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[HDS05-P06] Analysis of time lag between surface displacement and precipitation by InSAR time series method
Keywords:PS-InSAR, Sentinel-1A, Time lagged cross correlation
Landslide is a very important type of geological hazard, China is a country with frequent occurrence of geological disasters, and landslide disasters have caused huge economic losses and casualties every year. Persistent Scatterers Interferometry (PSInSAR) is a technique that capable to provide wide-area coverage (thousands of km2) and precise (from millimeter to centimeter resolution), spatially dense information on ground surface deformations, and it is not restricted by weather conditions, which providing a method for landslide research. However, how to better combine PSInSAR method with landslide research, accurate and timely monitoring of landslide motion are still the problem in the exploration stage and needs to be solved. This study takes Shimen County landslide in July 2020 as the research area. Inversion of the surface deformation in the study area during the year before the landslide occurred using PSInSAR method. The correlation between displacement and precipitation was also analyzed with the rainfall data in the study area.
Based on 33 Sentinel-1A SAR images, DInSAR technique and PSInSAR technique were used to analysis the surface deformation after and before the landslide, and the time-series surface deformation patterns were obtained for the period of May 2019-July 2020. Based on the obtained PSInSAR results, three characteristic points within the landslide area were selected, and the characteristics of the temporal deformation in the line of sight (LOS) direction of the points were analyzed one by one.
Precipitation data for the study area for the two years 2018-2020 were obtained based on CLDAS-v2.0 data, and were analyzed from both temporal and spatial perspectives. The cumulative rainfall in 2020 has a large increase compared to the previous two years. The monthly average precipitation one month prior to the landslide occurrence was 705 mm, about 2.3 times the average precipitation for the same month in 2019 (309 mm) and about 3 times the average precipitation for the same month in 2018 (228 mm). The average daily precipitation (162 mm) on the day before the landslide (2020/07/05) was the largest daily precipitation in the past 5 years. Spatially, the areas with higher rainfall are distributed in the northwestern part of Shimen County, the very area where the landslide is located.
The result of PSInSAR is shown in the figure (Fig.). From the results, pixels where the landslide occurred had a different movement pattern from neighboring slopes. Displacement velocities within the landslide area ranged from -10 to -5 mm/year. Three months prior to the landslide, significantly anomalous displacements can have been seen in the PSInSAR result.
Time-lagged cross correlation (TLCC) analysis was performed on the displacement of the landslide area and the accumulated prior precipitation before the image acquisition date. The obtained results showed that among two time series of prior precipitation and ground displacement data, the prior precipitation was the first signal that appeared and had a guiding effect on the ground displacement. And there was a delay of 36 days to 72 days between the prior rainfall event and displacement.
Based on 33 Sentinel-1A SAR images, DInSAR technique and PSInSAR technique were used to analysis the surface deformation after and before the landslide, and the time-series surface deformation patterns were obtained for the period of May 2019-July 2020. Based on the obtained PSInSAR results, three characteristic points within the landslide area were selected, and the characteristics of the temporal deformation in the line of sight (LOS) direction of the points were analyzed one by one.
Precipitation data for the study area for the two years 2018-2020 were obtained based on CLDAS-v2.0 data, and were analyzed from both temporal and spatial perspectives. The cumulative rainfall in 2020 has a large increase compared to the previous two years. The monthly average precipitation one month prior to the landslide occurrence was 705 mm, about 2.3 times the average precipitation for the same month in 2019 (309 mm) and about 3 times the average precipitation for the same month in 2018 (228 mm). The average daily precipitation (162 mm) on the day before the landslide (2020/07/05) was the largest daily precipitation in the past 5 years. Spatially, the areas with higher rainfall are distributed in the northwestern part of Shimen County, the very area where the landslide is located.
The result of PSInSAR is shown in the figure (Fig.). From the results, pixels where the landslide occurred had a different movement pattern from neighboring slopes. Displacement velocities within the landslide area ranged from -10 to -5 mm/year. Three months prior to the landslide, significantly anomalous displacements can have been seen in the PSInSAR result.
Time-lagged cross correlation (TLCC) analysis was performed on the displacement of the landslide area and the accumulated prior precipitation before the image acquisition date. The obtained results showed that among two time series of prior precipitation and ground displacement data, the prior precipitation was the first signal that appeared and had a guiding effect on the ground displacement. And there was a delay of 36 days to 72 days between the prior rainfall event and displacement.