基于SBAS/PS-InSAR技术的滑坡遥感监测对比研究

以2015~2019年12景ALOS-2 PALSAR2影像和2018~2019年38景Sentinel-1A影像为主要数据源,利用PS-InSAR和SBAS-InSAR技术提取西藏江达县波罗乡白格滑坡点的形变信息,并对处理结果进行交叉验证。研究得到以下结论：1）PS-InSAR技术条件下,ALOS-2数据和Sentinel-1A数据的平均形变速率范围为-68.9~37.9 mm/a和-64.5~24.2 mm/a;SBAS-InSAR技术条件下,ALOS-2数据和Sentinel-1A数据的平均形变速率范围为-84.2~-40.0 mm/a和-84.0~-13.0 mm/a。2）对2种数据结果中提取的4个特征点进行时序分析和定量分析显示,2种InSAR技术结果变化趋势较为一致,验证了两者在滑坡监测中的可靠性和准确性。     

基于升降轨Sentinel-1A SBAS InSAR的西南山区滑坡隐患早期识别研究

以贵州省水城县为研究区,使用SBAS InSAR分别对2018-07~2019-07鸡场镇滑坡发生前31期升轨和30期降轨Sentinel-1A数据进行处理,提取地表形变场。结果表明：1）鸡场镇滑坡发生前SBAS InSAR形变场并未出现明显形变,已超出12 d重访周期SAR的形变监测能力;2）研究区存在5个明显形变区,推断与斜坡失稳、地下/露天采矿和矿物加工的抽排水有关;3）升降轨数据的SBAS InSAR形变场相互补充、验证,可显著提升卫星雷达对山区滑坡隐患早期识别和形变监测能力。研究方法可为贵州省以及中国西南山区滑坡隐患调查与早期识别提供技术参考。     

滑坡灾害预测预报信息共享平台

 滑坡是最常见的一种地质灾害,其主要诱因是降雨。滑坡灾害多发生在雨量充沛地域或洪水季节。南京市受自然环境和地质环境的影响,滑坡是其最主要的地质灾害类型之一,为了有效地预测滑坡的发生情况并最大限度地减少滑坡灾害为南京带来的损失,本文在已有的南京市地质灾害易发区等研究的成果上,结合南京市历史滑坡数据、气象资料和地质灾害预测数学模型构建了南京市滑坡灾害预测方法并确定了南京市滑坡灾害预测预报技术流程。在该预测方法和技术流程的基础上,本文同时应用了数据库技术、ArcGIS Server技术、AJAX远程调用技术、网页局部刷新技术和地图缓存技术等,融合地理信息系统功能与滑坡灾害预测预报业务功能,开发了南京市滑坡灾害预测预报信息共享平台。该平台可以对滑坡灾害基础数据和实时气象数据动态、科学地管理,结合南京市实时降雨数据可实现滑坡灾害预测预报并将灾害信息实时在线发布,同时提供对滑坡灾害信息的查询、检索、统计分析等功能,最终通过该信息共享平台,为南京市滑坡灾害的防灾减灾提供决策支持,为其他需要建立滑坡灾害预测信息共享平台的城市提供参考。     

基于Sentinel-1A的南昌市时间序列InSAR地面沉降监测

本文基于2016-01~2018-07的Sentinel-1A数据,采用PS-InSAR和SBAS-InSAR时序处理方法获取南昌市主城区地面形变信息,对比2种监测结果,分析产生不均匀地面形变的原因。结果表明,2种时序技术的监测结果相关性较高,南昌市主城区的形变趋势为西北抬升、东南下沉。形变区空间分布存在梅岭抬升区、南昌西火车站沉降区、赣江东岸沉降区、邓家埠沉降区和南钢沉降区,主要受地质构造、含水层介质、地下水开采和城市建设等因素影响。     

地基雷达干涉测量技术在滑坡灾后稳定性评估中的应用

针对2014-09-01大树场镇大面积山体滑坡灾后稳定性,从IBIS-L地基雷达形变测量原理和关键技术(步进频率连续波和合成孔径雷达)入手,给出地基InSAR数据处理流程,获得了滑坡灾后高精度、高时空分辨率的形变演化特征,测量精度达到亚mm级。地基InSAR结果表明,滑坡体滑动幅度较大的区域位于滑坡体左侧中上部(120mm)和右侧中上部(75mm)。滑动主要由堆积松散土在裂隙水、雨水等作用下造成,产生较大次生灾害的可能性较小。     

四川汶川“5.12”地震滑坡堰塞湖遥感监测分析

运用可见光、雷达和航片等不同空间分辨率的多源遥感数据,对四川汶川"5.12"地震灾区因地震诱发形成的大型堰塞湖进行了遥感监测,对堰塞湖发生的地点、数量以及空间分布规律进行了讨论。重点对唐家山堰塞湖进行了动态监测,提取了其堰塞湖回水长度、水面面积与水量等信息,并对这一结果进行了详细分析,为地震滑坡堰塞湖科学处置与减灾决策提供了科学依据。     

风振影响下乔木坡地暴雨型浅层滑坡演化机制

强对流或台风等极端天气下乔木坡地发生浅层滑坡灾害往往是暴雨和强风共同作用的结果。以皖南山区一处暴雨型浅层滑坡——畈章组滑坡为例, 通过现场调查和气象资料的分析表明, 除暴雨外风荷载也有可能促进滑坡的启动。为揭示该滑坡启动与破坏后这一完整运动过程的演化机制, 首先基于无限斜坡模型分析了实际降雨条件下的滑坡稳定性, 然后对取自于滑坡体内乔木根系周围和滑动面附近的两种土样利用DPRI型环剪仪, 分别开展了不排水循环剪切试验和自然排水残余剪切试验。结果表明: ①降雨入渗引起滑动面孔隙水压力的上升, 并导致稳定性的降低是畈章组滑坡启动的直接原因; ②乔木根系周围的饱和土在风振作用产生的动剪切荷载下易形成高的超孔隙水压力, 并导致浅表层的局部失稳滑动, 增加了畈章组滑坡整体破坏的可能性; ③滑动面土体的残余强度具有强烈的"正速率效应", 从而控制了畈章组滑坡启动后不会表现出高速远程的运动特征, 与现场调查结论一致。研究结果可以为暴雨协同风振作用下富乔木坡地浅层滑坡的预警预报研究提供参考。      

兴仁“6·10”彭家洞高速滑坡运动特征与形成机理

2021年6月10日20时30分左右, 贵州省兴仁彭家洞发生高速滑坡, 滑坡体高速运动沿途铲刮坡面崩塌堆积体, 造成3人遇难, 18栋房屋损毁。通过对滑坡发生前后影像资料遥感解译、灾害发生现场详细的地质调查及室内综合分析等技术手段, 对彭家洞滑坡的特征进行了详细描述, 阐明了滑坡发生的运动特征与形成机理。研究表明: 斜坡地形"上陡-中缓-下陡"与岩土结构"上硬下软"是滑坡形成的内在因素, 人类工程活动、强降雨的饱水加载和下渗软化作用是滑坡形成的外在因素; 滑坡平面形态呈折线形, 根据运动特征和堆积结构将滑坡分为滑源区(Ⅰ)、铲刮-流通区(Ⅱ)、铲刮堆积区(Ⅲ)3个区; 滑坡是由危岩带形成、滑坡孕育及斜坡失稳3个阶段孕育形成的挤压-推移式高速滑坡。研究结果对贵州类似的斜坡地带及岩土结构区域开展防灾减灾工作具有较强的指导作用。      

滑坡的危害和分布

<正>滑坡(土体和岩体滑动、也包括泥石流和崩塌等)是丘陵和山区经常发生的地质灾害。在我国的大多数山区几乎每年都会发生大大小小的滑坡,在有些地方一年可以发生几次,甚至几十次。滑坡灾害的特点是:发生     

四川省滑坡灾害气象预警模型建立与验证

四川省滑坡灾害严重,特别是2008年之后,灾情显著加剧,如何预防滑坡灾害是保护人民生命财产安全的有效途径。滑坡灾害的预警模型研究是滑坡灾害预防领域的核心课题。本文对四川省滑坡灾害危险性进行了评价,并开展了滑坡灾害气象风险预警模型研究。①以确定性系数的方法量化坡度、地形起伏度、水文地质岩性、植被覆盖度、地震烈度和年均降雨量因子,建立逻辑回归模型,定量地进行四川省滑坡灾害危险性区划,并对结果进行验证。结果表明,四川省滑坡灾害高危险性区域成“Y”字型分布,此外川中、川东北地区滑坡灾害危险性也非常高,这与四川省滑坡灾害的空间分布情况相符。②在前期滑坡灾害与降雨量统计分析、滑坡灾害危险性评价的基础上,以滑坡灾害危险性评价为静态因子,日降雨量数据为动态因子,通过逻辑回归模型的结果,确定以当日降雨量概率化值、滑坡灾害危险性值、前一日降雨概率化值、前两日降雨概率化值、前三日降雨概率化值为临灾模型影响因子,各因子对预警结果影响程度按上述顺序递减,建立了地质-气象耦合的临灾气象预警模型。通过检验区数据对模型的检验表明,该预警模型能成功预警80%以上的滑坡灾害;通过滑坡灾害群发个例检验发现,该预警模型与四川省现用模型相比,预警区域明显减小,空报率和漏报率显著降低。     

Empirical-statistical models based on remote sensing for estimating the volume of landslides induced by the Wenchuan earthquake

The Wenchuan Ms 8.0 earthquake on May 12, 2008 induced a huge number of landslides. The distribution and volume of the landslides are very important for assessing risks and understanding the landslide - debris flow - barrier lake - bursts flood disaster chain. The number and the area of landslides in a wide region can be easily obtained by remote sensing technique, while the volume is relatively difficult to obtain because it requires some detailed geometric information of slope failure surface and sub-surface. Different empirical models for estimating landslide volume were discussed based on the data of 107 landslides in the earthquake-stricken area. The volume data of these landslides were collected by field survey. Their areas were obtained by interpreting remote sensing images while their apparent friction coefficients and height were extracted from the images unifying DEM (digital elevation model). By analyzing the relationships between the volume and the area, apparent friction coefficients, and the height, two models were established, one for the adaptation of a magnitude scale landslide events in a wide range of region, another for the adaptation in a small scope. The correlation coefficients (R2) are 0.7977 and 0.8913, respectively. The results estimated by the two models agree well with the measurement data.     

基于物理模型试验的多层滑带滑坡变形演化特征

滑坡变形演化特征一直是滑坡灾害预测与防治领域急需解决的关键问题, 但对于多层滑带滑坡的变形演化特征却少有研究。以物理模型试验为手段建立了三层滑带滑坡物理试验模型, 完成了多层滑带滑坡变形演化全过程的模拟。基于PIV技术获取坡表位移数据, 通过柔性测斜仪监测滑坡深部位移, 同时布设土压力盒获取滑坡内部土压力的变化情况, 实现了多层滑带滑坡演化过程多参量数据分析。试验结果表明, 多层滑带滑坡破坏过程可分为初始、等速、加速和破坏4个阶段。不同破坏阶段滑坡的主要变形区域不同, 下层滑体受到上层滑体牵引作用, 在重力和推力作用下滑坡变形逐渐向浅层发展。变形过程中滑坡应力逐渐向滑带集中, 滑坡推力沿埋深方向呈多级梯形分布。加速变形阶段滑带处应力迅速增大, 滑坡体内产生多层应力集中带, 滑带位置推力变化与滑坡位移显著相关。      

Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture(Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle(UAV), and a digital elevation model(DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include Quick Bird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km2, and the volume of the landslide was 7.70 ± 1.46 million m3. The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.     

基于模型试验的动水驱动型顺层岩质滑坡启滑机制初探

动水驱动型顺层岩质滑坡数量多、灾害频发、危害大, 是滑坡地质灾害领域的研究重点, 但目前对于滑坡启滑机制的认识仍不充分, 滑坡的准确预报还面临巨大挑战。鉴于此, 以含软弱夹层的中倾角顺层岩质滑坡为研究对象, 通过构建理想的单层滑带滑坡物理模型, 开展了一系列动水作用下的滑坡模型试验研究。结果表明, 动水作用下顺层岩质滑坡从开始变形至失稳滑动需经历初始变形、缓慢变形、加速变形和失稳破坏4个阶段, 而各个阶段的演化特征与滑面粗糙度和倾角密切相关。滑面倾角越大或粗糙度越小, 滑坡体从开始变形至失稳滑动所需的时间则越短; 相应地, 坡体加速变形阶段越不明显, 滑坡破坏的突发性越强。滑带内的渗流冲蚀作用会使滑带土中的骨料流失, 导致其抗剪强度降低, 进而引发坡体滑动。与此同时, 上覆坡体的压剪作用以及变形演化过程亦将反过来影响冲蚀强度。基于滑带土黏聚力随水力梯度和冲蚀时间的变化关系, 提出了渗流驱动下滑带土黏聚力演化模型, 可较好地描述滑带土黏聚力的退化过程。滑面粗糙度的存在不仅显著影响了滑带的冲蚀劣化规律, 还改变了滑带不同区域的破坏模式。此外, 通过考虑滑面粗糙度对滑带不同区域破坏模式的影响, 开展了动水多效应关联分析, 建立了滑坡地质体力学分析模型, 实现了动水作用下顺层岩质滑坡动态稳定性的有效评估。本研究成果可为实际动水驱动型顺层岩质滑坡的预测和防治提供理论参考。      

基于滑面分区段力学模型的高速滑坡运动过程能量转化研究

高速滑坡具有运动速度快、波及范围广的灾害特征, 因此对滑坡启动、加速和静止整个运动过程进行研究很有必要。基于滑面力学特性将滑面分为弹性介质区和应变弱化区, 构建了高速滑坡二维力学模型, 提出了滑坡启动动能计算公式和滑坡运动过程的能量计算公式; 以千将坪滑坡为例, 采用启动动能计算公式得出滑坡的启动速度为2.35 m/s; 依据滑面形态将其运动轨迹划分为快速加速、平稳加速、平稳减速、急剧减速4个阶段, 进行运动过程分析, 得出滑坡最大速度为16.8 m/s, 以滑坡前缘高程所在平面为势能基准面, 分析不同能量与总能量占比的变化情况, 在滑坡的4个运动阶段中, 动能占比分别为9.1%, 25.6%, 15.1%, 0%;摩擦损耗能量占比分别为: 5.5%, 58.8%, 81.7%, 95.5%;势能占比分别为: 85.2%, 14.2%, 0%, 0%;其他阻力能耗占比分别为: 0.2%, 1.4%, 3.2%, 4.5%。研究结论对高速滑坡致灾机制和风险分析具有重要意义。      

黄土区滑坡研究中地形因子的选取与适宜性分析

黄土高原是中国生态较为脆弱的地区,也是滑坡发育的地层之一。黄土滑坡发育是孕灾环境、致灾因子和承灾体等多种因素联合作用的结果,其中作为重要孕灾环境因素的地形因子的选取是黄土滑坡风险研究的基础。本文选取黄土滑坡灾害多发的甘谷县作为研究区,综合利用敏感性指数、确定性系数和相关系数方法进行地形因子在滑坡灾害研究中的适宜性分析,得出以下结论：基于确定性系数法、敏感性分析模型和相关系数法,最终筛选出适宜于本区域滑坡灾害评价的地形因子为：坡度、坡度变率、坡形和地表粗糙度;确定性系数法、敏感性分析模型都基于分析单一因子与滑坡之间的关系进行致灾因子选取,忽视地形因子之间的相关性。实验结果表明,研究区稳定性较差的区域与已发生滑坡灾害分布数量具有较好的对应关系,并深入分析了滑坡与地形因子分级范围的关系,发现地形因子分级范围对地质灾害风险研究具有重要的影响,是导致部分区域的差异性主要原因之一。实地调查发现,河网切割密度及人类工程活动也对研究区危险性具有重要的控制作用,是重要的地形因素。     

Evidence of the formation of landslide-dammed lakes in the Zagros Mountains range,Iran

Alternation of high and low resistance sedimentary beds,active tectonics,large rivers,and slope erosion in valleys consequently resulted in landslide in dammed lakes within the Zagros range.This study presents the results in the analysis of geological and topographic data,satellite imageries,morphotectonics and hydrodynamics of drainage networks about the landslide dammed lakes.There are four landslides in central Zagros(Zagros FoldThrust Belt,ZFTB)which have formed five dammed lakes named,Seymareh,Jaidar,Shur,Shimbar,and Godar.According to the results,damming landslides occurred in the active-tectonic regions on the slopes of anticlines and in valleys with undercutting effects of rivers on their slopes consisting of alternations of loose and resistant beds.The studied landslide dams in narrow valleys are formed as a result of blocking river by sliding debris slopes and rock slides.This study also indicates the formation of Jaidar and Godar in one stage and the presence of Lake Terrace sequence in Seymareh,Shur and Shimbar lakes.The observed sequences of terrace formation in these lakes are caused by four Seymareh Landslides followed by the three-stage excavation of Shur andShimbar lakes.     

Landslide and basin self-organized criticality in the Lushan Hot Spring area

Defining a basin under a critical state(or a self-organized criticality) that has the potential to initiate landslides,debris flows,and subsequent sediment disasters,is a key issue for disaster prevention.The Lushan Hot Spring area in Nantou County,Taiwan,suffered serious sediment disasters after typhoons Sinlaku and Jangmi in 2008,and following Typhoon Morakot in 2009.The basin’s internal slope instability after the typhoons brought rain was examined using the landslide frequency-area distribution.The critical state indices attributed to landslide frequency-area distribution are discussed and the marginally unstable characteristics of the study area indicated.The landslides were interpreted from Spot 5 images before and after disastrous events.The results of the analysis show that the power-law landslide frequency-area curves in the basin for different rainfall-induced events tend to coincide with a single line.The temporal trend of the rainfallinduced landslide frequency-area distribution shows 1/f noise and scale invariance.A trend exists for landslide frequency-area distribution in log-log space for larger landslides controlled by the historical maximum accumulated rainfall brought by typhoons.The unstable state of the basin,including landslides,breached dams,and debris flows,are parts of the basin’s self-organizing processes.The critical state of landslide frequency-area distribution could be estimated by a critical exponent of 1.0.The distribution could be used for future estimation of the potential landslide magnitude for disaster mitigation and to identify the current state of a basin for management.