(a) Magnitude image of the master image where the date is 20181012. (b) Average coherence coefficient of an interference pair. (c) CPs' spatial distribution with a coherent threshold as 0.5. (d) CPs' spatial distribution with a coherent threshold as 0.375. (e) CPs' spatial distribution with a coherent threshold as 0.25. (f) DSPs' spatial distribution. The white pixel (value as 1) represents the measuring point of CPs and DSPs in (c-f).

(a) Magnitude image of the master image where the date is 20181012. (b) Average coherence coefficient of an interference pair. (c) CPs' spatial distribution with a coherent threshold as 0.5. (d) CPs' spatial distribution with a coherent threshold as 0.375. (e) CPs' spatial distribution with a coherent threshold as 0.25. (f) DSPs' spatial distribution. The white pixel (value as 1) represents the measuring point of CPs and DSPs in (c-f).

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The Coherent Pixels Technique Interferometry Synthetic Aperture Radar (CPT-InSAR) method of inverting surface deformation parameters by using high-quality measuring points possesses the flaw inducing sparse measuring points in non-urban areas. In this paper, we propose the Adaptive Coherent Distributed Pixel InSAR (ACDP-InSAR) method, which is an a...

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Context 1
... use TanDEM and precise orbit data to preprocess Sentinel-1 data and then generated the single look complex (SLC) data after coregistration. The date of the main image used in the registration is 12 October 2018, and the amplitude image of the main image is shown in Figure 5a. We follow the steps in Section 2.4 in order to process SLC data. ...
Context 2
... multilook ratio between the azimuth and range is 4:20. The average coherence coefficient of the study area is shown in Figure 5b. According to statistics, the average coherence coefficient of the entire study area is 0.165. ...
Context 3
... selecting CPs, the coherence threshold is 0.5; that is, the pixels with the average coherence coefficient greater than 0.5 are selected as CPs. The results of the traditional CPs selection method with a coherent threshold at 0.5, 0.375 and 0.25 are shown in Figure 5c,d,e, respectively. In Figure 5c,d and Figure 5e, there are 329, 808 and 1872 coherent pixels, respectively. ...
Context 4
... results of the traditional CPs selection method with a coherent threshold at 0.5, 0.375 and 0.25 are shown in Figure 5c,d,e, respectively. In Figure 5c,d and Figure 5e, there are 329, 808 and 1872 coherent pixels, respectively. Although the number of CPs with low threshold is obviously more than the number of CPs with high threshold, the poor phase quality of CPs with low coherence threshold will affect the accuracy of deformation results. ...
Context 5
... results of the traditional CPs selection method with a coherent threshold at 0.5, 0.375 and 0.25 are shown in Figure 5c,d,e, respectively. In Figure 5c,d and Figure 5e, there are 329, 808 and 1872 coherent pixels, respectively. Although the number of CPs with low threshold is obviously more than the number of CPs with high threshold, the poor phase quality of CPs with low coherence threshold will affect the accuracy of deformation results. ...
Context 6
... comparing the spatial relationship between the magnitude map, optical image, land used data and CP, it was observed that CPs are mainly distributed in the built-up areas of the township and on bare rock. It should be noted that the coordinate system in Figure 5 is the SAR coordinate system, while the optical image coordinate system in Figure 4 is the WGS-84 coordinate system. DSP is extracted by using the method outlined in Section 2.2. ...
Context 7
... the candidate DSPs were judged based on the pixel number of SHPs: The candidate DSPs below 48 were rejected, and the remaining candidate DSPs are the final DSPs. The results of DSP pixel selection are shown in Figure 5f, with 4499 measuring points. By comparing the spatial relationships of the magnitude map, optical images and DSP, it was found that DSP points were mainly distributed in agricultural fields and submerged vegetation areas. ...

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... To address the inherent limitation of sparse measurements in non-urban areas in the conventional coherent pixels technique InSAR (CPT-InSAR), an adaptive coherent distributed pixels selection method was integrated into the CPT-InSAR processing chain [35]. DS pixels were identified by classical statistical testing and their phases were also optimized by the joint use of the phase triangle algorithm (PTA) and Eigen decompositionbased maximum likelihood estimator of interferometric phase (EMI) [35]. ...
... To address the inherent limitation of sparse measurements in non-urban areas in the conventional coherent pixels technique InSAR (CPT-InSAR), an adaptive coherent distributed pixels selection method was integrated into the CPT-InSAR processing chain [35]. DS pixels were identified by classical statistical testing and their phases were also optimized by the joint use of the phase triangle algorithm (PTA) and Eigen decompositionbased maximum likelihood estimator of interferometric phase (EMI) [35]. ...
... To address the inherent limitation of sparse measurements in non-urban areas in the conventional coherent pixels technique InSAR (CPT-InSAR), an adaptive coherent distributed pixels selection method was integrated into the CPT-InSAR processing chain [35]. DS pixels were identified by classical statistical testing and their phases were also optimized by the joint use of the phase triangle algorithm (PTA) and Eigen decomposition-based maximum likelihood estimator of interferometric phase (EMI) [35]. ...
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