地铁施工塌陷的SBAS-InSAR长时序监测与早期识别

Long-term monitoring and early detection of subway construction-induced subsidence using SBAS-InSAR

以2019年青岛市沙子口和胜利桥发生的2处地铁施工塌陷事故为研究对象,基于改进的SBASInSAR技术,利用60景Sentinel-1卫星影像数据,获取地面塌陷前后的青岛市的地表形变时序信息,分析了塌陷事故区地面形变过程与塌陷事故的相关性,提出了利用合成孔径雷达卫星遥感数据开展城市地铁施工地面塌陷监测预警的方法。通过对沙子口和胜利桥2处事故点的长时间序列地表形变监测数据进行统计分析比较,将累积形变量转化为每日平均沉降速率,提出了用于早期识别地表沉降的指标,即在1个周期(12 d)内,平均沉降速率超过0.02 mm/d,而施工预警阈值为连续观测3个周期,平均沉降速率超过0.02 mm/d。

This study focuses on the two subway construction-induced subsidence that occurred at Shazikou and Shengliqiao in Qingdao of China in 2019.Using an improved SBAS-InSAR technique and selecting data from 60 sets of Sentinel-1 satellite images,we captured the temporal information of surface deformation in Qingdao before and after the ground subsidence events.We investigated the correlation between the ground deformation process in the subsidence accident zones and the subsidence incidents.Furthermore,we established a method for utilizing synthetic aperture radar satellite remote sensing data to conduct monitoring and early warning of ground subsidence induced by urban subway construction.By conducting a statistical analysis and comparison of long-term sequential ground deformation monitoring data from the Shazikou and Shengliqiao incident sites,the cumulative deformation variables are transformed into daily average subsidence rates.The paper proposes indicators for the early identification of surface subsidence,where an average subsidence rate exceeds 0.02 mm/d within a single cycle(12 d),while the construction warning threshold is defined after a continuous observation of an average subsidence rate exceeding 0.02 mm/d for three cycles(36 d).