that the phase-based linear model outperforms the other models by at least 6.6% if the whole monitoring time span of the SAR images in the study area are considered. The proper tropospheric correction model in different seasons is not the same. The phase-based linear model is robust against the variations of atmospheric characteristics of the four seasons.

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“…Liu, X., et al (2018a) based on the combination of correlation coefficient algorithm and three baselines minimum sum algorithm, the best common master image is obtained by combining the time baseline, effective spatial baseline, and Doppler center-frequency difference of image pairs. Liu, X., et al (2018b) proposed an error analysis method to calculate the difference evaluation tolerance and total error between the spatial-temporal baseline and Doppler centroid frequency and weighted the interferogram sequence under the condition of removing gross error to obtain the weighted and maximum optimal common master image. However, there are problems in the current studies when considering the effects of the time, space, and Doppler centroid-frequency baselines.…”

Section: Introductionmentioning

confidence: 99%

Selection of Persistent Scatterer Interferometric Synthetic Aperture Radar Master Image Considering Temporal Baseline, Spatial Baseline and Doppler Centroid Frequency Difference

Zhang

Tong

et al. 2020

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper proposed a new algorithm master Image Temporal Spatial baseline, Doppler centroid frequency difference (MITSD) to select the PS-InSAR common master image (CMI), by using the sum of temporal baselines, spatial baselines, and Doppler centroid frequency differences as a reference. The existing persistent scatterer interferometric synthetic aperture radar (PS-InSAR) common master images election method is affected by three baseline factors: temporal baseline, spatial baseline, and Doppler centroid frequency differences, then one single baseline factor in the three baselines being too large or above the baseline threshold will cause the decoherence. This method normalizes the temporal baseline, spatial baseline, and Doppler centroid frequency baseline to the same order of magnitude, and then the results of baseline optimization are summed up as the minimum coherence. Simultaneously，the algorithm in this paper sets each limit the average value of each baseline as a threshold to reduce the influence of a single baseline. The C-band Sentinel-1A single-look complex (SLC) image data (VV-polarization) in the study area was used as experimental data to compare with the MITSD, the current MSTB (minimum sum of three baselines), and CCCM (comprehensive correlation coefficient method). The results showed that (a) the baseline optimization method was more reasonable and reliable in the selection of the master image in PS-InSAR technology; and (b) in this method, the calculation steps were reduced into the calculation process, and the model was more concise than other algorithms.

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Optimized Method for Selecting Common Master Image in PS-DINSAR

Cited by 3 publications

References 17 publications

An Evaluation of Tropospheric Correction Models for InSAR in Ground Deformation Monitoring: A Case Study in Zhejiang Province, China

An Evaluation of Tropospheric Correction Models for InSAR in Ground Deformation Monitoring: A Case Study in Zhejiang Province, China

Assessing Tropospheric Correction Models for InSAR Used to Monitor Ground Deformation: A Case Study in Zhejiang Province, China

Selection of Persistent Scatterer Interferometric Synthetic Aperture Radar Master Image Considering Temporal Baseline, Spatial Baseline and Doppler Centroid Frequency Difference

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