基于GIS的城市滑坡灾害易发性评价——以湖北省宜昌市城区为例

[目的]对城市滑坡灾害进行易发性分区评价,为城市规划与防灾减灾工程提供理论依据。[方法]以湖北省宜昌市城区为研究区,通过GIS平台选取高程、坡度、地层岩性、归一化植被指数(NDVI)、与水系的距离和道路密度等6个评价因子,采用似然比方法分析评价因子和滑坡发育的关系,并以归一化似然比值将评价因子参数分类量化;以量化值作为Logistic回归模型的自变量,抽取样本数据建立滑坡易发性评价回归模型。[结果]评价因子结果显著,模型的整体准确率达到79.2%,ROC曲线下面积达0.871;极低易发区和低易发区占全区面积的61.59%,包含滑坡灾害的11.29%;高易发区和极高易发区虽仅占全区面积的17.88%,却发育了68.55%的滑坡灾害,结果与滑坡灾害分布特征相符合。[结论]对宜昌市城区的滑坡易发性进行了等级划分。采用GIS和Logistic回归相结合的滑坡易发性评价方法,结果准确可靠。     

GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations

The Ardesen area is prone to landslides because of the climate conditions, geologic, and geomorphologic characteristics of the region. As in previous years, in 2001 due to heavy rainfall there were many landslides resulting in damage and human casualties. There is still a great danger of further landslides in the region. Therefore, it is vitally important to prepare a landslide susceptibility map of the region. In this study, the analytical hierarchy process (AHP), the statistical index (Wi), and weighting factor (Wf) methods were used to produce and later compare three susceptibility maps. For this purpose, thematic layers including landslide inventory, lithology-weathering, slope, aspect, land cover, distance to stream, drainage density, and distance to road were used. In this study area, 98% of landslides occurred in highly or completely weathered units. Lithology-weathering, land cover, and slope data layers were found to be important factors in the study area. To confirm the practicality of the three susceptibility maps were compared with a landslide activity map containing 16 active landslide zones. The outcome was that the active landslide zones do not completely fit into the high and very high susceptibility classes. But 81.3% of these landslide zones fall into the high and very high susceptibility zones of the AHP method while this is 62.5% in the case of Wi method, and 68.8% with the Wf method. In spite of the results obtained in this study, the development of a susceptibility map is usually determined by the needs and available resources. The results showed that the AHP method gave a more realistic picture of the actual distribution of landslide susceptibility, than the Wi and Wf methods.     

遵义市不同地质灾害易发区滑坡临界雨量研究

[目的]确定遵义市不同地质灾害易发区的滑坡临界雨量,建立阈值模型并对其进行检验评估,为该地区滑坡预测提供科学依据。[方法]利用遵义市2010—2016年59次滑坡事件对应的逐小时降雨资料,采用统计方法对不同地质灾害易发区的滑坡临界雨量的历时、降雨类型对比分析,建立阈值模型并对其进行检验评估。[结果]中锋型是主要的降雨类型;大于10和20mm/h强降雨基本来自滑坡发生当天,但中易区降雨历时均长于高易区的降雨历时。对于高易区来说,滑坡当日1h最大雨量与前期3d的有效雨量组合的阈值模型预报准确率最大,因此将滑坡当天1h最大雨量作为高易区滑坡发生的激发雨量。而对于中易区来说,滑坡当天3h最大雨量是其滑坡发生的激发雨量。[结论]不同等级地质灾害易发区其滑坡临界雨量不同。对已经确定的滑坡阈值模型需根据新增滑坡信息进行检验评估,如果预测模型对新增滑坡预测不准确,需调整其滑坡判别线,从而对阈值模型进行订正。     

Study on Vegetation Root Strength of Pioneer Plants for Forest Areas in Taiwan

Forest plant roots may restrain the occurrence of shallow landslides for forest land and pioneer tree species can also reduce runoff and soil erosion;thus they are useful practical ecological materials for landslide control and erosion control. In this study, two important pioneer plant species ; Formosan Alder （Alnus formosana Makino） and Roxburgh Sumac （Rhus chinensis Mill. Var, roxburghi i（DC. ） Rehd. ） were selected at landslide areas under vegetation treatments for soil and water conservation. In order to obtain the root strength model for the factors affecting pulling resistance and root tensile strength, experimental materials were tested and the data were analyzed using regression techniques. These models could be used to provide the index of slope stability and to quantify the root-strength using non-destructive methods.     

比较二元逻辑回归和层次分析法评估罗马尼亚Dobrovat河盆地滑坡敏感性

A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil conservation. The purpose of the present study was to compare the usefulness of two methods, i.e., binary logistic regression (BLR) and analytical hierarchy process (AHP), for the assessment of landslide susceptibility over a 130-km² area in the Moldavian Plateau (eastern Romania) region, where landslides affect large areas and render them unsuitable for agriculture. A large scale inventory mapping of all types of landslides (covering 13.7% of the total area) was performed using orthophoto images, topographical maps, and field surveys. A geographic information system database was created, comprising the nine potential factors considered as most relevant for the landsliding process. Five factors (altitude, slope angle, slope aspect, surface lithology, and land use) were further selected for analysis through the application of a tolerance test and the stepwise filtering procedure of BLR. For each predictor, a corresponding raster layer was built and a dense grid of equally spaced points was generated, with an approximately equal number of points inside and outside the landslide area, in order to extract the values of the predictors from raster layers. Approximately half of the total number of points was used for model computation, while the other half was used for validation. Analytical hierarchy process was employed to derive factor weights, with several pair-wise comparison matrices being tested for this purpose. The class weights, on a scale of 0 to 1, were taken as normalized landslide densities. A comparison of results achieved through these two approaches showed that BLR was better suited for mapping landslide susceptibility, with 82.8% of the landslide area falling into the high and very high susceptibility classes. The susceptibility class separation using standard deviation was superior to either the equal interval or the natural break method. Results from the study area suggest that the statistical model achieved by BLR could be successfully extrapolated to the entire area of the Moldavian Plateau.     

The impacts of logging on landslide activity at Clayoquot Sound, British Columbia

The objective of this study was to investigate the impacts of logging on landslide activity in Clayoquot Sound on the west coast of Vancouver Island, British Columbia. A total of 1004 landslides were documented in order to test the hypothesis that areas affected by logging activities show different density, frequency and magnitude characteristics of landsliding than areas unaffected by logging. The frequency of landslides in logged terrain was found to be nine times higher than in undisturbed forest. An exponential increase in landslide frequency within the area logged was observed on a large watershed scale. Failures in logged terrain occur on gentler slopes than in natural terrain, partly because fewer slopes steeper than 40° have been logged. Debris slides and debris flows are the most frequently occurring mass movements, initiating mostly from road fill failures and from within cutblocks. Most landslides initiated on SE-facing slopes, with the highest landslide frequency near the coast and diminishing exponentially further inland. This pattern of activity most likely reflects the greater impact of severe storms arriving from the Pacific with winds dominating from the southeast. Concave and straight slopes are most susceptible to landslide initiation. A preliminary examination of geologic control on the frequency of landslides suggests that the Quatsino Formation, the Island Plutonic Suite and the Sicker Group are significantly above the average rate. Further work is needed to identify and quantify factors confounding the trends and correlations identified in this overview study. Results obtained in this study will be used to implement changes in forest management.     

黄土滑坡稳定性评价的集合卡尔曼滤波同化方法

[目的] 为提升区域滑坡稳定性评价模型的预测精度,解决传统滑坡稳定性分析基于静态的物理模型过度简化滑坡发生机理与力学机制,导致过度预测的缺点,以及模型参数通常具有的时空变异性、不确定性的问题。[方法] 基于集合卡尔曼滤波的数据同化方法,以甘肃省兰州市北环路周边区域为例,构建了基于TRIGRS模型和SBAS-InSAR观测数据的区域滑坡数据同化方案,对模型中的安全系数(F_s)进行同化,更新模型参数内摩擦角,进而修正滑坡稳定性,并利用均方根偏差(RMSD)检验同化值的精度。[结果] 同化后研究区域滑坡安全系数明显高于模型预测的结果,不稳定区域的面积比例由12 %降低至7 %,与实际观测更为接近;试验使内摩擦角参数逐渐向观测值方向改正,实现了模型参数的动态更新;均方根偏差从0.33减小到0.04左右。[结论] 基于集合卡尔曼滤波的数据同化方法有效修正了模型稳定性预测结果,可以更准确体现当前区域滑坡实际情况,具有更高的预测精度。     

长江中下游地区滑坡的易发性评价——以江西省为例

[目的] 预测长江流域滑坡灾害分布情况,旨在开展隐患排查和危险评估,提升灾害的应对能力。[方法] 基于1 211个滑坡分布点数据和15个环境变量,通过MaxEnt模型对江西省的滑坡易发区分布进行预测,同时采用Jackknife检验评估15个环境变量对预测结果的重要程度,最终确定不同程度滑坡易发区的面积和分布以及影响滑坡灾害发生的主要环境变量。[结果] 江西省内极高、高和中易发区分别占全省总面积的29.6%,36.5%和23%。滑坡发生的概率以鄱阳湖平原为中心向四周呈现逐渐增加的趋势,集中分布在西部和南部的山地丘陵地带。海拔、坡度、植被归一化指数NDVI、年均降雨量和距离水系和道路的距离是影响滑坡发生和分布的主要环境变量,累积贡献率在83%以上。[结论] 江西省滑坡易发区的分布具有明显的空间差异性,主要分布在海拔较高、地质复杂和岩层节理裂隙发育的地区,降雨是滑坡发生的直接诱导因子。     

Topographic controls of landslides in Rio de Janeiro: field evidence and modeling

Landslides are common features in the Serra do Mar, located along the southeastern Brazilian coast, most of them associated with intense summer storms, specially on the soil-mantled steep hillslopes around Rio de Janeiro city, where the favelas (slums) proliferated during the last few decades. On February 1996, hundreds of landslides took place in city of Rio de Janeiro triggered by intense rainstorms. Since then, many studies have been carried out in two experimental river basins in order to investigate the role played by the topographic attributes in controlling the spatial distribution of landslides inside them. Landslide scars and vegetation cover were mapped using aerial photographs and field observations. A detailed digital terrain model (4 m² resolution) of the basins was generated from which the main topographic attributes were analyzed, producing maps for slope, hillslope form, contributing area and hillslope orientation. By comparing these maps with the spatial distribution of the landslide scars for the 1996 event, a landslide potential index (LPI) for the many classes of the different topographic attributes was defined. At the same time, field experiments with the Guelph permeameter were carried out and a variety of scenarios were simulated with the SHALSTAB model, a process-based mathematical model for the topographic control on shallow landslides. The results suggest that most of the landslides triggered in the studied basins were strongly influenced by topography, while vegetation cover did affect landslide distribution. Between the topographic attributes, hillslope form and contributing area played a major role in controlling the spatial distribution of landslides. Therefore, any procedure to be used in this environment towards the definition of landslide hazards need to incorporate these topographic attributes.     

汶川地震灾区崩塌滑坡体几何特征信息遥感定量提取与分析

选取灾区107个崩塌滑坡样本,利用遥感影像获取崩塌滑坡面积,遥感影像结合DEM获取崩塌滑坡体坡高(前后缘高差)、滑移距离、视摩擦角等信息,通过野外调查获取体积信息,对灾害评估中关注的两个关键因子崩塌滑坡体体积、滑移距离与各特征因子的相关性进行了分析,探讨了体积、滑移距离与相关性显著因子间的关系。研究表明,崩塌滑坡体体积与崩塌滑坡面积、坡高相关性显著,且与崩塌滑坡面积呈显著的幂函数关系,与坡高呈二次多项式关系,与滑移距离、视摩擦角有一定关系,但不显著;崩塌滑坡滑移距离与坡高相关性显著,且呈线性关系,与崩塌滑坡面积也有一定关系,但不十分显著。     

基于Logistic回归和MCMC方法评价地震滑坡敏感性

Logistic回归模型(Logistic Regression,LR)在滑坡敏感性评价上应用广泛,但目前对于模型参数不确定性的研究较为缺乏。马尔可夫链蒙特卡罗(Markov Chain Monte Carlo,MCMC)方法能够结合参数的先验信息得到其后验分布,从而对估计参数的不确定性进行分析。为探索MCMC方法在Logistic滑坡敏感性模型构建中的有效性; 量化模型参数估计值的不确定性,以西南地区2013年4·20芦山地震,2017年8·8九寨沟地震和2014年8·3鲁甸地震为例,基于MCMC方法对Logistic回归模型的回归系数进行估计。构建了区域的地震滑坡敏感性模型,对模型参数的估计值进行了不确定性分析,并绘制了区域的滑坡敏感性图。结果表明:在芦山地震案例中,模型参数估计值的不确定性都比较低; 在九寨沟案例中,岩性因子的参数估计值不确定性较高; 在鲁甸地震中,岩性、剖面曲率和平面曲率的参数不确定性较高。总的来说,模型中的大多数参数估计值不确定性都较低。所构建的Logistic回归模型在三次地震滑坡事件中的预测精度都较高,AUC(Area Under ROC Curve)值均在0.9以上,这证明了MCMC方法对Logistic模型参数估计的准确性。在三次地震滑坡事件中,因子相对重要性最大的为高程,其次为距离断层的距离以及修正麦卡利烈度。研究为利用LR模型进行滑坡敏感性评价提供了一种新的思路和方法。     

香港暴雨中心迁移与滑坡位置关系分析

香港地区每年均有一定数量的滑坡灾害发生,诱发滑坡灾害的主要因子是强降水,即暴雨.暴雨过程中,降水强度的时空分布存在一定差异性,这种降水强度的时空与滑坡灾害的时空分布存在一定的联系.以香港地区1992年5月8日暴雨为例,以30 min为时间间隔,分析了暴雨中心时空变动与滑坡事件时空分布及出现频率之间的关系,发现空间上滑坡均出现在暴雨中心或暴雨中心的边沿地区;时间上滑坡事件出现在暴雨中心出现或上一阶段时间内;并且降水的强度与滑坡的出现频率也有一定关系.     

反距离加权法在区域滑坡危险性评价中的应用

区域滑坡危险性评价是进行区域滑坡风险性研究的基础。提出了一种基于反距离加权的"黑箱"式评价方法,该方法将滑坡作为一个系统进行分析,各影响因素作为滑坡系统中的子系统。根据相似相近的原理,假设已有滑坡点对周围区域的滑坡危险性存在局部性影响,利用反距离加权法对所有滑坡点进行分析评价,以获取研究区的滑坡危险性评价结果。同时对该方法运用于区域滑坡危险性评价的理论基础、适用范围进行分析,并以四川省苍溪县为例,验证了运用该方法进行区域滑坡危险性评价的可行性。     

滑坡的多模型综合预测预报研究

由于滑坡的复杂性以及预报模型和方法的局限性,简单地利用单一的滑坡预测预报模型准确地预报滑坡的滑动时间还很困难。为了提高滑坡预报的准确度,提出了在滑坡原型调研和机制研究的基础上,以滑坡的监测资料为依据,通过监测点的选取、监测信息的处理和变形阶段的判别,选择多个与所预报滑坡相适宜的预测预报模型对滑坡的滑动时间进行预测预报,并对多个模型的预报结果进行综合评判得出预报结果,最后以黄龙西村滑坡实例进行了应用。     

Comparative analysis of SHALSTAB and SINMAP for landslide susceptibility mapping in the Cunha River basin,southern Brazil

Purpose

The Shallow Landsliding Stability Model (SHALSTAB) and Stability Index Mapping (SINMAP) models have been applied to various landslide management and research studies. Both models combine a hydrological model with an infinite slope stability model for predicting landslide occurrence. The objectives of the present study were to apply these two models to the Cunha River basin, Santa Catarina State, southern Brazil, where many landslides occurred in November 2008, and perform a comparative analysis of their results.

Materials and methods

Soil samples were collected to determine the input parameters. The models were calibrated with a landslide scar inventory, and rainfall data were obtained from three rain gauges. A comparison of their results obtained from the models was undertaken with the success and error index.

Results and discussion

Based on the maps of stability and instability areas for the study basin, the models performed well. Since the initial equations of both models are not particularly different, their results are similar. Locations with steep slopes, as well as areas with concave relief that tend to have larger contribution areas and moisture, have lower stability indexes. SHALSTAB classified only ~13 % of the total area of the Cunha River basin as unstable, while SINMAP classified ~30 % as unstable.

Conclusions

The analysis of maps based on the results of the two models shows that if SHALSTAB is correctly calibrated, based on hydrological parameters, its results could be more accurate than SINMAP in the prediction of landslide areas. Although SINMAP showed better calibration of the landslide scars, its classification over the basin results in an overestimation of stability areas. The conclusion is that SHALSTAB is more suitable than SINMAP for the prediction of landslides in the Cunha River basin, Brazil.     

汶川震区滑坡堆积体体积三维激光扫描仪测量与计算方法

2008年5.12汶川8级地震形成的大量松散滑坡堆积体,破坏农用地,损毁农田基础设施,对震区农业经济造成重大损失,严重威胁震区农业生产安全。本研究所选震区典型滑坡堆积体位于汶川县草坡乡,采用三维激光扫描仪实地测量滑坡堆积体,构建滑坡堆积体几何模型,计算滑坡堆积体体积。扫描仪到滑坡堆积体前、后缘的距离分别为25.74和79.00 m,距离扫描仪200 m处的扫描精度为20.0 cm×20.0 cm。根据扫描得到的滑坡堆积体点云数据,采用特征值法拟合近似滑坡堆积体的坡面、滑动面,构建滑坡堆积体几何模型。计算得到该滑坡堆积体体积为19 018 m3。建立了使用三维激光扫描仪测量和计算滑坡堆积体体积的方法。这种测量与计算方法可为地震受损农用地灾后的土地整理提供重要依据。     

基于IOE和SVM模型的府谷镇滑坡易发性分区

将陕西省府谷县府谷镇作为研究区,通过野外实地调查,圈定了47个滑坡点,制作了研究区滑坡编录图。以GIS软件和统计分析模型为基础,开展研究区滑坡易发性分区研究。首先通过GIS软件将滑坡点随机分成训练样本（70%）和测试样本（30%）两组。然后选择坡度、坡向、高程、距断层的距离、距道路的距离、距河流的距离、岩性、土地利用、NDVI、降雨量作为影响因子,提取因子图层。分别应用熵权模型（IOE）和支持向量机模型（SVM）计算滑坡易发性指数,利用自然间断点法将研究区划分为低易发区、中易发区、高易发区和极高易发区。最后利用ROC敏感度曲线下的面积（AUC）分别检验两种模型所得到的分区结果,结果表明,成功率曲线和预测度曲线的AUC值均在0.70～0.90,表明两种模型所得到的分区结果具有较高的精度,都可以为研究区的滑坡防治提供参考。在训练样本和测试样本中SVM模型的AUC值均最高,说明SVM模型比IOE模型适合在研究区开展滑坡预测研究。     

基于GBDT-LR和信息量模型耦合的滑坡易发性评价

[目的]探索准确、快速的滑坡易发性区划方法,为区域安全监测提供参考,为政府治理滑坡灾害提供科学依据。[方法]以安徽省池州市贵池区为研究区域,采用梯度提升决策树—逻辑回归(GBDT-LR)和信息量(I)模型耦合的方法,实现区域滑坡易发性评价。该方法通过对原样本地学习,组合产生新的模拟样本,从而增强易发性评价模型对滑坡的拟合能力;采用Borderline-Smote算法解决样本数据不对称的问题。选用r.slopeunits软件划分的斜坡单元作为最小评价单元,选取坡度、坡向、地形曲率、剖面曲率、平面曲率、地形湿度指数(TWI)、地形起伏度、归一化植被指数(NDVI)、距断裂距离和距水系距离总计10个评价因子。分别从频率比、滑坡灾害点及隐患点密度、ROC曲线3个方面对构建的滑坡易发性模型进行评价。[结果]试验结果表明：耦合模型I-GBDT-LR分别比I,LR,I-LR模型的高易发区频率比所占比例提升约10%,13%,7%,高易发区滑坡灾害点及隐患点密度分别提升约9,11,7,ROC精度提升约10%,9%,5%。[结论]从检验指标综合来看,耦合模型的精度均高于单一模型,所提出耦合模型精度又高于I...     

A Comparative Analysis of Binary Logistic Regression and Analytical Hierarchy Process for Landslide Susceptibility Assessment in the Dobrovǎt River Basin,Romania

A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil conservation. The purpose of the present study was to compare the usefulness of two methods, i.e., binary logistic regression(BLR) and analytical hierarchy process(AHP), for the assessment of landslide susceptibility over a 130-km~2 area in the Moldavian Plateau(eastern Romania) region, where landslides affect large areas and render them unsuitable for agriculture. A large scale inventory mapping of all types of landslides(covering 13.7% of the total area) was performed using orthophoto images, topographical maps, and field surveys. A geographic information system database was created, comprising the nine potential factors considered as most relevant for the landsliding process. Five factors(altitude, slope angle, slope aspect, surface lithology, and land use) were further selected for analysis through the application of a tolerance test and the stepwise filtering procedure of BLR. For each predictor, a corresponding raster layer was built and a dense grid of equally spaced points was generated, with an approximately equal number of points inside and outside the landslide area, in order to extract the values of the predictors from raster layers. Approximately half of the total number of points was used for model computation, while the other half was used for validation. Analytical hierarchy process was employed to derive factor weights, with several pair-wise comparison matrices being tested for this purpose. The class weights, on a scale of 0 to 1, were taken as normalized landslide densities. A comparison of results achieved through these two approaches showed that BLR was better suited for mapping landslide susceptibility, with 82.8% of the landslide area falling into the high and very high susceptibility classes. The susceptibility class separation using standard deviation was superior to either the equal interval or the natural break method. Results from the study area suggest that the statistical model achieved by BLR could be successfully extrapolated to the entire area of the Moldavian Plateau.     

基于Mein-Larson入渗模型的降雨滑坡失稳破坏概率研究

[目的]评价降雨诱发浅层滑坡的失稳破坏概率,为相关研究提供理论依据。[方法]在引入并扩展了Mein-Larson降雨入渗模型的基础上,将Mein-Larson入渗模型与无限边坡稳定性方法有机结合,建立2种降雨情形(高强度短历时和低强度长历时)下降雨滑坡稳定性的确定性评价模型,然后再将蒙特卡洛数值模拟方法与降雨滑坡的确定性评价模型结合,建立降雨滑坡稳定性的概率评价方法。[结果]提出了1种降雨诱发浅层滑坡失稳的概率评价方法。[结论]概率评价方法可以描述降雨滑坡发生及发展过程中存在的不确定性,可以计算不同降雨情形下,不同降雨时刻降雨诱发边坡的失稳破坏概率。该方法的评价结果更符合边坡实际情况。