针对传统合成孔径雷达干涉测量（synthetic aperture radar interferometry, InSAR）技术在岩溶塌陷监测中的局限性，提出一种集成永久散射体（permanent scatterer, PS）技术的小基线集（small baseline subset, SBAS）-InSAR地表形变监测方法，用于监测浅埋覆盖层岩溶塌陷群的形变特性。选取贵州省黔南州荔波县洞丢地区作为研究区域，收集2020年1月30日—2022年12月21日期间覆盖该区域的83幅Sentinel-1A影像数据，并应用时序InSAR技术对塌陷区域的形变速率特征进行分析。结果表明：2020—2022年，塌陷区域经历了形变速率的快速发展阶段，监测结果与实际划定的塌陷区域范围相吻合；塌陷区域的最大形变速率为-167.5 mm/a，主要发生在塌陷最为集中的区域。提出一种基于时序InSAR技术的岩溶塌陷群识别判据，该判据通过分析监测区域内任意3点相连的形变累积曲线的变化趋势一致性以及局部突变点，作为群发性岩溶塌陷群发育的早期识别特征。研究成果可为群发性浅埋覆盖层岩溶塌陷发育过程的识别提供重要的参考价值。

Aiming at the limitations of traditional synthetic aperture radar interferometry (InSAR) technology in monitoring karst collapse, a small baseline subset (SBAS)-InSAR surface deformation monitoring method integrating permanent scatterer (PS) technology was proposed to monitor the deformation characteristics of shallowly buried karst collapse groups. The study area was deliberately selected as the Dongdiu District in Libo County, Qiannan Prefecture, Guizhou Province. A dataset composed of 83 Sentinel-1A imagery acquisitions from January 30, 2020, to December 21, 2022, was thoroughly compiled and subsequently analyzed by time-series InSAR in a rigorous manner. The results show that during the period from 2020 to 2022, the collapse-prone areas undergo a phase of accelerated development in deformation rate. The monitoring results closely mirror the actual boundaries of the delineated collapse zones. The maximum deformation rate recorded within the collapse zones is -167.5 mm/a, predominantly occurring in regions with the most concentrated collapses. Moreover, a novel set of criteria for identifying karst collapse clusters was introduced, which was based on time-series InSAR technology. These criteria were founded on the analysis of the uniformity in the trends of deformation accumulation curves and the detection of local abrupt changes among any three interconnected points within the monitoring area. Such features were proposed as early indicators of the development of clustered karst collapses. The research findings are anticipated to provide valuable perspectives for the identification and characterization of the developmental processes associated with clustered, shallowly buried karst collapses.