位移监测在滑坡时空运动研究中的应用

滑坡时空运动特征是滑坡地质体在内因和外因共同作用下，自一种状态向另一种状态转化的地质过程。滑坡位移监测是研究滑坡变形影响因素、动态规律及预测预报的主要途径，特别是滑坡深部位移监测，又为研究滑坡体的时空运动过程提供了重要信息。本文结合几个滑坡的深部位移监测实践，综合分析位移监测信息，研究滑坡体的时空运动特征及发展趋势，为滑坡时空运动系统研究及稳定性预测提供依据。     

金龙山斜坡中多变形带的稳定性模糊综合评判

斜坡中发育的多种裂面在滑坡形成过程中将组合成多条变形带，随着变形的发展，变形逐渐向最大剪应力处集中，最终形成滑面。斜坡中多变形带稳定性模糊综合评判是采用数理统计的方法，将滑坡发育过程中影响变形带的因素作为不同的评判因子，对其进行模糊综合评判分析，然后确定最不稳定的变形带。文中最后以金龙山滑坡变形带的稳定性分析为例，证明该方法的正确性。     

丹巴县甲居滑坡复活机制及其稳定性分析

甲居滑坡为一个特大型堆积层古滑坡,因其位于四川省丹巴县甲居藏寨风景旅游区而广受关注.结合滑坡形成的地质环境条件,从滑坡形态、坡体结构、地表变形破坏发育特征等方面人手,对该典型堆积层滑坡进行了分析论述.研究表明,滑坡形成演化历史较为复杂,是一个多级多层滑动形成的非连续复合变形体,其变形复活与滑坡岩土结构、河流侵蚀和人类工程活动密切相关,滑坡具有长期间歇性蠕滑变形特征,以局部滑移为主,难以产生整体性变形破坏,进而为滑坡下一步的监测治理提供了依据.     

位移矢量角在堆积层滑坡时间预报中的应用

针对堆积层滑坡变形破坏特点，运用灰色理论，对滑坡位移观测资料进行了处理，求出了灰色位移矢量角。通过对新滩滑坡灰色位移矢量角特征分析，发现灰色位移矢量角具有与滑体稳定状态相一致的动态特征。因此提出运用灰色位移矢量角来预报堆积层滑坡的新方法。     

滑坡变形监测系统深部与地表变形关系初探

滑坡的孕育、演变、发生是一个累进性变形破坏过程,开展滑坡变形的长期监测工作对滑坡稳定性评价、滑坡的预测预报及治理具有重要的工程意义。目前,滑坡变形监测多集中于坡体表部,很难系统获得反映滑坡稳定性的深部变形资料。本文以某溃屈型滑坡为例,初步分析了滑坡深表部变形的关系,为滑坡稳定性分析及变形破坏趋势预测提供了依据。     

GPS技术在滑坡监测中的应用

探讨了应用GPS技术进行滑坡监测的原则和方法，结合向阳技校滑坡的实际监测资料对这一方法进行了论证。并通过对几年来观测数据的综合分析，得出了滑坡体位移的大小和方向和对该地区地表以及位于滑坡体上的建筑物造成的影响，提出了滑坡预测模型，进而利用该模型和监测数据对滑坡进行了预报，从而对该地区的防灾工作具有重要的意义，也为GPS技术在变形监测中的应用提供了重要的参考价值。     

基于GPS的雅安峡口滑坡变形监测

滑坡是斜坡体物质变形累积到一定程度而形成并发生的,因此通过滑坡体的变形监测,能揭示和预测坡体的变形趋势,且监测的数据精度越高,对滑坡的预测和趋势分析准确度越高.目前对滑坡体的地表变形监测手段很多,但大多数监测数据的精度都不尽如人意,因此监测仪器以及手段的选择至关重要.GPS对静止物体的空间相对定位精度已非常高,本研究正是基于GPS观测数据高精度的特点,借助其对滑坡进行监测,从而分析滑坡的变形特征以及可能发展趋势.     

滑坡稳定性判别的非计算方法

用计算来确定滑坡的稳定性，由于参数选取存不确定因素，就必然导致了其计算结果的不确定性。而滑坡稳定性判别的非计算方法，是通过对滑坡发育程度、形成条件的综合分析来确定滑坡的稳定程度的方法。文中通过归纳分析波坡的形成条件，然后从滑坡地貌条件、动力作用、堆积物特征、诱发因素等方面详细阐述了滑坡稳定性判别的方法，最后，例举了川藏公路102滑坡实例对该方法进行了验证。实践证明该方法是滑坡稳定性中非常实用和有效的方法。     

滑坡预报的BP-GA混合算法

提出了滑坡位移预报的一种改进人工神经网络方法－ＡＮＮ－ＧＡ法,与传统的人工神经网络方法相比,该方法加快一网络的学习速度,提高了滑坡位移的预报精度。同时它是一种面向数据的方法,适合于不同地区不同条件下滑坡的预报。两例滑坡预报平均相对误差分别为３．５５％和１．９３％,明显估于传统的ＢＰ算法（分别为１１．３５％和７．２４％）及ＧＰ改进方法（分别为３．９６％和２．６５％）,表明该方法具有科学性、可行性和有     

GM（1，1）优化模型在滑坡预测预报中的应用

灰色模型在社会科学、自然科学的许多方面已得到广泛的应用，并取得了一系列重大成果。在斜坡(滑坡)地质灾害研究方面，灰色模型多用于斜坡(滑坡)变形的中长期预测预报，且精度较高；但对滑坡短临预测预报精度较差，甚至不能适用，有待改进。滑坡变形预测预报的实际算例表明，以优化灰色模型背景值为基础的优化GM(1，1)模型。具有对建模结果进行优化的能力，即能用于斜坡变形的中长期预测预报，又能适于滑坡短临预测预报。且都能获得较高的模拟和预测精度。应用传统线性GM(1，1)模型和非线性Verhulst模型进行对比分析，检验了优化GM(1，1)模型的正确性和较广泛的适用性。     

岷江上游汶川-较场段滑坡稳定性的神经网络评判及其堵江可能性浅析

在滑坡的变形迹象研究的基础上,采用Ｂ－Ｐ神经网络模型对岷江上游汶川－较场河段内２８个典型滑支的稳定性进行评判,评判结果表明：目前岷江上游汶川－较场河段内共有１０个滑坡处于不稳定状态,在降雨、地震和人类工程活动等诱发因素作用下容易发生滑坡堵江。     

灌溉诱发突发性黄土滑坡机理研究

系统揭示黑方台突发性黄土滑坡物理力学机理,对滑坡防治具有重要的作用。自上世纪六十年代年黑方台常年的农业灌溉诱发了大量20~40 m厚的饱和突发性黄土滑坡。本研究在野外调查的基础上,通过分析滑坡的变形破坏特征,针对分布范围广、危害性较大的突发性黄土滑坡,利用室内GDS三轴试验和模型试验,分析研究了饱和黄土的应力应变特性及突发性黄土滑坡的力学机制。三轴试验结果表明,当围压小于300 kPa时,饱和黄土可产生完全液化,并处于流塑状态;当围压大于300 kPa时,饱和黄土仅产生部分液化,仍具有一定的抗剪强度。饱和黄土的应力—应变模式均表现为强烈的应变软化—剪缩型,并具有一定的稳态特性。模型试验表明突发性黄土滑坡的变形破坏过程可大致分为底部浸水饱和—毛细水上升—持续蠕动变形—突发性破坏4个阶段。斜坡发生突发性破坏时,孔隙水压力激增,但总应力仍大于孔隙水压力,黄土滑坡发生部分液化,饱和黄土仍具有一定的强度,为突发性黄土滑坡发生提供了应力和能量积累的力学条件。研究从有效应力原理的角度阐述了突发性黄土滑坡的力学机理,可以为滑坡的防治治理提供一定的理论依据。     

Predicting landslides for risk analysis — Spatial models tested by a cross-validation technique

A landslide-hazard map is intended to show the location of future slope instability. Most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides, thus precluding use of the maps for probabilistic risk analysis. To correct this deficiency we propose a systematic procedure comprising two analytical steps: “relative-hazard mapping” and “empirical probability estimation”. A mathematical model first generates a prediction map by dividing an area into “prediction” classes according to the relative likelihood of occurrence of future landslides, conditional by local geomorphic and topographic characteristics. The second stage estimates empirically the probability of landslide occurrence in each prediction class, by applying a cross-validation technique. Cross-validation, a “blind test” here using non-overlapping spatial or temporal subsets of mapped landslides, evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides. This quantitative approach, exemplified by several experiments in an area near Lisbon, Portugal, can accommodate any subsequent analysis of landslide risk.     

On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong

This paper presents a statistical approach to study the spatial relationship between landslides and their causative factors at the regional level. The approach is based on digital databases, and incorporates such methods as statistics, spatial pattern analysis, and interactive mapping. Firstly, the authors propose an object-oriented conceptual model for describing a landslide event, and a combined database of landslides and environmental factors is constructed by integrating the various databases within such a conceptual framework. The statistical histogram, spatial overlay, and dynamic mapping methods are linked together to interactively evaluate the spatial pattern of the relationship between landslides and their causative factors. A case study of an extreme event in 1993 on Lantau Island indicates that rainfall intensity and the migration of the center of the rainstorm greatly influence the occurrence of landslides on Lantau Island. A regional difference in the relationship between landslides and topography is identified. Most of the landslides in the middle and western parts of the island occurred on slopes with slope angles of 25–35°, while in the eastern part, the corresponding range is 30–35°. Overlaying landslide data with land cover reveals that a large number of landslides occurred in the bareland and shrub-covered area, and in the transition zones between different vegetation types. The proposed approach can be used not only to analyze the general characteristics of such a relationship, but also to depict its spatial distribution and variation, thereby providing a sound basis for regional landslide prediction.     

Mapping landslide susceptibility from small datasets: A case study in the Pays de Herve (E Belgium)

A landslide susceptibility map is proposed for the Pays de Herve (E Belgium), where large landslides affect Cretaceous clay outcrop areas. Based on a Bayesian approach, this GIS-supported probabilistic map identifies the areas most susceptible to deep landslides. The database is comprised of the source areas of ten pre-existing landslides (i.e. a sample of 154 grid cells) and of six environmental data layers, namely lithology, proximity to active faults, slope angle and aspect, elevation and distance to the nearest valley-floor. A 30-m-resolution DEM from the Belgian National Geographical Institute is used for the analysis. Owing to the small size of the sample, a special cross-validation procedure of the susceptibility map is performed, which uses in an iterative way each of the landslides to test the predictive power of the map derived from the other landslides. Four different sets of variables are used to produce four susceptibility maps, whose prediction curves are compared. While the prediction rates associated with the models not involving the “proximity to active fault” criterion are comparable to those of the models considering this variable, strong weaknesses inherent in the fault data on which the latter rely suggest that the final susceptibility map should be based on a model that excludes any reference to fault. This highlights the difference between a triggering factor and determining factors, and in the same time broadens the scope of the produced map. A single reactivated slide is also used to test the possibility of predicting future reactivation of existing landslides in the area. Finally, the need for geomorphological control over the mathematical treatment is underlined in order to obtain realistic prediction maps.     

Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence

Landslide hazard mapping is a fundamental tool for disaster management activities in mountainous terrains. The main purpose of this study is to evaluate the predictive power of weights-of-evidence modelling in landslide hazard assessment in the Lesser Himalaya of Nepal. The modelling was performed within a geographical information system (GIS), to derive a landslide hazard map of the south-western marginal hills of the Kathmandu Valley. Thematic maps representing various factors (e.g., slope, aspect, relief, flow accumulation, distance to drainage, soil depth, engineering soil type, landuse, geology, distance to road and extreme one-day rainfall) that are related to landslide activity were generated, using field data and GIS techniques, at a scale of 1:10,000. Landslide events of the 1970s, 1980s, and 1990s were used to assess the Bayesian probability of landslides in each cell unit with respect to the causative factors. To assess the accuracy of the resulting landslide hazard map, it was correlated with a map of landslides triggered by the 2002 extreme rainfall events. The accuracy of the map was evaluated by various techniques, including the area under the curve, success rate and prediction rate. The resulting landslide hazard value calculated from the old landslide data showed a prediction accuracy of > 80%. The analysis suggests that geomorphological and human-related factors play significant roles in determining the probability value, while geological factors play only minor roles. Finally, after the rectification of the landslide hazard values of the new landslides using those of the old landslides, a landslide hazard map with > 88% prediction accuracy was prepared. The methodology appears to have extensive applicability to the Lesser Himalaya of Nepal, with the limitation that the model's performance is contingent on the availability of data from past landslides.     

长江三峡库区梯田稳定性分析与对策*──以鄂西秭归县为例

三峡库区历史上就是滑坡、崩塌作用强烈的地带,在调查分析秭归县滑坡、崩塌对梯田稳定性的影响的基础上,探讨了四种不稳定梯田培坎的特征、性质和现状,提出了利用优势植物固土护坎等相应的对策。     

数字地形分析在滑坡研究中的应用综述

高效的数字地形分析（Digital Terrain Analysis,DTA）是滑坡预测与评估研究的重要手段。文章综述了DTA在滑坡研究中的应用现状,基本内容包括地形因子分析、地形形态分析、地形单元划分以及DEM与滑坡模型的结合分析。地形因子分析的应用多而广,主要思路是在地形因子与滑坡发育的关系研究基础上分析其滑坡敏感性,进而构建滑坡预测和评估模型;地形形态分析是滑坡识别的重要手段,加强地貌形态和滑坡发育的关系研究有助于对潜在滑坡地形的识别;地形单元划分能为滑坡研究提供统计和分析单元;DEM与滑坡专业模型的结合方式多样,程度各异。同时,从尺度选择与转换的角度探讨了DTA滑坡研究的尺度问题,分析了DTA的局限性,指出DEM不能提供完备无误的地形信息,DTA不能完全取代常规的地形分析。最后,基于以上论述对未来的研究趋势提出了展望。     

地形对黄土高原滑坡的影响

高分辨率地形与影像数据的缺乏已成为研究地表现象、特征与过程的重要瓶颈。低成本无人机设备和摄影测量技术的发展,打开了地学领域获取高分辨率数据的大门,大大提高了地质灾害野外调查与灾害编目的精度与效率。本文通过无人机野外调查和遥感室内目视解译,构建了一个包含307个黄土滑坡属性的数据库。在此基础上,通过数字地形分析和数理统计等方法,总结归纳了黄土滑坡样本数据的分布规律,探讨了地形对黄土滑坡分布的影响,阐述了地形相对高差对最长滑动距离、滑坡周长、滑坡面积的影响,提出了基于传统经验公式拟合的滑坡规模快速预测公式。结果表明：① 滑坡规模—频率分布具有明显的规律性,不同最大长度、最大宽度和周长的黄土滑坡数量分布均呈现正偏态分布,而不同面积的滑坡数量分布则服从幂函数分布;② 地形对黄土滑坡发育控制作用明显,不同地形高差、平均坡度、坡形的斜坡单元滑坡发育数量差异较大;③ 地形相对高差与滑坡的最长滑距、周长和面积的拟合曲线很好地符合幂律分布规律,但不同地形区的拟合效果有所差异,黄土丘陵区拟合效果最好,黄土高原全区次之,黄土台塬区最差;④ 本文建立的黄土滑坡规模快速预测模型,为黄土滑坡灾害调查提供了经验公式支撑。     

汶川地震灾区滑坡空间特征变化分析

“5.12”汶川大地震触发了大量滑坡,给人民群众生命财产和社会经济发展造成了巨大损失。基于GIS空间分析方法,结合震前和震后的滑坡编目数据,对滑坡与坡度、坡向、高程、岩土类型、道路、河流和断裂带等7个孕灾环境因素的空间分布关系进行统计分析。结果表明：滑坡与孕灾环境因素的空间分布关系受地震的影响比较大。相比于震前,震后滑坡发生的优势坡度、优势岩土类型、优势距离缓冲区等均发生了很大的变化;并且坡向、距道路距离、距河流距离等因素对滑坡有明显地趋势性影响。