The Daguangbao landslide was the largest landslide triggered by the "5.12" Wenchuan Mw 7.9 earthquake. This landslide is among the few superlarge-scale landslides of 1 billion m 3 magnitude worldwide. As the landslide accumulation represents a potential hazard, long-term monitoring and geological interpretation of the Daguangbao landslide is important to reveal the postsliding deformation characteristics and laws of this landslide type. To study the kinematic characteristics 10 years postearthquake, the landslide accumulation deformation was monitored in two stages using different data sets and processing methods. First, regarding the deformation 2 years postearthquake, we selected PALSAR-1 data (21 October 2008 to 14 March 2011) and obtained the LOS (line of sight) direction time series deformation of the landslide using the Small BAseline Subset (SBAS) algorithm. Second, for the last 4.5 years of deformation, Sentinel-1 data sets (26 November 2015 to 8 June 2020) in two ascending and one descending path are experimentally used. The vertical and east-west deformations during this period are obtained. Thickness, topography, precipitation, and other factors are combined to analyze the landslide accumulation deformation. The landslide accumulation volume decreases under gravitational influence, shrinkage is accelerated under precipitation influence, and periodic fluctuations occur, which lag precipitation changes. The maximum vertical direction deformation rate is below 80 mm/year, and the deformation magnitude in the east-west direction is approximately ±35 mm/year. Local deformation is still affected by the surface slope and aspect, and the overall landslide accumulation movement trend involves gathering of the eastern and western parts toward the middle. In the observation window, with the stabilization of accumulation, the deformation tends decrease.
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.
The increasing availability of multiplatform, multiband, very-high-resolution (VHR) satellite synthetic aperture radar (SAR) data has attracted the attention of a growing number of scientists and archeologists. In particular, over the last two decades, archeological research has benefited from SAR development mainly due to its unique ability to acquire scenes both at night and during the day under all weather conditions, its penetration capability, and the provided polarimetric and interferometric information. This paper explored the potential of a novel method (nonlocal (NL)-SAR) using TerraSAR-X (TSX) and Constellation of Small Satellites for Mediterranean Basin Observation (COSMO)-SkyMed (CSK) data to detect buried archeological remains in steep, rugged terrain. In this investigation, two test sites were selected in southern Tunisia, home to some of the most valuable and well-preserved limes from the Roman Empire. To enhance the subtle signals linked to archeological features, the speckle noise introduced into SAR data by the environment and SAR system must be mitigated. Accordingly, the NL-SAR method was applied to SAR data pertaining to these two significant test sites. Overall, the investigation (i) revealed a fortified settlement from the Roman Empire and (ii) identified an unknown urban area abandoned during this period via a field survey, thus successfully confirming the capability of SAR data to reveal unknown, concealed archeological sites, even in areas with a complex topography.
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