Measuring precursory movements of the recent Xinmo landslide in Mao County,China with Sentinel-1 and ALOS-2 PALSAR-2 datasets

The Xinmo landslide occurred in the early morning of 24 June 2017 at about 5:38 am local time. This catastrophic event caused enormous casualties and huge economic losses in Xinmo Village, Mao County, Sichuan Province, China. In this study, Synthetic Aperture Radar (SAR) datasets acquired by X-band TerraSAR-X, Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard the Advanced Land Observing Satellite-2 (ALOS-2), and C-band Sentinel-1 over the disaster area were collected and analyzed to characterize this landslide. The high-resolution TerraSAR-X intensity images were used to evaluate the landslide disaster and delineate the sliding area. Afterwards, two ALOS-2 PALSAR-2 image pairs and a stack of 45 Sentinel-1 images were processed to detect precursory movements of the landslide surface, using the conventional differential InSAR (DInSAR) method and advanced time series InSAR analysis. The unstable source area near the ridge was identified from the displacement rate map derived from Sentinel-1 datasets. The maximum displacement rate detected at the source area was ?35mm/year along the radar line of sight (LOS) direction. The time series of LOS displacements over 2 years presents an easily discerned seasonal evolution pattern. In particular, a sudden acceleration of the displacement, dozens of days before the collapse was clearly captured by the Sentinel-1 observations, which might suggest that early warning of landslide disasters is possible given the availability of operational SAR data acquired in frequent repeat-pass mode, such as the Sentinel-1 twin-satellite constellation.     

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

Post-event Interferometric Synthetic Aperture Radar (InSAR) analysis on a stack of 45 C-band SAR images acquired by the ESA Sentinel-1 satellites from 9 October 2014 to 19 June 2017 allowed the identification of a clear precursory deformation signal for the Maoxian landslide (Mao County, Sichuan Province, China). The landslide occurred in the early morning of 24 June 2017 and killed more than 100 people in the village of Xinmo. Sentinel-1 images have been processed through an advanced multi-interferogram analysis capable of maximising the density of measurement points, generating ground deformation maps and displacement time series for an area of 460 km² straddling the Minjiang River and the Songping Gully. InSAR data clearly show the precursors of the slope failure in the source area of the Maoxian landslide, with a maximum displacement rate detected of 27 mm/year along the line of sight of the satellite. Deformation time series of measurement points identified within the main scarp of the landslide exhibit an acceleration starting from April 2017. A detailed time series analysis leads to the classification of different deformation behaviours. The Fukuzono method for forecasting the time of failure appear to be applicable to the displacement data exhibiting progressive acceleration. Results suggest that satellite radar data, systematically acquired over large areas with short revisiting time, could be used not only as a tool for mapping unstable areas, but also for landslide monitoring, at least for some typologies of sliding phenomena.     

滑坡灾害InSAR应急排查技术方法研究

研究探索了一条以InSAR变形为主,辅助光学遥感、地貌和地质条件特征,进行活动性滑坡快速排查的技术方法,并以四川省雷波县域为例进行了实验。应用4种SAR数据（PALSAR-1升轨、Sentinel-1 A/B升、降轨和PALSAR-2降轨数据）进行合成孔径雷达干涉（Interferometric Synthetic Aperture Radar,InSAR）处理,共解译活动性地质灾害163处,并分析了其时空分布规律,获得了几点认识:（1）InSAR技术能够追溯滑坡长期微小变形,从而实现活动性滑坡的有效识别;（2）多时段、多角度和多分辨率SAR数据的综合使用,可以有效克服滑坡观测的阴影叠掩、失相干等问题,提高滑坡（尤其是高位滑坡）识别的效果、效率和时效性;（3）与地面调查结果比较,InSAR识别的滑坡更全面、规模更准确,对高位滑坡和集中分布滑坡识别更有效,可以作为现今地质灾害排查的重要手段之一;（4）雷波县地质灾害主要分布在金沙江及美姑河沿岸,北向坡和30°~40°坡度是地质灾害高发区,除寒武系、奥陶—志留系地层发生地质灾害比例较高,其它各地层总体分布较均一。      

D-InSAR-based landslide location and monitoring at Wudongde hydropower reservoir in China

Differential synthetic aperture radar interferometry (D-InSAR) has become a useful technique for monitoring ground movement. The technique enables the analysis of very small ground movements in continuous, large areas and has the advantages of high accuracy, high resolution, all-weather adaptability, low cost, and inaccessible area coverage. Thus, D-InSAR has been widely used in the investigation of geologic hazards, such as subsidence, landslide, earthquake, and volcanic activity. In this paper, D-InSAR is used to locate and monitor landslide movement in the wide area of Wudongde Hydropower Reservoir in Jinsha River, China. Five SAR acquisitions are obtained by using the phased array-type L-band synthetic aperture radar sensor of the Advanced Land Observing Satellite. Detailed moving displacement maps in two time periods are derived by using the D-InSAR technique, and potentially moving landslide areas, as well as landslide hazard areas, are then located. The L1R-6 landslide, which is in active state, is investigated in detail. The deforming tendency obtained via D-InSAR is consistent with that obtained via global positioning system (GPS) monitoring. Error analysis of the D-InSAR results is also conducted. Finally, the grid function interpolation method of error reduction, which combines D-InSAR and GPS, is proposed to reduce the single-point error in D-InSAR monitoring and is further verified by the considerable improvement in the accuracy of L1R-6 landslide monitoring.     

Sentinel-1数据在西南山区水库变形斜坡InSAR监测中的适用性评价:以溪洛渡水库为例

Sentinel卫星凭借其超高的辐射分辨率、稳定的轨道系统、较大的覆盖能力、较短的重返时间、可免费下载的数据,在斜坡灾害识别监测方向上有广泛的应用。自1963年意大利瓦伊昂特大滑坡发生以来,岸坡地质灾害一直是峡谷区水库关注的主要问题之一。以金沙江上游溪洛渡水库区为例,结合PALSAR-2、TerraSAR-X数据,评价Sentinel-1 SAR数据在西南山区水库变形斜坡InSAR监测中的适用性,以理论结合实际结果分析Sentinel-1数据是否可以在一定条件下替代其他商业数据,为今后相关行业应用提供参考。结果显示:Sentinel-1数据在研究区可解译的变形斜坡约200处,类型有滑坡、危岩体和塌岸;经现场核查,Sentinel-1数据解译的最小变形斜坡投影面积约为2400 m2,约35 m(长)×77 m(宽)大小,共16个变形像元聚集。高山峡谷区叠掩、阴影现象严重,通过对雷达常用观测模式下的SAR数据的比较,在SAR数据交集区域,有效观测面积为Sentinel-1升轨70.3%,Sentinel-1降轨68.9%,PALSAR-2升轨70.4%,PALSAR-2降轨67.6%,TerraSAR-X降轨52.5%,在不考虑分辨率的情况下,在库区Sentinel-1数据与其他两种SAR数据观测能力相比持平或更优秀。6月至11月初是溪洛渡水库的水位上升期,周边植被发育较好,造成数据相干性较差,2017年后Sentinel-1A(1B)双星拍摄获取的SAR数据量增加,高频观测可使相干性提高,利用2017年后该卫星数据可有效识别水库蓄—排水周期内的区域性变形斜坡发育变化情况。当长时间缺失SAR数据时,会造成最近一对SAR数据间的某些像元测量的变形超过其InSAR最大量程,解缠时丢失相位周期。Sentinel-1数据由于连续性较好,监测斜坡的变形趋势较为连续,因此更适合连续小变形的趋势识别。      

Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry

This paper is addressed to readers without advanced knowledge of remote sensing. It illustrates some current and potential uses of satellite Synthetic Aperture Radar interferometry (InSAR) for landslide assessment. Data acquired by SAR systems can provide 3D terrain models and be used to assist in regional scale investigations, e.g. aimed at evaluation of susceptibility of slopes to failure. Under favourable environmental conditions, the innovative Permanent Scatterers (PS) technique, which overcomes several limitations of conventional SAR differential interferometry (DInSAR) applications in landslide studies, is suitable for monitoring slope deformations with millimetric precision. The PS technique combines the wide-area coverage typical of satellite imagery with the capability of providing displacement data relative to individual image pixels. With the currently available radar satellites, however, only very slow ground surface displacements can be reliably detected and measured. The presented case study of a landslide from the Liechtenstein Alps indicates that the most attractive and reliable contribution provided by this remote sensing technique lies in the possibility of (i.) wide-area qualitative distinction between stable and unstable areas and (ii.) qualitative (relative) hazard zonation of large, slow landslides based on the identification of segments characterised by different movement rates. Since only the radar line of sight projection of the displacements can be detected, a quantitative exploitation of the PS data is possible only where sufficient ground truth is available. In site specific or single landslide investigations the PS data can represent a very useful complementary data source with respect to the information acquired through ground based observations and in situ surveying. However, the difficulties associated with the feasibility assessments of the applicability of SAR data to local scale problems, as well as with the interpretation of PS results, require a close collaboration between landslide experts and specialists in advanced processing of radar satellite data. The interpretation of the exact geotechnical significance of small, radar sensed ground surface deformations is challenging, especially where ground truth is lacking. Although any ground deformation is potentially of interest to an engineering geologist, detection of movements in both vertical and horizontal directions is needed in the case of landslides to evaluate slope failure mechanisms. With their high radar viewing angles, however, the current space-borne systems can detect only a fraction of the horizontal component of movement. It is expected that the upcoming SAR dedicated missions with new sensors and different acquisition geometries, combined with the rapid developments in the field of advanced radar data processing, will allow a full 3D reconstruction of deformation data and help to further reduce the current limitations of the PS and similar DInSAR approaches.     

Structural control on the kinematics of the deep-seated La Clapière landslide revealed by L-band InSAR observations

The objective of this work is to document the deformation pattern of the deep-seated La Clapière landslide for the period 2007–2010 from the combination of L-band synthetic aperture radar (SAR) interferograms, ground-based total station measurements and identification of the slope geomorphological structures. The interferograms are calculated for pairs of ALOS/PALSAR images at a time interval of 46 days. The displacement field derived from the interferograms reveals a non-uniform displacement gradient from the top (subsidence) to the bottom (accumulation). Vertical velocities are calculated from the unwrapped phase values and are in good agreement with ground-based measurements. The results demonstrate the potential of L-band ALOS/PALSAR imagery for the monitoring of active landslides characterized by complex kinematic patterns and by important changes in the soil surface backscattering in time.     

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.     

Investigating a reservoir bank slope displacement history with multi-frequency satellite SAR data

Slope instability arisen along with dam construction is a common problem of great concern in reservoir areas. Thus, displacement monitoring of active slopes is of great importance for the safety of dam operation. The unstable Guobu slope is located only about 1.5 km away from Laxiwa hydropower station in upstream Yellow River. In this study, Synthetic Aperture Radar (SAR) datasets acquired by C-band Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR), L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2), and X-band TerraSAR-X covering different evolution stages of Guobu slope were collected to investigate the displacement history so as to facilitate understanding of its deformation and failure mechanisms. The displacements occurred during the past decade were quantitatively identified for the first time by SAR pixel offset tracking analyses. The results show that before the reservoir impoundment, the maximum accumulative displacements on the slope were more than 7 m from 2003 to 2008, while the post-impoundment displacements also exceeded 7 m in just 1 year from September 2009 to September 2010. Furthermore, this slope is still in active deformation up to now. Nevertheless, the displacement rates seem decreased recently according to the interferometric results of TerraSAR-X data pairs from September 2015 to March 2016.     

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.     

Land subsidence and earth fissures in south-central and southern Arizona,USA

Land subsidence due to groundwater overdraft has been an ongoing problem in south-central and southern Arizona (USA) since the 1940s. The first earth fissure attributed to excessive groundwater withdrawal was discovered in the early 1950s near Picacho. In some areas of the state, groundwater-level declines of more than 150 m have resulted in extensive land subsidence and earth fissuring. Land subsidence in excess of 5.7 m has been documented in both western metropolitan Phoenix and Eloy. The Arizona Department of Water Resources (ADWR) has been monitoring land subsidence since 2002 using interferometric synthetic aperture radar (InSAR) and since 1998 using a global navigation satellite system (GNSS). The ADWR InSAR program has identified more than 25 individual land subsidence features that cover an area of more than 7,300 km². Using InSAR data in conjunction with groundwater-level datasets, ADWR is able to monitor land subsidence areas as well as identify areas that may require additional monitoring. One area of particular concern is the Willcox groundwater basin in southeastern Arizona, which is the focus of this paper. The area is experiencing rapid groundwater declines, as much as 32.1 m during 2005–2014 (the largest land subsidence rate in Arizona State—up to 12 cm/year), and a large number of earth fissures. The declining groundwater levels in Arizona are a challenge for both future groundwater availability and mitigating land subsidence associated with these declines. ADWR’s InSAR program will continue to be a critical tool for monitoring land subsidence due to excessive groundwater withdrawal.     

The deformation analysis of Wenjiagou giant landslide by the distributed scatterer interferometry technique

After the deadly Ms 8.0 Wenchuan earthquake, the Wenjiagou landslide produced steep topography, a narrow gully and abundant loose sediments; these factors have contributed to the high debris flow risk in the Wenjiagou area during subsequent rainy seasons. At least five debris flows have occurred in the Wenjiagou area between September 24, 2008, and September 18, 2010, which resulted in seven casualties and an economic loss of approximately 446 million RMB. To reduce the risk of debris flows and landslides, the Wenjiagou Valley Debris Flow Control Project (WVDFCP), which cost over 2 billion RMB, was carried out and completed in 2011. The control measures of the project effectively reduced the scale and damage of the following debris flows. In this paper, the recent deformation of the giant landslide and its effect on the WVDFCP are evaluated by applying a time-series interferometric synthetic aperture radar (InSAR) technique based on distributed scatterers (DSs) to the Radardat-2 SAR data collected from June 2014 to September 2015. In addition, the experimental results show that most areas of the landslide are stable, with an average deformation rate of less than 5.0 mm/year. The results demonstrate that the control measures of the WVDFCP not only reduced the damage caused by the later debris flows but also contributed to the consolidation of the loose sediments in the Wenjiagou landslide area. The time-series InSAR technique based on the DSs of high-resolution SAR images is an important tool for deformation monitoring of earthquake-induced landslides.     

川藏交通廊道典型工点InSAR监测及几何畸变精细判识

为了探明川藏交通廊道典型工点高陡岸坡的稳定性,以及明确SAR(synthetic aperture radar)几何畸变对InSAR(interferometric synthetic aperture radar)形变结果的影响,利用时序InSAR技术开展川藏交通廊道典型工点高陡岸坡形变监测,并提出了一种可识别所有几何畸变类型的SAR几何畸变精细判识方法.成功识别出9处不稳定的高陡岸坡,获取了各轨道SAR几何畸变精细识别结果.在精细划分几何畸变的前提下,通过进一步地将几何畸变与形变结果联合分析,首次揭示了各类几何畸变(包括透视收缩、主被动叠掩、主被动阴影)对InSAR形变结果的影响效果.研究明确了InSAR技术在川藏交通廊道高陡山区的应用能力、适用范围以及几何畸变区结果可靠性的判识,可为后续高陡岸坡形变监测、精确解译等研究提供重要参考.      

Survey and monitoring of landslide displacements by means of L-band satellite SAR interferometry

This paper illustrates the capabilities of L-band satellite SAR interferometry for the investigation of landslide displacements. SAR data acquired by the L-band JERS satellite over the Italian and Swiss Alps have been analyzed together with C-band ERS-1/2 SAR data and in situ information. The use of L-band SAR data with a wavelength larger than the usual C-band, generally considered for ground motion measurements, reduces some of the limitations of differential SAR interferometry, in particular, signal decorrelation induced by vegetation cover and rapid displacements. The sites of the Alta Val Badia region in South Tyrol (Italy), Ruinon in Lombardia (Italy), Saas Grund in Valais (Switzerland) and Campo Vallemaggia in Ticino (Switzerland), representing a comprehensive set of different mass wasting phenomena in various environments, are considered. The landslides in the Alta Val Badia region are good examples for presenting the improved performance of L-band in comparison to C-band for vegetated areas, in particular concerning open forest. The landslides of Ruinon, Saas Grund, and Campo Vallemaggia demonstrate the strength of L-band in observing moderately fast displacements in comparison to C-band. This work, performed with historical SAR data from a satellite which operated until 1998, demonstrates the capabilities of future planned L-band SAR missions, like ALOS and TerraSAR-L, for landslide studies.     

DInSAR analysis of ALOS PALSAR images for the assessment of very slow landslides: the Tena Valley case study

In this work we analyse the performance of advanced land observing satellite (ALOS) phased array type L-band syntetic aperture radar (PALSAR) images for mapping and monitoring of very slow landslides using conventional differential interferometry in the Tena Valley (Central Pyrenees, Spain). These results are compared with those retrieved in previous works where multi-band advanced differential interferometric synthetic aperture radar (DInSAR) analysis was performed for the same area using PSI techniques. The study area is largely underlain by slates (ca. 80 %) where large deep-seated very slow earth flows are dominant. The results reveal that DInSAR analysis is able to measure displacements of landslides with a greater spatial coverage than PSI analysis, but for a lower amount of them (nine against 51). Overall, the combination of the DInSAR and multi-band PSI analysis permitted to map and monitor 68 % of the landslides in Tena Valley. From this amount, 63 landslides are considered as active. The main advantage of DInSAR with respect to PSI analysis is the capability to detect faster movements (up to 145 cm?year^?1) derived from the 46 days interferograms. That is the case of Sextas and La Selva landslides where an acceleration of the moving mass was measured after intense rainfall periods producing major damages to linear infrastructures. The combination of measured displacement from ALOS interferograms, with the observed damages on the A-136 road, was useful to assess the potential damage that could cause these slow movements. In general, it is demonstrated that even though PSI analysis provides a better performance in terms of landslide mapping, L-band DInSAR analysis provides an added value for landslide hazard assessment through radar remote sensing. For this reason it is necessary to encourage the launch of new satellite missions similar to ALOS PALSAR that could operate with shorter revisiting time periods.     

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.     

Landslide activity as a geoindicator in Italy: significance and new perspectives from remote sensing

Landslide activity responds to rapid environmental changes and represents a relevant geoindicator in mountainous or hilly areas. This paper discusses the socio-economic relevance of landslide hazard in Italy and the problems encountered in establishing relationships between landslide frequency, climate and vegetation changes at different time scales. Landslides blocking a river channel have been carefully taken into account because they are usually characterized by high intensities (with regard to the involved masses and movement velocities) and their occurrences are often datable via radiocarbon dating. This is due to the recovery of organic matter in the landslide dammed lakes. For these reasons they can be considered important geoindicators in the wider category of slope failures. The marked effects of the anthropogenic activity on slope instability processes in the last 50 years are discussed with reference to two case histories: the Chianti hills in Tuscany and the Cinque Terre National Park in Liguria. Finally, two novel techniques of remote sensing are proposed as tools for a systematic monitoring of slope instability at different time and spatial scales. Both techniques are based on the interferometric synthetic aperture radar (SAR) technology and differ on the type of platform (satellite and ground-based) used to acquire data.     

基于SBAS-InSAR技术的川藏铁路澜沧江段滑坡隐患早期识别

早期识别是实现地质灾害防灾减灾的有效途径之一,然而复杂地形区滑坡的早期识别一直是个难题,尤其是位于高山峡谷区的滑坡隐患点。为了全面准确地获取川藏铁路澜沧江段的滑坡隐患,采用SBAS-InSAR技术,通过Sentinel-1(升轨)和RADARSAT-2(降轨)数据结合互补的方式,对川藏铁路澜沧江段进行滑坡隐患早期识别。解译结果显示2018年8月至2020年2月研究区LOS向的形变速率分别为-58~21 mm/a(升轨)和-42~16 mm/a(降轨),转换后的斜坡向最大平均速率达到-128 mm/a。基于升降轨数据的斜坡向形变结果,识别出川藏铁路澜沧江段的113处滑坡隐患点,其中存在4处滑坡隐患密集区以及13处典型滑坡隐患点,进一步分析了两处重点滑坡隐患的形变特征和滑移机制。本次研究结果对于川藏铁路线路选定以及澜沧江大桥上、下游的防灾减灾具有一定指导作用,不同轨道数据结合互补的方式为川藏铁路沿线的高山峡谷地区的滑坡隐患早期识别提供参考。