Deformation monitoring of long-span railway bridges based on SBAS-InSAR technology

The deformation monitoring of long-span railway bridges is significant to ensure the safety of human life and property.The interferometric synthetic aperture radar(In SAR)technology has the advantage of high accuracy in bridge deformation monitoring.This study monitored the deformation of the Ganjiang Super Bridge based on the small baseline subsets(SBAS)In SAR technology and Sentinel-1A data.We analyzed the deformation results combined with bridge structure,temperature,and riverbed sediment scouring.The results are as follows:(1)The Ganjiang Super Bridge area is stable overall,with deformation rates ranging from-15.6 mm/yr to 10.7 mm/yr(2)The settlement of the Ganjiang Super Bridge deck gradually increases from the bridge tower toward the main span,which conforms to the typical deformation pattern of a cable-stayed bridge.(3)The sediment scouring from the riverbed cause the serious settlement on the bridge’s east side compared with that on the west side.(4)The bridge deformation negatively correlates with temperature,with a faster settlement at a higher temperature and a slow rebound trend at a lower temperature.The study findings can provide scientific data support for the health monitoring of long-span railway bridges.

Mechanism of deformation around northern Hejin,China,observed by InSAR

Interferometric synthetic aperture radar （InSAR） images reveal deformation around northern Hejin, Shanxi Province. The small baseline subset （SBAS） approach for InSAR-derived deformation indicates that the observed deformation pattern can be characterized by the sum of two phenomena： background subsidence from December 2003 to February 2009 with a cumulative displacement of approximately 5 cm and uplift from Febru- ary 2009 to November 2010 with a cumulative displacement of approximately 2.5 cm. Deformation modeling indicates that the local deformation was caused by the closing and opening of a sill beneath northern Hejin. The modeled sill which is approximately 5 km long, 2 km wide, is centered at 1.5 km depth. The deformation was caused by the withdrawal and influx of subsurface water.

Present-day deformation of Agung volcano,Indonesia, as determined using SBAS-InSAR

Based on ALOS PALSAR images, time series deformation fields of the Agung w^lcann area were obtained using SBAS-InSAR in 2007 -2009. The time series deformation showed obvious inflation around the Agung volcano area, which was positively correlated with time. We modeled the cumulated deformation interferogram based on Mogi point source and vertical prolate spheroid source. The deformation model indicated that the vertical prolate spheroid model fit the observed deformation reasonably well. The magma chamber was loc, ated beneath the eenter of the volcano at a depth of approximately 5 km beneath the summit.

Identify Landslide Precursors from Time Series InSAR Results

Landslides cause huge human and economic losses globally.Detecting landslide precursors is crucial for disaster prevention.The small baseline subset interferometric synthetic-aperture radar(SBAS-InSAR)has been a popular method for detecting landslide precursors.However,non-monotonic displacements in SBAS-InSAR results are pervasive,making it challenging to single out true landslide signals.By exploiting time series displacements derived by SBAS-InSAR,we proposed a method to identify moving landslides.The method calculates two indices(global/local change index)to rank monotonicity of the time series from the derived displacements.Using two thresholds of the proposed indices,more than 96%of background noises in displacement results can be removed.We also found that landslides on the east and west slopes are easier to detect than other slope aspects for the Sentinel-1 images.By repressing background noises,this method can serve as a convenient tool to detect landslide precursors in mountainous areas.