时序InSAR技术三峡库区藕塘滑坡稳定性监测与状态更新

坡体表面形变是表征坡体稳定性的重要信息,因此,非常有必要对滑坡多发区域进行时序常规变形监测.近年来,星载合成孔径雷达数据由于其覆盖范围大、形变监测精度高的特点,被越来越多的用于山区滑坡识别与探测.首先介绍了联合分布式目标与点目标的时序InSAR方法,并将该方法应用于分析覆盖三峡藕塘滑坡的2007年至2011年的19景ALOS PALSAR数据和2015年至2018年的47景Sentinel-1数据,提取了数据覆盖时间段内的藕塘地区的变形速率.发现相比于2007年至2011年,2015年至2018年新增三处不稳定斜坡.进一步对滑坡的时序变形分析表明,降雨和水位变化是坡体稳定性最大的两个影响因素.实验证明时序InSAR方法可以作为常规形变手段来识别与监测三峡库区等地区潜在的滑坡,为防灾减灾提供支持与依据.      

Mapping of slow landslides on the Palos Verdes Peninsula using the California landslide inventory and persistent scatterer interferometry

Extremely slow landslides, those with a displacement rate <16 mm/year, may be imperceptible without proper instrumentation. These landslides can cause infrastructure damage on a long-term timescale. The objective is to identify these landslides through the combination of information from the California landslide inventory (CLI) and ground displacement rates using results from persistent scatterer interferometry (PSI), an interferometric synthetic aperture radar (InSAR) stacking technique, across the Palos Verdes Peninsula in California. A total of 34 ENVISAT radar images (acquired between 2005 and 2010) and 40 COSMO-SkyMed radar images (acquired between 2012 and 2014) were processed. An InSAR landslide inventory (ILI) is created using four criteria: minimum PS count, average measured ground velocity, slope angle, and slope aspect. The ILI is divided into four categories: long-term slides (LTSs), potentially active slides (PASs), relatively stable slopes (RSSs), and unmapped extremely slow slides (UESSs). These categories are based on whether landslides were previously mapped on that slope (in the CLI), if persistent scatterers (PSs) are present, and whether PSs are unstable or stable. The final inventory includes 263 mapped landslides across the peninsula, of them 67 landslides were identified as UESS. Although UESS exhibit low velocity and are relatively small (average area of 8865 m² per slide), their presence in a highly populated area such as the Palos Verdes Peninsula could lead to destruction of infrastructure and property over the long term.     

Permanent Scatterers for landslide investigations: outcomes from the ESA-SLAM project

Within the SLAM project (Service for Landslide Monitoring), launched in 2003 by the European Space Agency (ESA) the Permanent Scatterers (PS) technique, a multi-image interferometric approach, coupled with the interpretation of aerial-photos and optical satellite images, was carried out for landslide investigations. The PS analysis was applied at a regional scale as support for landslide inventory mapping and at local scale for the monitoring of single well-known slope movements. For the integration of the PS measurements within a landslide inventory the Arno river basin (Italy) was chosen as test site for the presence of a high number of mass movements (to date about 300 areas at high landslide risk and more than 27,000 individual landslides mapped by the institutional authorities). About 350 SAR images have been interferometrically processed by means of the PS technique, with the detection of about 600,000 PS. The use of optical images contributed spatial meaning to the point-wise information provided by the PS, making it easier to identify terrain features related to slope instability and the landslide boundaries. Here we describe the employed methodology and its impact in the updating of a preexisting landslide inventory. 6.8% of the total number of landslides were characterized by ground displacement measurements from the PS: 6.1% of already mapped landslides and 0.8% of new unstable areas detected through the PS analysis. Moreover, most of the PS are located in urban areas, showing that the proposed methodology is suitable for landslide mapping in areas with a quite high density of urbanization, but that over vegetated areas it still suffers from the limitations induced by the current space-borne SAR missions (e.g. temporal de-correlation). On the other hand, the use of InSAR for the monitoring of single slow landslides threatening built-up areas has provided satisfactory results, allowing the measurement of superficial deformations with high accuracy on the landslide sectors characterized by a good radar reflectivity and coherence.     

Permanent Scatterers for landslide investigations: outcomes from the ESA-SLAM project

Within the SLAM project (Service for Landslide Monitoring), launched in 2003 by the European Space Agency (ESA) the Permanent Scatterers (PS) technique, a multi-image interferometric approach, coupled with the interpretation of aerial-photos and optical satellite images, was carried out for landslide investigations. The PS analysis was applied at a regional scale as support for landslide inventory mapping and at local scale for the monitoring of single well-known slope movements. For the integration of the PS measurements within a landslide inventory the Arno river basin (Italy) was chosen as test site for the presence of a high number of mass movements (to date about 300 areas at high landslide risk and more than 27,000 individual landslides mapped by the institutional authorities). About 350 SAR images have been interferometrically processed by means of the PS technique, with the detection of about 600,000 PS. The use of optical images contributed spatial meaning to the point-wise information provided by the PS, making it easier to identify terrain features related to slope instability and the landslide boundaries. Here we describe the employed methodology and its impact in the updating of a preexisting landslide inventory. 6.8% of the total number of landslides were characterized by ground displacement measurements from the PS: 6.1% of already mapped landslides and 0.8% of new unstable areas detected through the PS analysis. Moreover, most of the PS are located in urban areas, showing that the proposed methodology is suitable for landslide mapping in areas with a quite high density of urbanization, but that over vegetated areas it still suffers from the limitations induced by the current space-borne SAR missions (e.g. temporal de-correlation). On the other hand, the use of InSAR for the monitoring of single slow landslides threatening built-up areas has provided satisfactory results, allowing the measurement of superficial deformations with high accuracy on the landslide sectors characterized by a good radar reflectivity and coherence.     

基于SBAS InSAR的鲜水河断裂带蠕滑型滑坡特征研究

鲜水河断裂带是青藏高原东部川滇地块的一条重要边界断裂,全新世以来活动强烈,断裂带沿线岩土体结构破碎强烈,在断裂活动诱发地震、断裂蠕滑和强降雨等因素作用下,断裂带沿线滑坡、泥石流等地质灾害发育密度大,危害严重。在前人研究的基础上,采用短基线集(SBAS InSAR)的方法,基于日本对地观测卫星(ALOS 1)所获得的2007—2011年期间15景PALSAR数据,对鲜水河断裂带道孚至炉霍段的活动速率进行分析计算,获取了该段断裂带内蠕滑型滑坡5年间的时间序列形变特征。研究结果表明：鲜水河断裂带道孚至炉霍段近年来以蠕滑滑动为主,蠕滑速率为(94±078) mm/a,断裂的蠕滑作用对区域构造应力场和断裂带内滑坡具有重要的控制作用,表现为距离鲜水河断裂带越近,影像间相干性越强,稳定的相干点越多,干涉效果越好,滑坡滑动累计位移越大。沿鲜水河断裂道孚至炉霍段,共识别出98个蠕滑型滑坡,沿鲜水河断裂带两侧呈线性展布,并分析了典型蠕滑型滑坡的地表形变特征。基于SBAS InSAR的雷达数据处理方法,可以有效地分析地表的缓慢变形以及区域性蠕滑型滑坡的发育发展变化规律,研究结果对于鲜水河断裂带沿线防灾减灾及类似构造活动地区的地质灾害研究具有一定的指导作用。     

Activity and kinematic behaviour of deep-seated landslides from PS-InSAR displacement rate measurements

Large landslides and deep-seated gravitational slope deformations (DSGSD) represent an important geo-hazard in relation to the deformation of large structures and infrastructures and to the associated secondary landslides. DSGSD movements, although slow (from a few millimetres to several centimetres per year), can continue for very long periods, producing large cumulative displacements and undergoing partial or complete reactivation. Therefore, it is important to map the activity of such phenomena at a regional scale. Ground surface displacements at DSGSD typically range close to the detection limit of monitoring equipment but are suitable for synthetic aperture radar (SAR) interferometry. In this paper, permanent scatterers (PSInSAR?) and SqueeSAR? techniques are used to analyse the activity of 133 DSGSD, in the Central Italian Alps. Statistical indicators for assigning a degree of activity to slope movements from displacement rates are discussed together with methods for analysing the movement and activity distribution within each landslide. In order to assess if a landslide is active or not, with a certain degree of reliability, three indicators are considered as optimal: the mean displacement rate, the activity index (ratio of active PS, displacement rate larger than standard deviation, overall PS) and the nearest neighbor ratio, which allows to describe the degree of clustering of the PS data. According to these criteria, 66% of the phenomena are classified as active in the monitored period 1992–2009. Finally, a new methodology for the use of SAR interferometry data to attain a classification of landslide kinematic behaviour is presented. This methodology is based on the interpretation of longitudinal ground surface displacement rate profiles in the light of numerical simulations of simplified failure geometries. The most common kinematic behaviour is rotational, amounting to 41 DSGSDs, corresponding to the 62.1% of the active phenomena.     

Erratum to: Integration of GPS with InSAR to monitoring of the Jiaju landslide in Sichuan,China

In 2006, a cooperation project between China Geological Survey and the Geological Survey of Canada started the monitoring of the landslide along the deep-cut valley in the western Sichuan using integrated GPS and InSAR observation at the Jiaju landslide. Both GPS and InSAR techniques provided complementary measurements with the GPS providing horizontal movement and InSAR providing vertical motion. Meanwhile, InSAR images demonstrate also an effective tool to recognize new landslides in complex steep mountain region. The GPS observations provide continuous monitoring data while InSAR data provide monthly measurements. The differential InSAR results show a deformation information that divided the Jiaju landslide to two areas, the north and south parts. The north part is sliding greater than the southern part in spatial domain. The sliding was faster in 2008 than that in 2006 in time domain, suggesting a gradual increased acceleration over time. The GPS displacement data during the past 2  years show the northern part slid horizontally 55–207 mm/a and vertically −23 mm/a, while the southern part slid horizontally 12–34 mm/a; and the vertical displacement mainly moved downward 0.05 to 12 mm/a. On average, the observations from December of 2006 to January of 2008 indicate that the northern part is sliding at 41.6 mm/a horizontally and 43.9 mm/a vertically, while the southern part is sliding at 16.1 mm/a horizontally and 17.5 mm/a vertically. The data acquired through the GPS and InSAR are generally comparable. Geological survey revealed some secondary landslides, cracks, and fissures within the deformation of the Jiaju landslide that could be induced by following factors: surface water drainage, river erosion, and slope cutting and overloading.     

利用InSAR技术研究黄土地区滑坡分布

InSAR技术能够获取大面积、连续、高精度的地表垂直形变信息,可用来监测地震、火山、滑坡等自然灾害造成的地表形变。文章介绍了InSAR技术在监测陕北黄土地区滑坡中的应用,首先进行野外地质勘察和TM光学遥感影像解译,接着通过EnviSat SAR数据差分干涉处理,获取研究区干涉形变场,提取出滑坡位移量,最后详细分析黄草湾至董家寺沿线一带的滑坡变形范围,并划定出了4个有一定变形的重点监视区。     

Measuring displacements of the Thompson River valley landslides,south of Ashcroft,BC, Canada,using satellite InSAR

The Thompson River valley, south of Ashcroft in British Columbia, Canada, has experienced several landslides since the mid-1800s. The national railways that run along the valley cross a number of these landslides. All the landslides occur in glacial deposits, typically sliding on weak clay layers. Some have failed rapidly to very rapidly and are currently inactive or showing deformation rates from a few millimeters to centimeters per year. An evaluation of satellite InSAR (Interferometric Synthetic Aperture Radar) using RADARSAT-2 images between September 2013 and November 2015 provides new insight into landslide displacements in the Thompson River valley. This information enhances the ongoing hazard management of unstable terrain. This paper presents the comparison of the InSAR measurements with other instrumentation (GPS and ShapeAccelArrays? -SAA) installed at one moving landslide and then addresses the extent and magnitude of the slope movements observed. InSAR was found to provide similar displacement values to those measured otherwise. The stable location showed displacements of +/?1 mm with an average near zero during the whole monitoring period. Six areas of slope movement were identified within the study area, all within or adjacent to the footprints of past landslides. The average line of sight (LOS) displacement rates range between 11 and 39 mm/year. Most of the landslides exhibited seasonal variations in velocity that corresponds to changes in river elevation in the valley.     

Retrieval of time series three-dimensional landslide surface displacements from multi-angular SAR observations

A major limitation for wide application of Synthetic Aperture Radar (SAR) remote sensing in mapping landslide surface displacements is the intrinsic gap between the ultimate objective of measuring three-dimensional displacements and the limited capability of detecting only one or two-dimensional displacements by repeat-pass SAR observations of identical imaging geometries. Although multi-orbit SAR observations of dissimilar viewing geometries can be jointly analyzed to inverse the three-dimensional displacements, the reliability of inversion results might be highly questionable in case of continuous motion because of the usually asynchronous acquisitions of multi-orbit SAR datasets. Aiming at this problem, we proposed an approach of retrieving time series three-dimensional displacements from multi-angular SAR datasets for step-like landslides in the Three Gorges area in this article. Firstly, time series displacements of a common ground target in the azimuth and line-of-sight (LOS) direction can be estimated using traditional methods of SAR interferometry (InSAR) and SAR pixel offset tracking (POT), respectively. Then, a spline fitting and interpolation procedure was employed to parameterize the displacement history in the sliding/dormant periods of step-like landslides and estimate displacements from multi-angular observations for identical date series. Finally, three-dimensional displacements can be inverted from these synchronized multi-angular measured displacements in traditional ways. As a case study, the proposed method was applied to retrieve the three-dimensional displacements history of the Shuping landslide in the Three Gorges area, China. Comparisons between SAR-measured displacements and measurements of global positioning system (GPS) showed good agreement. Furthermore, temporal correlation analyses suggest that reservoir water level fluctuation and rainfall are the two most important impact factors for the Shuping landslide stability.     

An InSAR and depth-integrated coupled model for potential landslide hazard assessment

Assessing the hazard of potential landslides is crucial for developing mitigation strategies for landslide disasters. However, accurate assessment of landslide hazard is limited by the lack of landslide inventory maps and difficulty in determining landslide run-out distance. To address these issues, this study developed a novel method combining the InSAR technique with a depth-integrated model. Within this new framework, potential landslides are identified through InSAR and their potential impact areas are subsequently estimated using the depth-integrated model. To evaluate its capability, the proposed method was applied to a landslide event that occurred on November 3, 2018 in Baige village, Tibet, China. The simulated results show that the area with a probability of more than 50% to be affected by landslides matched the real trimlines of the landslide and that the accuracy of the proposed method reached 85.65%. Furthermore, the main deposit characteristics, such as the location of maximum deposit thickness and the main deposit area, could be captured by the proposed method. Potential landslides in the Baige region were also identified and evaluated. The results indicate that in the event of landslides, the collapsed mass has a high probability to block the Jinsha River. It is therefore necessary to implement field monitoring and prepare hazard mitigation strategies in advance. This study provides new insights for regional-scale landslide hazard management and further contributes to the implementation of landslide risk assessment and reduction activities.

     

金沙江下游金坪子Ⅱ区低速滑坡活动机理初探

金坪子滑坡是金沙江下游乌东德水电站下游方向距离大坝最近的一处巨型深厚崩坡积碎屑土古滑坡,以Ⅱ区活动部分为研究对象,在大量勘察试验成果以及长达11a的精确监测基础上,分析滑坡岩土体的物理力学性质以及滑坡的长期动态特征,特别是滑坡与降雨和地下水的动态响应关系,并基于Green-Ampt降雨入渗模型研究了降雨直接入渗补给地下水的可能性,利用极限平衡法探讨了理想刚塑性条件下该滑坡所受力的平衡关系,进而分析滑坡的活动机理。研究结果表明,滑坡的长期持续活动是滑带土黏性流变特征的表现,地表和深部位移均表现为牵引活动模式,地表自2005~2016年的平均位移速率为0.19~0.87mm ·d-1,深部以基底滑动为主,不同部位具有不同程度的内部变形。降雨是影响滑坡动态的最主要因素,在理想情况下,降雨很难直接入渗补给滑区地下水,地下水动态变化缓慢,与滑坡活动有一定正相关关系,但作用并不显著。与一些动态特征直接受地下水位影响的浅层低速滑坡不同,金坪子Ⅱ区的活动机理更可能是降雨在滑坡上部一定深度范围内形成暂态饱和区,滑体容重和渗透作用的变化影响了滑坡的动态。     

Detection and accuracy of landslide movement by InSAR analysis using PALSAR-2 data

Interferometric synthetic aperture radar (InSAR) analysis is a radar technique for generating large-area maps of ground deformation using differences in the phase of microwaves returning to a satellite. In recent years, high-resolution SAR sensors have been developed that enable small-scale slope deformation to be detected, such as the partial block movement of a landslide. The L-band SAR (PALSAR-2) is mounted on Advanced Land Observing Satellite-2 (ALOS-2), which was launched on 24 Mar. 2014. Its main improvements compared with ALOS are enhanced resolution of as high as 3 m with a high-frequency recurrence period (14 days). Owing to its high resolution and the use of the L-band, PALSAR-2 can obtain reflective data passing through a tree canopy surface, unlike the other synthetic aperture radars. Therefore, the coherence of InSAR in mountainous forest areas is less likely to decrease, making it advantageous for the extraction of slope movement. In this study, to verify the accuracy of InSAR analysis using PALSAR-2 data, we compared the results of InSAR analysis and the measurement of the displacement in a landslide by global navigation satellite system (GNSS) observation. It was found that the average difference between the displacements obtained by InSAR analysis and the field measurements by GNSS was only 15.1 mm in the slant range direction, indicating the high accuracy of InSAR analysis. Many of the areas detected by InSAR analysis corresponded to the locations of surface changes due to landslide activity. Additionally, in the areas detected by InSAR analysis using multiple datasets, the ground changes due to landslide movement were confirmed by site investigation.     

基于InSAR和光学遥感的贵州鬃岭采煤滑坡识别与危险性评价

贵州鬃岭滑坡群具有孕灾规律性强、 发育集中密集、 威胁严重等特点.文章利用InSAR和光学遥感进行精细识别,获取了区域滑坡灾害信息,总结了鬃岭区域滑坡变形破坏模式,基于此建立了该地区的滑坡风险评价的体积-距离统计公式,并对典型灾害体进行了计算,获得了一些重要认识.地下采煤活动是引起鬃岭桌山边缘山体变形的主要原因;InS...     

Geometric and kinematic characterization of landslides affecting urban areas: the Lungro case study (Calabria,Southern Italy)

The geometric and kinematic characterization of landslides affecting urban areas is a challenging goal that is routinely pursued via geological/geomorphological method and monitoring of ground displacements achieved by geotechnical and, more recently, advanced differential interferometric synthetic aperture radar (A-DInSAR) data. Although the integration of all the above-mentioned methods should be planned a priori to be more effective, datasets resulting from the independent use of these different methods are commonly available, thus making crucial the need for their standardized a posteriori integration. In this regard, the present paper aims to provide a contribution by introducing a procedure that, taking into account the specific limits of geological/geomorphological analyses and deep/surface ground displacement monitoring via geotechnical and A-DInSAR data, allows the a posteriori integration of the results by exploiting their complementarity for landslide characterization. The approach was tested in the urban area of Lungro village (Calabria region, southern Italy), which is characterized by complex geological/geomorphological settings, widespread landslides and peculiar urban fabric. In spite of the different level of information preliminarily available for each landslide as result of the independent use of the three methods, the implementation of the proposed procedure allowed a better understanding and typifying of the geometry and kinematics of 50 landslides. This provided part of the essential background for geotechnical landslide models to be used for slope stability analysis within landslide risk mitigation strategies.     

A finite element approach for the analysis of active slow-moving landslides

In the present paper, a finite element approach is proposed to analyse the mobility of active landslides which are controlled by groundwater fluctuations within the slope. These landslides are usually characterised by low displacement rates with deformations that are essentially concentrated within a narrow shear zone above which the unstable soil mass moves with deformations of no great concern. The proposed approach utilises an elasto-viscoplastic constitutive model in conjunction with a Mohr-Coulomb yield function to describe the behaviour of the soil in the shear zone. For the other soils involved by the landslide, an elastic model is used for the sake of simplicity. A significant advantage of the present method lies in the fact that few constitutive parameters are required as input data, the most of which can be readily obtained by conventional geotechnical tests. The rest of the required parameters should be calibrated on the basis of the available monitoring data concerning the change in the piezometric levels and the associated movements of the unstable soil mass. After being calibrated and validated, the proposed approach can be used to predict future landslide movements owing to expected groundwater fluctuations or to assess the effectiveness of drainage systems which are designed to control the landslide mobility. The method is applied to back-predict the observed field behaviour of three active slow-moving landslides documented in the literature.     

Characteristics of a rapid landsliding area along Jinsha River revealed by multi-temporal remote sensing and its risks to Sichuan-Tibet railway

The Sichuan-Tibet railway goes across the Upper Jinsha River, along which a large number of large historical landslides have occurred and dammed the river. Therefore, it is of great significance to investigate large potential landslides along the Jinsha River. In this paper, we inspect the deformation characteristics of a rapid landsliding area along the Jinsha River by using multi-temporal remote sensing, and analyzed its future development and risk to the Sichuan-Tibet railway. Surface deformations and damage features between January 2016 and October 2020 were obtained using multi-temporal InSAR and multi-temporal correlations of optical images, respectively. Deformation and failure signs obtained from the field investigation were highly consistent. Results showed that cumulative deformation of the landsliding area is more than 50 cm, and the landsliding area is undergoing an accelerated deformation stage. The external rainfall condition, water level, and water flow rate are important factors controlling the deformation. The increase of rainfall, the rise of water level, and faster flow rate will accelerate the deformation of slope. The geological conditions of the slope itself affect the deformation of landslide. Due to the enrichment of gently dipping gneiss and groundwater, the slope is more likely to slide along the slope. The Jinsha River continuously scours the concave bank of the slope, causing local collapses and forming local free surfaces. Numerical simulation results show that once the landsliding area fails, the landslide body may form a 4-km-long dammed lake, and the water level could rise about 200 m; the historic data shows that landslide dam may burst in 2–8 days after sliding. Therefore, strategies of landslide hazard mitigation in the study area should be particularly made for the coming rainy seasons to mitigate risks from the landsliding area.

     

Deep-seated gravitational slope deformations triggered by extreme rainfall and agricultural practices (eastern Michoacan,Mexico)

The study of deep-seated gravitational slope deformations (DSGSD) in Mexico is scarce; therefore, their localization and causes are highly overlooked. The present paper examines the characterization of the DSGSD of Jungapeo and Las Pilas in eastern Michoacan state, currently active and endangering their inhabitants. An integrated study, including detailed lithology, morpho-structural inventories, analysis of land use, and pluviometric regime, was performed and complemented with differential global positioning system monitoring networks. Both landslides developed over highly weathered volcano-sedimentary rocks. On the one hand, the Jungapeo landslide has an estimated volume of 990,455 m³ with steady decreasing velocity rates from 41 to 15 cm/month in the first monitoring period to 13–3 cm/month in the last one. On the other hand, the Las Pilas landslide estimated volume is about 1,082,467 m³ with a stable velocity rate of 1.3 to 0.1 cm/month. Despite the multi-storeyed style of activity, two behaviors of instability were distinguished: slow deformation and secondary landslide stages. The conditioning factors for slow deformation in both DSGSD are the combination of weathered lithology with clay- and sand-rich content, and the shift toward intensive monoculture. The triggering factor is related to excess water produced by an inefficient flood-irrigation system that also generates an atypical acceleration behavior in both landslides during the dry season. The DSGSD activity thus predisposes the generation of tension cracks and secondary scarps from which the collateral landslides are triggered by atypical rainfall, such as that of 2010.     

藏东冻土区滑坡形变时序InSAR监测分析

受气候暖湿化和冻融作用的影响,近年来西藏东部地区的山体滑坡多发频发,对人民生命财产安全造成严重威胁,制约了当地经济社会发展,因此,迫切需要利用有效手段对滑坡灾害隐患开展大范围调查与早期识别。以藏东317国道矮拉山地区为例,利用小基线集时序InSAR（Interferometric Synthetic Aperture Radar）技术,分别对2017年3月—2019年7月期间Sentinel-1A SAR升、降轨数据集进行地表形变监测分析,获取了该地区滑坡体隐患的分布情况,并讨论了滑坡历史形变演化特征及成因。结果表明：大部分区域较为稳定,滑坡隐患主要集中在山谷两侧,升降轨InSAR提高了滑坡监测识别的准确性和覆盖度;冻融滑坡形变过程与降雨型滑坡存在差异,呈现平稳期和失稳期交替出现的季节性变化特征;形变过程主要受冻融和降雨影响,两者共同作用加速坡体变形。实验结果验证了InSAR技术能够有效弥补传统监测手段的不足,可在高山冻土区滑坡隐患早期识别与监测防治中发挥重要作用。