Safe operation of tailings reservoirs is essential to protect downstream life and property, but current monitoring methods are inadequate in scale and refinement, and most reservoirs are built in low coherence areas far from cities. Use of polarization data to monitor deformation may improve area coherence and thus point selection density. With the example of the Kafang tailings reservoir and dual-polarization Sentinel-1 data from 9 August 2020 to 24 May 2021, homogeneous points of different polarization channels were identified with the hypothesis test of the confidence interval method. Results were fused, and BEST, sub-optimum scattering mechanism (SOM), and equal scattering mechanism (ESM) methods were used to optimize phase quality of persistent scatterer (PS) and distributed scatterer (DS) pixels and obtain more detailed deformation information on the area with time series processing. The fusion of homogeneous point sets obtained from different polarization intensity data increased the number of homogeneous points, which was 3.86% and 8.45% higher than that of VH and VV polarization images, respectively. The three polarization optimization methods improved point selection density. Compared with the VV polarization image, the high coherence point density increased by 1.83 (BEST), 3.66 (SOM), and 5.76 (ESM) times, whereas it increased by 1.17 (BEST), 1.84 (SOM), and 2.04 (ESM) times in the tailings reservoir. The consistency and reliability of different methods were good. By comparing the monitoring results of the three methods using polarization data, the hypothesis test of the confidence interval (HTCI) algorithm, and the polarization optimization method will effectively increase the point selection number of the study area, and the ESM method can show the deformation of tailings area more comprehensively. Monitoring indicated deformation of the tailings reservoir tended to diffuse outward from the area with the largest deformation and was relatively stable.
CITATION STYLE
Wu, H., Zheng, X., Fan, H., & Tian, Z. (2022). Deformation Monitoring of Tailings Reservoir Based on Polarimetric Time Series InSAR: Example of Kafang Tailings Reservoir, China. Remote Sensing, 14(15). https://doi.org/10.3390/rs14153655
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