Improved Persistent Scatterer analysis using Amplitude Dispersion Index optimization of dual polarimetry data

Esmaeili, Mostafa; Motagh, Mahdi

doi:10.1016/j.isprsjprs.2016.03.018

Cited by 31 publications

(16 citation statements)

References 25 publications

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“…Therefore, the polarimetric DInSAR (PolDInSAR), or polarimetric PSI (PolPSI), was introduced [12] and developed to improve the detection and characterization of deformation phenomena by increasing the density and quality of valid pixels in comparison with the single polarization case. Starting from the so-called Best method [12], which selects the polarimetric channel with the highest quality estimator among all available channels, PolPSI techniques have been evolved to more sophisticated methods that search the optimal polarimetric channel in a more extended space [13]- [23].…”

Section: Introductionmentioning

confidence: 99%

“…Conventional PolPSI techniques improve interferograms through either the optimization of an amplitude-based criterion (e.g. D A , suitable for PSs) [13]- [15], [23], [24] or the maximization of the coherence stability (γ, suitable for DSs) [13]- [15], [20]- [22], [25]- [28]. Another phase quality metric, the temporal sublook coherence (TSC) [29], [30], has also been proposed to optimize interferograms [30], and it is effective mainly for point-like scatterers (i.e.…”

Section: Introductionmentioning

confidence: 99%

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SMF-POLOPT: An Adaptive Multitemporal Pol(DIn)SAR Filtering and Phase Optimization Algorithm for PSI Applications

Zhao

Mallorquí

2019

IEEE Trans. Geosci. Remote Sensing

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Speckle noise and decorrelation can hamper the application and interpretation of PolSAR images. In this paper, a new adaptive multi-temporal Pol(DIn)SAR filtering and phase optimization algorithm is proposed to address these limitations. This algorithm first categorizes and adaptively filters permanent scatterer (PS) and distributed scatterer (DS) pixels according to their polarimetric scattering mechanisms (i.e. the Scattering-Mechanism based Filtering (SMF)). Then two different POLDIn-SAR phase OPTimization methods are applied separately on the filtered PS and DS pixels (i.e. POLOPT). Finally, an inclusive pixel selection approach is used to identify high quality pixels for ground deformation estimation. 31 full-polarization Radarsat-2 SAR images over Barcelona (Spain) and 31 dual-polarization TerraSAR-X images over Murcia (Spain) have been used to evaluate the performance of the proposed algorithm. The PolSAR filtering results show that the speckle of PolSAR images has been well reduced with the preservation of details by the proposed SMF. The obtained ground deformation monitoring results have shown significant improvements, about ×7.2 (the fullpolarization case) and ×3.8 (the dual-polarization case) w.r.t. the classical full-resolution single-pol amplitude dispersion method, on the valid pixels' densities. The excellent PolSAR filtering and ground deformation monitoring results achieved by the adaptive Pol(DIn)SAR filtering and phase optimization algorithm (i.e. the SMF-POLOPT) have validated the effectiveness of this proposed scheme.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

SMF-POLOPT: An Adaptive Multitemporal Pol(DIn)SAR Filtering and Phase Optimization Algorithm for PSI Applications

Zhao

Mallorquí

2019

IEEE Trans. Geosci. Remote Sensing

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“…More recently, the amplitude dispersion index was optimized through ESPO to improve the PS analysis in [27]. Moreover, an alternative way to optimize the coherence was proposed to decrease the computation time [29].…”

Section: B Espomentioning

confidence: 99%

“…Polarimetric PSI implementations, up to now, either optimize amplitude-based criteria for identification of PS pixels [23], [24], [26], [27], or select the polarimetric channel combination that maximizes the ensemble coherence of surrounding pixels [24]- [26]. The former approach can be quite successful for bright scatterers, such as buildings, but less for natural PS.…”

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confidence: 99%

A New Polarimetric Persistent Scatterer Interferometry Method Using Temporal Coherence Optimization

Sadeghi

Zoej

Hooper

et al. 2018

IEEE Trans. Geosci. Remote Sensing

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Abstract-While polarimetric persistent scatterer InSAR (PSI)is an effective technique for increasing the number and quality of selected PS pixels, existing methods are suboptimal; a polarimetric channel combination is selected for each pixel based either on amplitude, which works well only for high-amplitude scatterers such as man-made structures, or on the assumption that pixels in a surrounding window all have the same scattering mechanism. In this paper, we present a new polarimetric PSI method in which we use a phase-based criterion to select the optimal channel for each pixel, which can work well even in nonurban environments. This algorithm is based on polarimetric optimization of temporal coherence, as defined in the Stanford Method for PS (StaMPS), to identify the scatterers with stable phase characteristics. We form all possible copolar and crosspolar interferograms from the available polarimetric channels and find the optimum coefficients for each pixel using defined search spaces to optimize the temporal coherence. We apply our algorithm, PolStaMPS, to an area in the Tehran basin that is covered primarily by vegetation. Our results confirm that the algorithm substantially improves on StaMPS performance, increasing the number of PS pixels by 48%, 80%, and 82% with respect to HH+VV, VV, and HH channels, respectively, and increasing the signal-to-noise ratio of selected pixels.Index Terms-Polarimetric persistent scatterer InSAR (PSI), Stanford Method for PS (StaMPS), temporal coherence.

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“…Polarimetric optimization becomes a direction of using polarimetric images to monitor deformation. The dual-polarimetric SAR dataset supported by Sentinel-1A and TerraSAR-X has been proved to be able to obtain more PSs with higher coherence [22,27,28]. It has been demonstrated that the polarimetric information introduction can increase the PS density.…”

Section: Introductionmentioning

confidence: 99%

Polarimetric Stationarity Omnibus Test (PSOT) for Selecting Persistent Scatterer Candidates with Quad-Polarimetric SAR Datasets

Luo

Wang

Shen

2020

Sensors

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In the traditional single polarimetric persistent scatterers interferometric (PSI) technology, the amplitude dispersion index (ADI) is usually used to select persistent scatterer candidates (PSC). Obviously, based on single polarimetric information, it is difficult to use the statistical characteristics for comprehensively describing the temporal stability of scatterers, which leads to a decrease in persistent scatterer (PS) density. Considering that the temporal polarimetric stationarity of PS, the paper is based on complex Wishart distribution and proposes the polarimetric stationarity omnibus test (PSOT) for identifying PSC. The nonstationary pixels can be removed by the preset significance threshold, which reduces the subsequent processing error and the calculation cost. Then, the exhaustive search polarimetric optimization (ESPO) method is selected for improving the phase quality of PSCs while suppressing the sidelobe of the strong scatterer effectively. For validating the effectiveness of the proposed method, we select a time-series quad-polarimetric ALOS PALSAR-1 images in an urban area as experimental data and mainly perform five group experiments for detailed analysis, including the PSOT+ESPO, ADI+ESPO, ADI+HH, ADI+HV, and ADI+VV. The results show that the proposed PSOT+ESPO method has a better performance on both PSC selection and interferometric phase optimization aspects than that of other methods. Specifically, compared to the last four methods, both the PSCs and PSs identified by the proposed PSOT+ESPO are more concentrated in the high-coherence region. The PSs with the standard deviation (STD) less than 5mm in the PSOT+ESPO method account for 94% of all PSs, which is greater than that of the ADI+ESPO, ADI+HH, ADI+HV, and ADI+VV methods, respectively.

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Improved Persistent Scatterer analysis using Amplitude Dispersion Index optimization of dual polarimetry data

Cited by 31 publications

References 25 publications

SMF-POLOPT: An Adaptive Multitemporal Pol(DIn)SAR Filtering and Phase Optimization Algorithm for PSI Applications

SMF-POLOPT: An Adaptive Multitemporal Pol(DIn)SAR Filtering and Phase Optimization Algorithm for PSI Applications

A New Polarimetric Persistent Scatterer Interferometry Method Using Temporal Coherence Optimization

Polarimetric Stationarity Omnibus Test (PSOT) for Selecting Persistent Scatterer Candidates with Quad-Polarimetric SAR Datasets

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