Insar Error Budget for Large Scale Deformation

Zan, Francesco De; Parizzi, Alessandro; González, Fernando Rodríguez; Ansari, Homa; Gomba, Giorgio; Brcic, Ramon; Eineder, Michael

doi:10.1109/igarss.2019.8900404

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…As revealed by the comparisons, both the bias and dispersion decrease when more interferograms are exploited for phase and, consequently, deformation estimation. The overall performance of the E-StBAS techniques is observed to be worse than the achievable precision of 1-2 mm/year for the Sentinel-1 data stacks [23], [24], while the exploitation of the full covariance matrix helps EMI in retaining this potential performance.…”

Section: B Bias In Displacement Velocitymentioning

confidence: 99%

Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry

Ansari

Zan

Parizzi

2021

IEEE Trans. Geosci. Remote Sensing

128

101

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This article investigates the presence of a new interferometric signal in multilooked synthetic aperture radar (SAR) interferograms that cannot be attributed to the atmospheric or Earth-surface topography changes. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. The presence of such a fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the estimation of Earth surface deformation from SAR time series. Here, the contribution of the mentioned phase component is quantitatively assessed. The biasing impact on the deformation-signal retrieval is further evaluated. A quality measure is introduced to allow the prediction of the associated error with the fading signals. Moreover, a practical solution for the mitigation of this physical signal is discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease significantly. Based on these analyses, we put forward our recommendations for efficient and accurate deformation-signal retrieval from large stacks of multilooked interferograms.

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Section: B Bias In Displacement Velocitymentioning

confidence: 99%

Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry

Ansari

Zan

Parizzi

2021

IEEE Trans. Geosci. Remote Sensing

128

101

View full text Add to dashboard Cite

show abstract

“…As revealed by the comparisons, both the bias and dispersion decrease when more interferograms are exploited for phase and consequently deformation estimation. The overall performance of E-StBAS techniques is observed to be worse than the achievable precision of 1-2 mm/yr for Sentinel-1 data stacks [22], [23], while the exploitation of full covariance matrix helps EMI in retaining this potential performance.…”

Section: B Bias In Displacement Velocitymentioning

confidence: 99%

Study of Systematic Bias in Measuring Surface Deformation with SAR Interferometry

Ansari¹,

Zan²,

Parizzi³

2020

Preprint

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<div>This paper investigates the presence of a new interferometric signal in multilooked Synthetic Aperture Radar (SAR) interferograms which cannot be attributed to atmospheric or earth surface topography changes. The observed signal is short-lived and decays with temporal baseline; however, it is distinct from the stochastic noise usually attributed to temporal decorrelation. The presence of such fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the estimation of Earth surface deformation from SAR time series. <br></div><div>The contribution of the mentioned phase component is quantitatively assessed. For short temporal baseline interferograms, we quantify the phase contribution to be in the regime of 5 rad at C-band. The biasing impact on deformation signal retrieval is further evaluated. As an example, exploiting a subset of short temporal baseline interferograms which connects each acquisition with the successive 5 in the time series, a significant bias of -6.5 mm/yr is observed in the estimation of deformation velocity from a four-year Sentinel-1 data stack. A practical solution for mitigation of this physical fading signal is further discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease to -0.24 mm/yr for the Sentinel-1 time series.</div>Based on these analyses, we put forward our recommendations for efficient and accurate deformation signal retrieval from large stacks of multilooked interferograms.

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Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model

Liu

et al. 2021

International Journal of Applied Earth Observation and Geoinfor

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Insar Error Budget for Large Scale Deformation

Cited by 5 publications

References 11 publications

Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry

Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry

Study of Systematic Bias in Measuring Surface Deformation with SAR Interferometry

Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model

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