Background . The paper is devoted to the analysis of vertical displacements based on remote sensing data as an identifier of hazardous engineering-geological processes in areas with underground infrastructure. The study was carried out on the example of the of the tunnel between Demiivska and Lybidska stations of the Kyiv subway. In December 2023, processes of uneven compaction and vibration creep of the soil massif around the tunnel lining were detected, and there was a risk of loss of stability of the tunnel structures and an emergency. Methods . This study employs the Differential Interferometric Synthetic Aperture Radar (D-InSAR) method which allows monitoring of soil surface deformations through phase change analysis among radar images. The correction procedures were applied to mitigate noise in processed images caused by temporal and geometric decorrelation, atmospheric disturbances, and other noise interferences. Correction and filtering method, specifically Canny and Sobel linear filters, were used to improve accuracy. Their application to processed satellite images enhances the contours of recorded vertical displacements and reduces geometric distortion noise, preserving the structural integrity of the images. According to our calculations, effective anomaly detection in images of urbanized areas requires a minimum threshold of 25 % in image contrast and clarity. The filters' application for highlighting significant intensity changes achieved a 28 % increase in clarity, indicating high processing effectiveness for further analysis of displacement maps and other parameters related to vertical shifts. Results . Abnormal zones of vertical displacements were identified within the study area based on vertical displacement data. During the 2022-2023 observation period, these zones shifted toward the metro tunnel axis. Vertical displacements directly above the area of subsidence near the 'Rozetka' store were detected during the fifth observation period, October-December 2023, coinciding with the tunnel closure for repairs. Overall, displacement values shifted from negative in 2022 to positive in 2023, suggesting that displacements may have served as an early indicator of underground structure deformation activation. The use of filters allowed for more precise identification of displacement dynamics and localization of deformation zones throughout the observation periods. In the final period, the anomalous zone aligned with the location of tunnel deformations and recorded surface subsidence. Conclusions . Using the example of the distillation tunnel section, we demonstrate the possibility of using the analysis of vertical surface displacements performed by D-InSAR together with a combination of Kenny and Sobel filters to track vertical surface displacements, which is important for monitoring the condition of underground facilities and preventing possible accidents. This study lays the foundation for further development of methodological approaches to the analysis of potential deformations of underground structures based on surface dynamics (vertical displacements). Further improvement of the methodology will help to ensure the accuracy and reliability of data in the context of monitoring underground structures.

The collapse of open-pit coal mine slopes is a kind of severe geological hazard that may cause resource waste, economic loss, and casualties. On 22 February 2023, a large-scale collapse occurred at the Xinjing Open-Pit Mine in Inner Mongolia, China, leading to the loss of 53 lives. Thus, monitoring of the slope stability is important for preventing similar potential damage. It is difficult to fully obtain the temporal and spatial information of the whole mining area using conventional ground monitoring technologies. Therefore, in this study, multi-source remote sensing methods, combined with local geological conditions, are employed to monitor the open-pit mine and analyze the causes of the accident. Firstly, based on GF-2 data, remote sensing interpretation methods are used to locate and analyze the collapse area. The results indicate that high-resolution remote sensing can delineate the collapse boundary, supporting the post-disaster rescue. Subsequently, multi-temporal Radarsat-2 and Sentinel-1A satellite data, covering the period from mining to collapse, are integrated with D-InSAR and DS-InSAR technologies to monitor the deformation of both the collapse areas and the potential risk to dump slopes. The D-InSAR result suggests that high-intensity open-pit mining may be the dominant factor affecting deformation. Furthermore, the boundary between the collapse trailing edge and the non-collapse area could be found in the DS-InSAR result. Moreover, various data sources, including DEM and geological data, are combined to analyze the causes and trends of the deformation. The results suggest that the dump slopes are stable. Meanwhile, the deformation trends of the collapse slope indicate that there may be faults or joint surfaces of the collapse trailing edge boundary. The slope angle exceeding the designed value during the mining is the main cause of the collapse. In addition, the thawing of soil moisture caused by the increase in temperature and the reduction in the mechanical properties of the rock and soil due to underground voids and coal fires also contributed to the accident. This study demonstrates that multi-source remote sensing technologies can quickly and accurately identify potential high-risk areas, which is of great significance for pre-disaster warning and post-disaster rescue.

多年冻土是青藏高原主要的,也是关键的土壤类型。其发生、发展对青藏高原生态、水文等都有重要的影响。自出现合成孔径雷达干涉技术(Interferometric Synthetic Aperture Radar,In SAR)以来,对多年冻土区土壤冻融的研究就出现了一种新的手段,利用该方法可以有效探测近地表土壤的冻融状态。本文首先介绍了多年来各国的星载合成孔径雷达(SAR),然后阐述了该方法的理论基础,最后对差分干涉合成孔径雷达技术(D-In SAR)、小基线子集方法(Small Baseline Subset Approach,SBAS-DIn SAR)和永久散射体技术(Permanent Scatterers,PS)都做出了描述。综上所述,利用适合的SAR数据和有效的In SAR方法研究青藏高原冻土区的冻融状况,可以为今后的科学研究提供范围广、类型多样、精度高的基础数据。

青藏铁路多年冻土区域路基稳定性关系到青藏铁路能否长期安全运营,因此对铁路沿线冻土区进行形变监测有着非常重要的意义。近年来,雷达差分干涉测量(D-InSAR)技术已发展成为监测地表形变的一项重要技术手段。本文利用此技术结合重复轨道ENVISAT ASAR雷达影像数据,获取青藏铁路羊八井-当雄区冻土形变结果,所得形变结果与冻土冻胀融沉的物理变化规律非常符合,说明采用D-InSAR技术提取铁路沿线冻土区域大范围地表形变信息的效果良好。

随着青藏铁路的开通,对青藏高原地区进行形变监测显得尤为重要,由于ALOS卫星PALSAR传感器采用的是L波段,相干性得到明显改善,适合于地形较复杂区域和冻土地区监测。本文选择了青藏高原地区部分时间段的PALSAR数据,采用外部DEM,运用GAMMA软件进行二轨法差分干涉测量,获得该地区的形变图。结合实地情况进行定性分析,其形变较好的符合冻土的物理变化规律,证明了PALSAR数据在青藏高原冻土地区运用于形变监测具有良好的前景。