基于GIS的重庆市万州区滑坡灾害危险性评价

在充分调查万州区地质环境及滑坡灾害基本特征的基础上,根据资料的有效性和可获得性,选取地表高程、坡度、地层岩性、地质构造、土地利用类型、区域交通建设和河流侵蚀冲刷7个影响滑坡发生的因素作为评价指标,采用AHP法确定各个指标的权重并建立滑坡灾害危险性指数模型,通过GIS系统的空间分析功能进行栅格运算,得出研究区滑坡灾害危险性分区.采用上述指标和方法将重庆市万州区的滑坡灾害划分为极高危险区、高危险区、中危险区、低危险区和极低危险区,划分结果符合该区滑坡灾害的实际情况.     

高山峡谷区地质灾害危险性评价

针对崩塌、滑坡和泥石流等灾种齐全的高山峡谷区,选取四川省阿坝县为研究区,采用多灾种耦合的评价思路,开展地质灾害危险性精细化评价。崩塌、滑坡等斜坡类灾害危险性评价以栅格为评价单元,泥石流灾害危险性评价以流域为评价单元。基于信息量模型和层次分析法,分别开展危险性评价,进而采用取大值的方法,获取研究区综合地质灾害危险性评价结果。研究表明,工作区综合地质灾害极高危险区、高危险区面积明显大于单灾种评价结果,极高危险区、高危险区主要位于崩塌、滑坡较发育的碎裂岩区域和极度易发的泥石流流域。针对高山峡谷区地质灾害危险性评价,多灾种耦合的评价思路能更合理的反映不同类型灾害在形态及空间上的差异,获取更精确的危险性评价结果。     

基于GIS的重庆万州区滑坡灾害危险性评价

在充分调查万州区地质环境及滑坡灾害基本特征的基础上,根据资料的有效性和可获得性,选取地表高程、坡度、地层岩性、地质构造、土地利用类型、区域交通建设及河流侵蚀冲刷7个影响滑坡发生的因素作为评价指标,采用AHP法确定各个指标权重并建立滑坡灾害危险性指数模型,通过GIS系统的空间分析功能进行栅格运算,得出研究区滑坡灾害危险性分区。采用上述指标和方法将重庆市万州区的滑坡灾害划分为极高危险区、高危险区、中危险区、低危险区和极低危险区,划分结果符合该区滑坡灾害的实际情况。     

四川省雅江县上游河段滑坡灾害危险性评价

雅江县位于四川省西部雅砻江中游河段,以中山-高山峡谷地貌为主,地质灾害频发.为保障人民生命财产安全,基于逻辑回归与确定性系数叠加分析,进行雅江县上游河段滑坡灾害危险性评价.结果表明：1）雅江县上游河段滑坡极易发生在海拔2 500~3 000 m、拔河高度600~900 m、坡度30~45°、距离河流水系0~200 m范围较硬岩夹较软岩类地带;2）雅江县上游河段高危险区、极高危险区面积占总面积的46.75%,发生滑坡占滑坡总数的65.91%,说明该区域内滑坡分布密集,危害程度相对较高,与野外实际调查结果相符;3）雅江县上游河段呷拉镇一带多属极高危险区、高危险区,瓦多乡一带多属中等危险区,木绒乡、普巴绒乡一带多属低危险区、极低危险区;4）通过查验点及ROC曲线对评价结果验证,该评价结果有较高的准确性,能够作为研究区防灾减灾与河谷开发利用的合理方案依据.     

基于证据权法的九寨沟地震滑坡危险性评价

2017年8月8日四川省北部九寨沟县暴发了Ms7.0级地震,是继2013年"4·20"芦山Ms7.0级地震后再次发生在巴颜喀拉块体边界的强烈地震,地震诱发了近1 880处滑坡,通过地理信息系统与遥感技术,选取与高程、坡度、坡向、与水系距离、峰值加速度(PGA)、与震中距离、岩性、与断裂距离等8个因素作为九寨沟地震滑坡危险性评价因子,采用加法和减法2种证据权方法,对九寨沟地震滑坡危险性进行评价。结果表明:基于加法证据权的评价模型的准确率为88.29%,基于减法证据权的评价模型的准确率为87.31%。利用自然断点法,将研究区按滑坡危险性程度分为极高危险区、高危险区、中危险区、低危险区与极低危险区。其中,基于加法证据权所计算的极高和高危险区面积之和约300.17 km~2,占研究区总面积的33.84%,发育的滑坡面积占滑坡总面积的91.10%;基于减法证据权所计算的极高和高危险区面积之和约214.35 km~2,占研究区总面积的24.17%,发育的滑坡面积占滑坡总面积的85.04%。评价结果可为震后地质灾害防治、基础设施重建,特别是九寨沟自然风景区的灾后重建工作提供重要的参考。     

证据权法在区域滑坡危险性评价中的应用以贵州省为例

以GIS为技术平台,采用证据权法对研究区进行了滑坡地质灾害危险性分析。综合分析历史滑坡数据及其环境因素和触发因素,数据源主要有地形图、DEM、地质图,选取地层岩性、构造、高程、坡度、坡向、地形起伏度、道路、水系作为危险性评价因子。首先应用ArcGIS软件对数据源进行处理,提取各个评价因子图层,并对每个图层进行分级、缓冲区分析等处理,建立若干证据层。然后将历史灾害点与评价因子进行空间关联分析,计算每个评价因子等级的权重,最后计算出评价单元的危险性指数,并将危险性分为极高危险区、高危险区、中等危险区、低危险区。采用成功率曲线法对证据权法评价精度进行验证,结果表明本次评价的精度为71%。利用历史滑坡数据对评价结果进行验证,结果显示评价结果与实际情况较为吻合,说明证据权可以客观定量地评价各影响因子对滑坡的影响程度,该方法应用于区域地质灾害危险性评价比较有效。     

三峡库区重庆市丰都县滑坡灾害危险性评价

在对三峡库区丰都县滑坡灾害调查和统计分析的基础上,初步概括了滑坡灾害的分布特征和主要影响因素,进而利用综合信息模型评价了丰都县滑坡灾害的危险性,将丰都县滑坡灾害的危险性划分为高危险区、中危险区、低危险区和基本安全区4个等级。其中,高危险区和中危险区分别占全县总面积的2.6%和23.2%,主要分布在长江干流及其支流两岸的居民相对集中区,不同规模的滑坡灾害经常发生,因此潜在危害也很大;低危险区占全县总面积的47.5%,偶有小规模的滑坡灾害发生;基本安全区占全县总面积的25.5%,在人为因素的诱发下可能偶有小规模的滑坡灾害发生,适合于大型工程建设和城镇居民点建设。     

基于Random Forest 和AHP的贵德县北部山区滑坡危险性评价

滑坡危险性评价是滑坡灾害防治和管理的重要依据。文章基于层次分析法和随机森林模型,结合距离函数法,探索性地提出了一种新的组合赋权法（RF-AHP）。采用RF-AHP对青海省贵德县北部山区滑坡进行了危险性评价,对比探讨了AHP、RF和RF-AHP三种模型评价结果与实际滑坡灾害的吻合性,结果表明:（1）RF-AHP在高危险区和极高危险区面积占比38.38%的情况下,包括了60.13%的滑坡灾害,结果准确性相比AHP和RF两种模型有较大提升;（2）随着危险性等级的逐步提高,RF-AHP区划结果中相应分区的灾害实际发生的比率也随之增高,并对三种方法出现结果差异的客观原因进行了分析讨论,证明RF-AHP适用于滑坡危险性评价工作。     

基于GIS的涪江上游南坝-水晶流域滑坡危险性评价

本文以涪江上游南坝-水晶流域滑坡为研究对象, 选取坡度、高程、坡向、岩性、岸坡结构等9个影响因子, 基于GIS平台, 采用滑坡确定性系数模型与层次分析模型相结合的 (CF-AHP) 模型对研究区进行滑坡危险性评价。根据评价结果, 将研究区划分为极高危险区 (18. 57%) 、高危险区 (38. 71%) 、中危险区 (23. 92%) 、低危险区 (18. 8%) 四个等级。利用危险性评价结果对比法和受试者工作特征曲线 (ROC) 对评价结果进行验证, 得到ROC曲线下面积AUC值为88. 36%, 表明CF-AHP模型能够较客观准确地对研究区滑坡危险性评价。     

基于I-CF模型的四川德格县滑坡危险性评价与区划CSCD

文章以德格县为研究区,以7 m DEM进行地形分析处理,并结合相关调查数据建立了德格县滑坡灾害数据库,通过选取的地震峰值加速度、断裂带、水系、坡度、坡向、高程、岩性等7个指标,在GIS技术支持下,利用信息量模型(I)、层次分析法模型(AHP)、确定性系数模型(CF)相互耦合对研究区灾害敏感性评价,再分析得到活动频率因素对研究区全县域进行危险性评价,将得到的结果分成4个区域,分别为高危险区、较高危险区、中危险区、低危险区,其中高、较高危险区占总面积2.23%。其中,滑坡灾害占总灾害的42%。评价结果与实际调查结果符合程度较高,能够为该地域未进行实地调查的地方进行相关滑坡灾害的预测预报,并对安全防治提供技术支持,亦可以为其他地区滑坡灾害危险性评价提供理论指导和技术参考。     

六盘山东麓断裂带滑坡类型与变形机理研究——以泾河源区为例

六盘山东麓地层结构特殊,断裂褶皱等构造发育,滑坡及其隐患点等不良地质灾害较多,特殊的地理、构造位置和潜在的孕震背景,致使该区具有产生大型滑坡的可能。本文依据新一轮以图幅带专题研究的地质灾害调查获取大量的数据,通过统计分析,对六盘山东麓断裂带滑坡产生的孕灾地质环境条件及其滑坡特性等进行了剖析,将研究区滑坡归纳为红层软岩滑坡、断层影响型滑坡、堆积层滑坡、黄土型滑坡4种不同类型,同时对其形成机理进行了探讨分析与研究,为完成地质灾害风险性区划评价,提出地质灾害综合防治对策建议提供了重要的理论依据。     

Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (Akşehir,Turkey)

Landslides cause heavy damage to property and infrastructure, in addition to being responsible for the loss of human lives in many parts of the Turkey. The paper presents GIS-based spatial data analysis for landslide susceptibility mapping in the regions of the Sultan Mountains, West of Akşehir, and central part of Turkey. Landslides occur frequently in the area and seriously affect local living conditions. Therefore, spatial analysis of landslide susceptibility in the Sultan Mountains is important. The relationships between landslide distributions with the 19 landslide affecting parameters were analysed using a Bayesian model. In the study area, 90 landslides were observed. The landslides were randomly subdivided into 80 training landslides and 10 test landslides. A landslide susceptibility map was produced by using the training landslides. The test landslides were used in the accuracy control of the produced landslide susceptibility map. Approximately 9% of the study area was classified as high susceptibility zone. Medium, low and very low susceptibility zones covered 8, 23 and 60% of the study area, respectively. Most of the locations of the observed landslides actually fall into moderate (17.78%) and high (77.78. %) susceptibility zones of the produced landslide susceptibility map. This validates the applicability of proposed methods, approaches and the classification scheme. The high susceptibility zone is along both sides of the Akşehir Fault and at the north-eastern slope of the Sultan Mountains. It was determined that the surface area of the Harlak and Deresenek formations, which have attained lithological characteristics of clayey limestone with a broken and separated base, and where area landslides occur, possesses an elevation of 1,100–1,600 m, a slope gradient of 25°–35° and a slope aspect of 22.5°–157.5° facing slopes.     

铜川市滑坡侵蚀灾害强度分区研究

铜川市是滑坡侵蚀灾害严重的地区之一,本项研究调查了铜川市滑坡侵蚀的形成环境,分析了滑坡侵蚀的基本规律,用现场调查得到的滑坡侵蚀量作等值线图,按照等值线将铜川市滑坡侵蚀强度分为剧烈侵蚀区、强烈侵蚀区、中度侵蚀区、轻度侵蚀区、微弱侵蚀区5个等级的分区。结果表明,中等以上侵蚀区面积5 8.2 5km2,占研究区总面积的70.6%。研究区内共有滑坡12 7个,滑坡侵蚀量115 42.6万t,占重力侵蚀总量的92.9%。研究表明,铜川市滑坡侵蚀非常剧烈,必须尽快建立防灾、减灾的预警系统,加大治理对人们生命财产有威胁的滑坡侵蚀。      

Different ways of landslide geometry interpretation in a process of statistical landslide susceptibility and hazard assessment: Horná Súča (western Slovakia) case study

The article draws a comparison between different ways of landslide geometry interpretation in the scope of the statistical landslide hazard and risk assessment processing. The landslides are included as a major input variable, which are compared with all of the input parametric factors. Based on the above comparison the input data are classified and the final map of landslide susceptibility is constructed. Methodology of multivariate conditional analysis has been used for the construction of final maps. Unique condition units was developed by combination of geological map (lithological units) and slope angle map. Lithological units were derived from geological map and subsequently reclassified into 22 classes. Slope angle map was calculated from digital elevation model (contour map at a scale 1:10,000) and reclassified into nine classes. As a case study, a wide area of Horná Súča (western Slovakia) strongly affected by landsliding (predominantly made of Flysch) has been chosen. Spatial data in the form of parametric maps, as well as final statistical data set were processed in GIS GRASS environment. Four different approaches are used for landslides interpretation: (1) area of landslide body including accumulation zone, (2) area of depletion zone, (3) lines of elongated main scarps, (4) lines of main scarp upper edge. For each approach, a zoning map of landslide susceptibility was compiled and these were compared with each other. Depending on the interpretation approach, the final susceptibility zones are markedly different (in tens of percent).     

Numerical Modeling of the Seasonal Dynamic Characteristics of the Koxkar Glacier,in West Tianshan,China

Landslides commonly occurs in hilly areas and causes an enormous loss iof life and property every year. National highway-1D (NH-1D) is the only road link between the two districts (Kargil and Leh) of Ladakh region that connects these districts with Kashmir valley. The landslide failure record of the recent past along this sector of the highway is not available. The present study documents landslide susceptible zones and records occurrence of 60 landslides during the last 4 years showing an increasing trend in the occurrence of landslides over these years in this sector. The landslide susceptibility zonation map has been prepared based on the numerical rating of ten major factors viz. slope morphometry, lithology, structure, relative relief, land cover, landuse, rainfall, hydrological conditions, landslide incidences and Slope Erosion, categorised the area in different zones of instability based on the intensity of susceptibility. The landslide susceptibility map of the area encompassing 73.03 km² is divided into 150 facets. Out of the total of 150 facets, 85 facets fall in low susceptibility zone covering 43.56 km2 which constitute about 59.65% of the total area under investigation with a record of 5 landslides; 40 facets fall in the moderate susceptibility zone covering 16.94km² which constitutes about 23.19% of the study area with a record of 20 landslides; and 25 facets fall in the high susceptibility zone covering 12.53 km² which constitute about 17.15% of the study area with a record of 35 landslides. Most of the facets which fall in HSZ are attributed to slope modification for road widening.     

Landslide susceptibility analysis using probabilistic likelihood ratio model—a geospatial-based study

The crucial and difficult task in landslide susceptibility analysis is estimating the probability of occurrence of future landslides in a study area under a specific set of geomorphic and topographic conditions. This task is addressed with a data-driven probabilistic model using likelihood ratio or frequency ratio and is applied to assess the occurrence of landslides in the Tevankarai Ar sub-watershed, Kodaikkanal, South India. The landslides in the study area are triggered by heavy rainfall. Landslide-related factors—relief, slope, aspect, plan curvature, profile curvature, land use, soil, and topographic wetness index proximity to roads and proximity to lineaments—are considered for the study. A geospatial database of the related landslide factors is constructed using Arcmap in GIS environment. Landslide inventory of the area is produced by detailed field investigation and analysis of the topographical maps. The results are validated using temporal data of known landslide locations. The area under the curve shows that the accuracy of the model is 85.83%. In the reclassified final landslide susceptibility map, 14.48% of the area is critical in nature, falling under the very high hazard zone, and 67.86% of the total validation dataset landslides fall in this zone. This landslide susceptibility map is a vital tool for town planning, land use, and land cover planning and to reduce risks caused by landslides.     

山西煤矿区滑坡特征及分类

滑坡分类研究一直是滑坡研究的基础和重点。通过对山西煤矿区滑坡灾害的工程实践和大量的调查统计分析,根据滑坡地层结构、岩性特征、诱发机制及运动特征等因素将山西煤矿区滑坡归结为5种类型:顺基岩面推移-滑动型黄土滑坡;蠕滑-挤出型黄土滑坡;水浸溜滑型黄土滑坡;煤层自燃倾覆-拉裂滑移型岩质滑坡;受节理控制的蠕滑-张裂型岩质滑坡。研究结果发现:黄土滑坡滑带土一般为松散土层,岩质滑坡的滑面为软弱结构面（多为泥岩薄层）或煤线;除溜滑型黄土滑坡滑动速度较快外,其他为低速滑坡,其典型特点是历时长,滑距短,致灾范围小,但滑坡推力大,破坏力强,往往造成更大损失。该研究进一步细化了滑坡分类的内容,其成果可对山西矿区及类似滑坡地质灾害的防治提供指导。      

Landslide hazard zonation using analytical hierarchy process along National Highway-3 in mid Himalayas of Himachal Pradesh,India

Landslide zonation studies emphasize on preparation of landslide hazard zonation maps considering major instability factors contributing to occurrence of landslides. This paper deals with geographic information system-based landslide hazard zonation in mid Himalayas of Himachal Pradesh from Mandi to Kullu by considering nine relevant instability factors to develop the hazard zonation map. Analytical hierarchy process was applied to assign relative weightages over all ranges of instability factors of the slopes in study area. To generate landslide hazard zonation map, layers in geographic information system were created corresponding to each instability factor. An inventory of existing major landslides in the study area was prepared and combined with the landslide hazard zonation map for validation purpose. The validation of the model was made using area under curve technique and reveals good agreement between the produced hazard map and previous landslide inventory with prediction accuracy of 79.08%. The landslide hazard zonation map was classified by natural break classifier into very low hazard, low hazard, moderate hazard, high hazard and very high landslide hazard classes in geographic information system depending upon the frequency of occurrence of landslides in each class. The resultant hazard zonation map shows that 14.30% of the area lies in very high hazard zone followed by 15.97% in high hazard zone. The proposed model provides the best-fit classification using hierarchical approach for the causative factors of landslides having complex structure. The developed hazard zonation map is useful for landslide preparedness, land-use planning, and social-economic and sustainable development of the region.     

Landslide susceptibility mapping using GIS and weighted overlay method: a case study from North Jordan

Road instability along the Jerash–Amman highway was assessed using the weighted overlay method in Geographic Information System environment. The landslide susceptibility map was developed from nine contributing parameters. The map of landslide susceptibility was classified into five zones: very low (very stable), low (stable), moderate (moderately stable), high (unstable), and very high (highly unstable). The very high susceptibility and high susceptibility zones covered 15.14% and 31.81% of the study area, respectively. The main factors that made most parts of study area prone to landslides include excessive drainage channels, road cuts, and unfavorable rock strata such as marl and friable sandstone intercalated with clay and highly fractured limestone. Fracture zones are a major player in land instability. The moderate and high susceptibility zones are the most common in urban (e.g., Salhoub and Gaza camp) and agricultural areas. About 34% of the urban areas and 28.82% of the agricultural areas are characterized by the high susceptibility zone. Twenty percent of the Jerash–Amman highway length and 58% of the overall highway length are located in the very high susceptibility zone. The landslide susceptibility map was validated by the recorded landslides. More than 80 of the inventoried landslides are in unstable zones, which indicate that the selected causative factors are relevant and the model performs properly.     

Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas

Landslide risk assessment (LRA) is a key component of landslide studies. The landslide risk can be defined as the potential for adverse consequences or loss to human population and property due to the occurrence of landslides. The LRA can be regional or site-specific in nature and is an important information for planning various developmental activities in the area. LRA is considered as a function of landslide potential (LP) and resource damage potential (RDP). The LP and RDP are typically characterized by the landslide susceptibility zonation map and the resource map (i.e., land use land cover map) of the area, respectively. Development of approaches for LRA has always been a challenge. In the present study, two approaches for LRA, one based on the concept of danger pixels and the other based on fuzzy set theory, have been developed and implemented to generate LRA maps of Darjeeling Himalayas, India. The LRA map based on the first approach indicates that 1,015 pixels of habitation and 921 pixels of road section are under risk due to landslides. The LRA map derived from fuzzy set theory based approach shows that a part of habitat area (2,496 pixels) is under very high risk due to landslides. Also, another part of habitat area and a portion of road network (7,204 pixels) are under high risk due to landslides. Thus, LRA map based on the concept of danger pixels gives the pixels under different resource categories at risk due to landslides whereas the LRA map based on the concept of fuzzy set theory further refines this result by defining the degree of severity of risk to these categories by putting these into high and low risk zones. Hence, the landslide risk assessment study carried out using two approaches in this paper can be considered in cohesion for assessing the risks due to landslides in a region.