【摘要】 针对单一轨道合成孔径雷达干涉(InSAR)观测结果难以完整识别滑坡隐患的问题，在小基线子集(SBAS)算法基础上引入时间约束因子，结合时空基线组合优化与升降轨联合解算策略，提出了长时序InSAR二维形变提取模型与方法.针对白玉县和贡觉县交界处的金沙江沿线滑坡易发区，采用2018年-2022年的Sentinel-1A升降轨影像数据集开展时序InSAR形变解算，识别得到了金沙江深切峡谷区域的10处滑坡隐患及其空间分布，探明5处特大滑坡隐患（单体超过5 000万m~3，最大形变速率超过-70 mm/a），进一步解算得到了各滑坡点的滑移方向及量值，并结合降水数据总结归纳了滑坡的季节性演化特征与长期发展趋势.相关研究结果可为该区域的地质灾害防治与重大基础设施建设提供重要的参考数据和信息支撑.更多还原

【Abstract】 The topography along the Jinsha River valley is complex, and the slope toe is seriously eroded by rainwater and river water, which has become one of the hardest hit areas of landslide disasters in China. Due to the difficulty of landslide hazards full identification with single track InSAR observations, a long time-series InSAR two-dimensional deformation extraction model and method was proposed in this paper. Firstly, a time constraint factor was introduced on the basis of SBAS algorithm, combining a spatio-temporal baseline optimization with ascending and descending track solving strategies. Then, being the landslide-prone area along the Jinsha River at the junction of Baiyu and Gongjue counties, a Sentinel-1A ascending and descending imagery of the landslideprone area from 2018 to 2022 was used to carry out the time-series InSAR deformation solution. Ten landslide hazards and their spatial distribution in the deep-cut canyon area of Jinsha River were identified and obtained.And five hidden dangers of mega-landslides were identified(the monomer exceeded 5 010~7 m~3, and the maximum deformation rate exceeded-70 mm/y), solving more the landslide direction and the amount of each landslide.Finally, seasonal evolution characteristics and long-term development trend of the landslides summarized were summarized based on combination of the precipitation data. The relevant research results can provide important reference data and information support for geological disaster prevention and major infrastructure construction in this area.更多还原