基于小基线集雷达干涉测量的中巴公路盖孜河谷地质灾害早期识别

Early identification of geological hazards in the Gaizi valley near the Karakoran Highway based on SBAS-InSAR technology

中巴喀喇昆仑公路是中巴经济走廊的重要建设部分,但沿线地质灾害多发,对公路正常运营造成严重威胁。尤其是盖孜河谷段地质环境更为复杂,在降水、地震诱发下,崩塌、滑坡、泥石流等地质灾害多发。本研究采用小基线集雷达干涉测量技术(SBAS-InSAR)技术结合实地验证对盖孜河谷段进行地表变形监测和地质灾害早期识别研究,得出如下结论:(1)利用SBAS-InSAR技术得到了中巴公路盖孜河谷段的时间序列地表形变信息,提取了每个形变点的年均形变速率和累计形变量,证实了该方法在山区地质灾害早期识别中的良好优势;(2)选择以公路为中心的10 km缓冲区作为研究范围,利用SBAS-InSAR的方法干涉处理得到研究区2016-2017年雷达视线方向(LOS,Line of Sight)的形变速率值为-76~28 mm/a,结合研究区的坡度、坡向及卫星采集数据的几何姿态等信息将视线方向形变转换到斜坡方向,得到沿斜坡向的最大形变速率值为-157 mm/a。(3)基于斜坡向滑移速率,结合野外考察得到发育在研究区的449处灾害点,包括31处滑坡,416处不稳定斜坡和2处冰川运动,通过遥感解译和野外实地验证识别出区域内23条泥石流沟。(4)利用热带降雨测量任务(TRMM)降水数据对时间序列形变曲线进行分析,得到区域滑坡、不稳定斜坡的发生与强降水相关,且滑移现象滞后于强降水的发生,所以应该重点关注异常降水的发生,为灾害早期识别和防治提供科学依据。

The Karakoram Highway( KKH) is an important part of the China-Pakistan Economic Corridor.However,geological disasters along the route are frequent,posing a serious threat to the normal operation of the highway. In particular,the geological environment of the Gaizi valley in China is more complicated,under the precipitation and induced earthquakes,geological disasters such as collapse,landslide and mudslide occur frequently. This study uses SBAS-InSAR technology combined with field verification to carry out surface deformation monitoring and early identification of geological disasters in the Gaizi valley,the time serious surface deformation information of the Gaizi valley section is obtained,and the annual average deformation rate and cumulative deformation variables of each deformation point are extracted. The 10 km buffer centered on KKH is selected as the research scope,and the deformation rate of the LOS( Line Of Sight) in the study area from 2016 to 2017 ranging from-76 to 28 mm/a is obtained by the SBAS-InSAR method. Combined with the slope and aspect of the study area and the geometrical attitude of the satellite acquisition data,the LOS deformation is converted to the slope direction,and the maximum deformation rate value along the slope direction is-157 mm/a. Based on the surface deformation rates of the slope direction,449 disaster points covering the study area are obtained by field investigation,including 31 landslides,416 unstable slopes and 2 glacial movements. Through remote sensing interpretation and field verification,23 debris flows are identified in the area. By using the TRMM precipitation data to analyze the time series deformation curve, the occurrence of regional landslides and unstable slopes is related to strong precipitation,and the sliding phenomenon lags behind the occurrence of heavy precipitation. Therefore,we should focus on the occurrence of abnormal precipitation. The results provide a scientific basis for early identification and prevention of disasters.