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.     

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.      

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。      

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.     

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.     

基于MSBAS技术的金沙江上游色拉滑坡形变分析

金沙江缝合带是滑坡灾害的高发区,且具有较大的堵江威胁。以堵江风险较高的色拉滑坡为研究对象,选取高时间分辨率的升降轨Sentinel-1A/B数据,利用MSBAS InSAR技术对该滑坡展开地表形变监测研究。文章在利用不同轨道的Sentinel-1A/B获取色拉滑坡2018—2020年间的二维动态形变时间序列的基础上,分析了典型特征点形变时间序列特征。结果表明,在2018年1月—2020年4月色拉滑坡东西向累积形变最高达到165 mm,垂直向累积形变达?102 mm,滑坡体形变加速的时间点被成功地捕获。最后,分析了该滑坡的形变趋势,通过现场调查结果验证了所获得滑坡监测结果的准确性。     

兴仁县罗马山滑坡体形变监测及成因分析

InSAR技术是当前从卫星雷达遥感获取的对地观测数据中提取地形信息最主要的技术手段。本文以贵州省普安县罗马山为研究区,收集了2017年4月16日至2018年8月5日共10景ALOS PALSAR2数据,生成9个干涉对,以形变时间序列的方式对研究区中的滑坡体进行形变监测分析。同时,收集兴仁县2017年4月至2018年8月降雨量信息,通过与形变时间序列的对比分析,可发现降雨量与形变的高度相关性,这对滑坡灾害的预防具有重要意义。     

西藏樟木口岸震后滑坡灾害变形InSAR监测分析

位于中国和尼泊尔边境的西藏樟木口岸是国家一类陆路通商口岸,也是西藏最大的边贸中心口岸。2015年尼泊尔大地震之后,西藏樟木口岸因多次发生滑坡灾害,而导致口岸关闭。为了调查樟木口岸区域滑坡灾害的分布和变形情况及更好的服务于区域减灾防灾,利用InSAR技术对覆盖该区域的Sentinel-1A和ALOS-2两种卫星影像数据进行了处理,并通过分析视线向年均形变速率图,圈定了17处疑似滑坡,并对其中的5处典型滑坡进行时间序列形变特征分析,监测识别出的滑坡基本沿318国道所在一侧的波曲河左岸分布。InSAR调查结果表明受地震影响樟木地区的滑坡多分布在沿波曲河左岸的陡峭山体上,中尼公路迪斯岗至友谊桥段的古滑坡出现了局部复活的现象,同时樟木镇居民所在的城区也发育有扎美拉山危岩体崩塌滑坡灾害。      

多元时间序列分析的滑坡演化阶段划分

滑坡的时间-位移曲线一般具有3个阶段特征,即初始变形阶段、等速变形阶段和加速变形阶段,不同演化阶段加速度具有不同的变化特点.目前往往是依据对加速度曲线特征的分析来人为划分演化阶段,缺少相应的理论支持和定量计算.针对上述问题,选取月降雨量、月库水位高程变化量对滑坡的累计位移建立多因素的时间序列预测模型.然后利用Chow分割点检验理论,以所建模型中F和LR统计量最大值点作为分割点对滑坡演化阶段进行划分.以新滩滑坡和三峡库区白水河滑坡为例,利用累计位移、降雨及库水位变化数据进行计算验证.结果表明,对多元时间序列模型进行Chow分割点检验可对滑坡的演化阶段进行准确划分,为滑坡的临滑预警预报提供重要判据.      

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.     

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。     

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.      

蔚县矿区地面沉陷InSAR多维形变监测

河北蔚县是我国华北地区最大的地下采煤区之一,该地区长期存在采矿塌陷灾害,不仅威胁采矿安全,而且严重破坏当地生态环境。本文基于合成孔径雷达干涉（InSAR）这一新型空间对地观测技术,采用61景Sentinel-1A/B干涉宽幅（Interferometric Wide swath,IW）模式数据进行矿区形变观测,获取整个矿区在2017—2018年间的地表形变空间分布特征,并对矿区地表的沉降量级及面积进行详细的统计分析。此外,采用融合多轨道SAR数据的多维形变时序估计方法,对西细庄矿数据进行东西向和垂向的二维形变分解,获取该矿的二维形变时间序列。结果表明:除南留庄井田外,其余三大井田在监测期间均存在不同程度的地面沉陷灾害;整个矿区年沉陷速率超过-10 cm/a的区域达到了2.16 km2;受成像几何影响,不同轨道数据获取的形变结果存在一定差异;西细庄矿以垂向形变为主,伴随明显的东西向水平形变。研究结果为蔚县矿区地面沉陷监测与煤矿安全开采提供数据参考。      

基于光学遥感与InSAR技术的潜在滑坡与老滑坡综合识别

我国滇西北区域地质灾害频发,主要灾害类型为滑坡,对该区域进行滑坡类地质灾害隐患识别是有效的防灾减灾措施,传统的地质灾害隐患识别手段较为单一,且依赖大量的人力,调查效率较低。利用WordView2、Sentinel-1A、ALOS-2几种遥感卫星数据,进行Stacking-InSAR等技术的处理,得到多种光学卫星影像和InSAR处理的地表形变图,建立滇西北区域潜在滑坡与老滑坡的光学解译标志和InSAR识别标志,并进行多次目视解译和人工交互式解译。依据解译、识别成果,总结识别方法并进行野外调查验证。共识别潜在滑坡与老滑坡696处,为今后滇西北区域地质灾害调查与评价提供新的调查思路和技术参考。     

Testing the potential of Sentinel-1A TOPS interferometry for the detection and monitoring of landslides at local scale (Veneto Region,Italy)

The recent Sentinel-1 mission, started by the European Space Agency in April 2014, provides the scientific community with new capabilities for the monitoring of the Earth surface. In particular, the Terrain Observation by Progressive Scans imaging technique used in the Interferometric Wide swath acquisition mode permits to acquire data over very wide areas (250 km of swath extension) at 20-m spatial resolution, with 12-day revisit time, making it suitable for ground displacement monitoring applications. With more than 1 year of synthetic aperture radar images available, it is now possible to carry out monitoring activities of slow moving phenomena such as landslides at both regional and local scales. In this work, the potential of Sentinel-1A for the monitoring of shallow (from 2 to 6 m of depth) landslides occurring in the North-Eastern Italian Pre-Alps was tested. Two stacks of Sentinel-1A scenes acquired in both ascending and descending orbits were processed using the Permanent Scatterer Interferometry (PSI) technique. The results, analysed in terms of PS density and quality, were compared with the ERS-1/2 and ENVISAT PSI database available from the Italian National Cartographic Portal to assess the capabilities of Sentinel-1A in detecting and monitoring landslides in respect to the previous satellite missions. The results of this work show the great potential of Sentinel-1A in the continuous monitoring of landslide-prone territories even at local scale. The achievable results can provide information that is useful to delineate the spatial and temporal evolution of landslides and precisely assess their rates of deformation.     

基于InSAR技术的川西高山峡谷区地质灾害早期识别研究——以小金川河流域为例

采用短基线集时序干涉测量(small baseline subset InSAR,SBAS-InSAR)技术,利用多时相合成孔径雷达数据,对川西高山峡谷区开展地表多时相、长时序形变监测与地质灾害隐患早期识别研究。介绍了时序InSAR方法原理,梳理了数据处理流程,分析了小金川河流域雷达可视性,利用2018-11—2019-12共26期的Sentinel-1A历史存档数据开展了流域内地表形变监测,结果表明: 流域内雷达视线方向的年平均形变速率为-51.12~75.28 mm/a; 依据形变异常分布规律,共判译出4处形变异常区与11处潜在地质灾害隐患点,其中6处隐患点为已知地质灾害点,其余5处隐患点尚不为人知。以隐患点P1(阿娘寨滑坡)为典型案例,开展了长时序监测分析与验证,评估利用InSAR技术开展地质灾害隐患早期识别的可靠性,证明了SBAS-InSAR技术在地质灾害早期识别中的优势及有效性,其技术成果在川西高山峡谷区具有大范围推广应用的潜力。     

Ground subsidence in Semarang-Indonesia investigated by ALOS–PALSAR satellite SAR interferometry

The focus of this study is investigation of land subsidence in Semarang city Indonesia with the use of Interferometry Synthetic Aperture Radar (InSAR) of ALOS–PALSAR satellite. We processed 22 ascending SAR images during January 2007 to January 2009 plus two descending SAR images acquired on 6 June 2006 and 17 June 2007. The time series analysis of interferometry was performed by using 12 pairs of interferogram relative to 21 January 2007 and 8 pairs of interferogram relative 24 January 2008. The topographic phase contribution was removed using the 3-arcsec (90 m) Shuttle Radar Topography Mission (SRTM), Digital Elevation Model (DEM). We performed precision baseline estimation to vanish the fringes from baseline effect between master and slave data. In order to investigate the contribution of horizontal movement in our analysis, we constructed two interferograms of ascending orbit and descending orbit. The time series results exhibited that the area is subsiding continuously without a significant seasonal effect during January 2007 to January 2009. The land subsidence observed from InSAR data is approximately up to 8 cm/year. Three cross sections on image displacement show the extreme land subsidence occurred especially along the coastal area and lowland area where this area is considered as industrial with high-density settlements, consuming a lot of groundwater, and land is changed from agriculture and cultivation purposes to industrial estates and house. Our result also shows a consistency with historical pattern of subsidence measured by leveling data. The results highlight the potential use of InSAR measurements to provide better constraints for land subsidence in Semarang city Indonesia.     

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。     

联合升降轨Sentinel-1A数据监测桃坪乡古滑坡沿坡向的形变速度场

单一平台或轨道的InSAR(Interferometric Synthetic Aperture Radar,InSAR)技术通常只能获取到滑坡体沿雷达卫星视线(LOS)方向的一维形变信息,无法直接获取到滑坡体沿坡向的形变信息,使得InSAR技术无法充分满足滑坡监测的工程需求。针对这一问题,本文提出联合升降轨Sentinel-1A数据提取滑坡沿坡向形变速度场的模型算法,其基本方法是:首先利用InSAR技术分别获取升轨和降轨沿LOS方向的形变速度场,然后根据坡向和坡度建立滑坡的滑动面坐标系,基于LOS方向与滑动面的几何关系对升降轨对应的LOS向形变速度值进行建模,在滑动面上不存在法线方向形变的合理假设下通过解算独立方程组获得滑坡体沿坡向的形变速度场和沿垂直坡向的形变速度场。本文选取四川省理县桃坪乡古滑坡作为研究对象,并通过模拟实验对模型的解算精度进行验证,结果表明:相比于LOS向形变速度场,重建的沿坡向和沿垂直坡向形变速度场更加清晰地揭露了滑坡体的主要位移模式和危险性较高的坡体区域。同时,模拟实验结果表明,模型算法的解算误差与噪声水平大致呈线性增加的关系,当噪声水平达到10 mm·a-1时,沿坡向形变速度场的解算误差为14.1 mm·a-1,沿垂直坡向形变速度场的解算误差为11.9 mm·a-1,证明了模型算法以及结果的可靠性。