基于信息量模型与Logistic回归模型耦合的地质灾害易发性评价

汶川地震在区内诱发了大量滑坡、崩塌等地质灾害,且孕育了大量松动岩体,这些松动岩体在降雨等因素诱发下将会产生大量次生地质灾害,危险性极大。故此对汶川县进行地质灾害易发性评价具有十分重要的现实意义。本文选取高程、坡度、坡向、起伏度、沟谷密度、工程岩组、断层、水系、道路9个影响因子,基于GIS的栅格数据模型,采用信息量模型、Logistic回归模型以及两种模型耦合分析进行地质灾害易发性评价。研究结果表明,采用耦合模型较信息量或Logistic单一模型评价结果更加合理、精度更高;易发性高与较高区域多集中于水系延展区域与断层集中区域。所计算得出的易发性分区结果与研究区实际情况相近,能在地质灾害风险评价中起到重要参考作用。     

浅谈地质科技档案资料的编研与开发利用

县城的快速发展日益受到地质灾害的显著制约,进行地质灾害危险性评价是县城可持续发展的客观需要。以甘肃省榆中县为例,建立了地质灾害危险性评价的3级模糊数学模型和全面详细的评价指标体系,查明了存在的主要地质灾害类型有滑坡、崩塌、泥石流及不稳定斜坡等,进行了地质灾害危险性3级模糊综合评价。结果表明,按照不易发、低易发、中易发和高易发4个级别,榆中县为地质灾害高易发区,该结果与实际情况较为一致。说明多级模糊综合法是实现地质灾害危险性评价由单因子定性评判过渡为多因子定量综合评判的有效途径。     

综合统计模型和物理模型的地质灾害精细评估——以福建省龙山社区为例

地质灾害易发性和危险性评价对象相同但评价内容有差异,即两者表达地质灾害的时间、空间和强度信息各有不同。本文将崩塌滑坡易发性中的统计模型和危险性评价中的物理模型进行结合,综合统计模型客观预测空间位置信息的优点以及物理模型模拟包含地质灾害发生机制的优势,弥补了区域统计模型无法预测灾害强度信息的不足,也对物理模型模拟的空间位置进行了有效的控制和修正,进而完成区域崩塌滑坡的易发性和危险性等级综合分析,实现对区域崩塌滑坡潜在高风险位置的精细评估。本文以福建省福鼎市龙山社区为例,利用野外获取的高清影像、地形、钻孔和地质灾害等数据,通过综合统计模型评价和物理模型危险性评估,完成潜在高风险位置的精细化分析。研究结果表明:需要进行重点排查治理的区域约占社区附近山体总面积的26.92%;研究区域内需要进行集中排查与治理的区域有5个,其中3个区域需要进行重点治理,其潜在高风险区域与野外地质灾害调查区域隐患点吻合;5个高风险区域直接对180幢左右楼房（约360余户居民）的安全构成威胁,该评估将野外调研中划定的大范围高风险区域精细化处理,并验证了该评价方法体系的可行性。该评价方法体系为区域崩塌滑坡地质灾害精细化排查和治理提供了工作思路和指导。     

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。     

钒矿带矿区地质灾害危险性评价——以陕西山阳-商南钒矿带中村镇钒矿开采区为例

在查明地质灾害孕灾背景、发育现状、矿区开采现状的基础上,基于定性结合定量的评价方法,开展了矿区地质灾害危险性评价.基于评价结果和野外调查情况,总结采矿活动对矿区主要地质灾害的影响.主要成果如下：1）总结了研究区地质灾害的发育及分布特征;2）综合分析矿区孕灾环境及地质灾害致灾因子,构建了研究区危险性评价指标体系,以ArcGIS为工作平台,以斜坡单元为最小评价单元,进行了由地质灾害易发性到地质灾害危险性的评价;3）针对评价结果,理论分析了采矿活动对滑坡、崩塌、泥石流及塌陷等灾害发生的影响方式.     

钒矿带矿区地质灾害危险性评价——以陕西山阳-商南钒矿带中村镇钒矿开采区为例

在查明地质灾害孕灾背景、发育现状、矿区开采现状的基础上，基于定性结合定量的评价方法，开展了矿区地质灾害危险性评价.基于评价结果和野外调查情况，总结采矿活动对矿区主要地质灾害的影响.主要成果如下：1）总结了研究区地质灾害的发育及分布特征；2）综合分析矿区孕灾环境及地质灾害致灾因子，构建了研究区危险性评价指标体系，以ArcGIS为工作平台，以斜坡单元为最小评价单元，进行了由地质灾害易发性到地质灾害危险性的评价；3）针对评价结果，理论分析了采矿活动对滑坡、崩塌、泥石流及塌陷等灾害发生的影响方式.     

陕北黄土崩塌灾害风险评价指标体系构建

在滑坡的易发性、危险性和风险评价中,评价指标的选取和定量化是非常关键的。目前国内外采取的主要方法是利用GIS工具提取地形、岩性、距河流或断层带的距离、土地类型、植被、降雨、河流密度等因子进行分析和计算。这些指标在滑坡易发性和危险性区划中得到了广泛应用并取得了丰硕的成果,但也有一些局限性,具体表现在3个方面:一是不能针对不同的滑坡类型提供不同的评价指标体系;二是提取的这些因子中在区域上有些是共性因子,如岩性、降雨等;三是尚未建立一个完整的风险评价指标体系。本次研究专门针对陕西北部地区广泛发育的一种称之为"黄土崩塌"的滑坡类型,运用国际上流行的滑坡风险管理理论,确定其风险评价总体指标体系;基于大量野外调查数据的统计规律,分析了黄土崩塌危险性的主要来源和影响危害性的主要因素,从失稳可能性评价指标、崩塌强度评价指标、承灾体评价指标和易损性评价指标4个方面共确定了16大类36个评价指标。该指标体系的构建可为进一步的陕北黄土地区斜坡单元崩塌灾害风险评价提供基础。     

基于 GIS和 AHP的安康市滑坡地质灾害危险性评估

安康市滑坡崩塌频繁发生,对当地造成了不可估量的损失。以安康市地震小区划为依托,对当地滑坡地质灾害的易发性进行研究。在研究区进行野外踏勘和搜集资料的基础上,借助magis和arcgis平台强大的绘图、分析功能,运用层次分析法对滑坡灾害因子进行加权叠加计算,绘制滑坡灾害危险性区划图。区划结果分为四个等级：无危险区、低危险区、中危险区、高危险区。无危险区、低危险区滑坡灾害易发性较低,为适宜城市规划和项目实施工作地带,中危险区、高危险区则要加以治理以减少滑坡地质灾害对居民生命和财产的威胁。     

陕西省地质灾害易发性综合评价方法初探

陕西省的地质灾害主要包括滑坡、崩塌、泥石流、地面塌陷、地裂缝及地面沉降。论文在总结陕西省107个县（市）地质灾害调查与区划工作的基础上,建立了陕西省地质灾害易发性综合评价指标体系。针对不同灾种选择了25个评价指标作为其易发性的主要影响因素。使用专家——AHP定权法确定各影响因素的权重,并基于GIS构建了综合评价数学模型——综合指数模型,将各指标因子图层按权重进行代数叠加运算,计算出全省地质灾害易发性综合指数。然后根据综合指数的大小,将陕西省地质灾害易发程度划分为高易发、中易发、低易发和非易发四级区。     

基于GIS汕头潮阳区崩塌、滑坡地质灾害危险性评价

以潮阳区1:5万地质灾害详细调查数据为基础,选取地质灾害点坡度、坡向、地形起伏度、工程地质岩组、地质构造、土地利用类型等6个因素评价指标,采用信息量法获取研究区易发性,基于GIS空间分析功能将10年一遇降雨工况和易发性分析计算,得出地质灾害危险性分区图。研究区综合地质灾害高危险区面积明显大于单灾种评价结果,高危险区主要位于崩塌、滑坡较发育的碎裂岩区域;对提高区域地质灾害风险预测能力及综合防治水平具有实际意义。     

Landslide hazard zoning along Himalayan Kaghan Valley of Pakistan��by integration of GPS, GIS, and remote sensing technology

This paper presents a methodology for developing a landslide hazard zonation map by integration of global positioning system (GPS), geographic information system (GIS), and remote sensing (RS) for Western Himalayan Kaghan Valley of Pakistan. The landslides in the study area have been located and mapped by using GPS. Eleven causative factors such as landuse, elevation, geology, rainfall intensity, slope inclination, soil, slope aspect, distances from main road, distances from secondary roads, and distances from main river and those from trunk streams were analyzed for occurrence of landslides. These factors were used with a modified form of pixel-based information value model to obtain landslide hazard zones. The matrix analysis was performed in remote sensing to produce a landslide hazard zonation map. The causative factors with the highest effect of landslide occurrence were landuse, rainfall intensity, distances from main road, distances from secondary roads, and distances from main river and those from trunk streams. In conclusion, we found that landslide occurrence was only in moderate, high, or very high hazard zones, and no landslides were in low or very low hazard zones showing 100% accuracy of our results. The landslide hazard zonation map showed that the current main road of the valley was in the zones of high or very high hazard. Two new safe road routes were suggested by using the GIS technology.     

Landslide hazard mapping along national highway-154A in Himachal Pradesh,India using information value and frequency ratio

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “slope, aspect, relative relief, soil, curvature, Land Use and Land Cover (LULC), lithology, drainage density, and lineament density” were selected for landslide hazard mapping based on landslide inventory. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard.” The results from these two methods have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.     

多源遥感数据支持下区域滑坡灾害风险评价

滑坡风险管理是防灾减灾的有效途径之一,而灾害风险评价是风险管理的基础和依据。以三峡库首区为研究区、多源遥感影像为主要数据源,利用立体像对技术及光谱分析等方法快速提取地形地貌、地表覆被、地质及水文条件等滑坡孕灾环境信息,应用随机森林模型分析区域滑坡危险性;采用面向对象方法建立典型承灾体识别规则,快速提取建筑物及交通道路等信息,综合分析滑坡危险性及承灾体信息,以实现区域滑坡灾害风险评价。结果显示:高风险区面积为41 km²,约占研究区面积的9%,主要集中于人口聚集的城镇和交通建设用地等经济价值大的地区。其评价结果与野外实地调查情况基本吻合。     

Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus

This study considers the impact of landslides on transportation pavements in rural road network of Cyprus using remote sensing and geographical information system (GIS) techniques. Landslides are considered to be one of the most extreme natural hazards worldwide, causing both human losses and severe damages to the transportation network. Risk assessment for monitoring a road network is based on the combination of the probability of landslides occurrence and the extent and severity of the resultant consequences should the disasters (landslides) occur. Factors that can trigger landslide episodes include proximity to active faults, geological formations, fracture zones, degree and high curvature of slopes, water conditions, etc. In this study, the reliability and vulnerability of a rural network are examined. Initially, landslide locations were identified from the interpretation of satellite images. Different geomorphological factors such as aspect, slope, distance from the watershed, lithology, distance from lineaments, topographic curvature, land use and vegetation regime derived from satellite images were selected and incorporated in GIS environment in order to develop a decision support and continuous landslide monitoring system of the area. These parameters were then used in the final landslide hazard assessment model based on the analytic hierarchy process method. The results indicated good correlation between classified high-hazard areas and field-confirmed slope failures. The CA Markov model was also used to predict the landslide hazard zonation map for 2020 and the possible future hazards for transportation pavements. The proposed methodology can be used for areas with similar physiographic conditions all over the Eastern Mediterranean region.     

基于GIS技术的区域滑坡灾害危险性预测

基于GIS技术,利用信息量模型开展区域滑坡灾害危险性预测研究,编制滑坡灾害易发分区图,为滑坡灾害的风险预测及实时预警预报提供基础资料。以浙江省永嘉县为例,利用MAPGIS二次开发得到的信息量专业模块,结合永嘉县历史滑坡灾害和2004年以来新发生的灾害点,分别评价了研究区的历史滑坡灾害危险性和现状滑坡灾害危险性;提出用历史滑坡灾害危险性图件结合新发生的灾害点来验证评价模型;将历史灾害点和新灾害点结合生成滑坡灾害危险性预测图件的预测过程;研究成果经在永嘉县的实际验证分析,2004年后3次台风期间（2004年的“云娜” 台风,2005年的“海棠”和“麦莎”台风）发生的有准确地点的滑坡灾害点全部位于滑坡灾害易发区内,表明采用的模型具有较好的实用性和可靠性;采用历史统计和快速聚类相结合的方法进行危险性等级的划分,克服了前人研究工作中人为划分易发区的缺陷,更科学、客观。     

Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.     

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.     

基于RS与GIS的层次分析法在滑坡危险性评估中的应用——以四川宣汉天台乡滑坡为例

基于遥感(RS)和地理信息系统(GIS)技术,采用多层次分析(AHP)法,以四川宣汉天台乡为研究区,根据该区实际情况,选取线性构造、道路、土地利用、坡度、坡向5种影响滑坡灾害发生的因素作为评价因子,进行区域滑坡危险性评估。在ArcGIS的空间分析环境中运行权重叠加,把研究区划分成滑坡极易发生区、易发生区、一般发生区、可能发生区、难发生区和极难发生区。通过实地调查和与研究区的滑坡灾害实证研究结果进行比较,发现评估结果与实际状况较为吻合,研究方法能够准确地评估区域滑坡灾害危险性的程度。     

基于数值模拟的城镇地质灾害危险性评价方法

定量计算城镇尺度地质灾害不同降雨强度下的危险性是地质灾害风险评价中的难点。以红层地区群发性浅层滑坡链式灾害为研究对象,探索一种新的城镇尺度下的地质灾害危险性量化评价方法,为城镇地质灾害风险评价奠定基础。通过查询喜德县米市河区域不同降雨频率下降雨参数,统计分析国家雨量站数据及近50 a的18场群发性地质灾害降雨历时、雨型分布特征。以土层厚度、植被覆盖度及地形数据处理为基础,基于STEM TRAMM数值计算方法及降雨分布曲线计算城镇地质灾害危险性,绘制研究区地质灾害危险性评价图。通过遥感解译数据、地面调查数据及灾害数据库数据与数值计算结果对比,表明应用降雨特征统计及STEM TRAMM数值计算方法精细化评价红层地区城镇地质灾害危险性具有良好的适应性、便捷性及科学性,可为其他不同孕灾背景下的城镇地质灾害危险性评价提供思路。     

Application of a RS- and GIS-based semi-quantitative approach (analytical hierarchy process – AHP) in landslide hazard risk assessment of the Shivkhola Watershed,Darjiling Himalaya

The present study deals with the application of analytical hierarchy process to prepare landslide hazard risk map of the Shivkhola Watershed applying remote sensing and geographic information system (GIS). Firstly, to integrate all the required thematic data layers and to prepare landslide susceptibility map, prioritised class rating value and prioritised factor rating value were obtained by developing couple-comparing matrix with a reasonable consistency and with the help of MATLAB software after Saaty. Three important risk factor/element maps, that is, weighted land use/land cover map, road contributing area map and settlement density map, were developed and their weighted linear combination was performed to prepare landslide risk exposure map. Then by integrating landslide susceptibility map and landslide risk exposure map, a classification was incorporated on ARC GIS Platform to prepare landslide hazard risk map. To evaluate the validity of the landslide hazard risk map, probability/chance of landslide hazard risk event has been estimated by means of frequency ratio between landslide hazard risk area (%) and number of risk events (%) for each landslide hazard risk class. Finally, an accuracy assessment was also made on ERDAS Imagine (8.5) which depicts that the classification accuracy of the landslide hazard risk map was 92.89 with overall Kappa statistics of 0.8929.