基于贡献权重叠加法的滑坡风险区划

贡献权重叠加法是对滑坡本底因子和承灾体因子在滑坡发育中的贡献率进行统计后,通过贡献率均值化、规一化处理,利用权重转换模型计算出每一个因子内部的权重——自权重和因子相互之间的权重——互权重。将滑坡因子、承灾体因子和两者的自权重、互权重分别相乘叠加,得到滑坡危险度和易损度区划结果,再将2项结果相乘得出滑坡风险区划结果。     

基于贡献权重迭加法的滑坡风险区划

贡献权重迭加法是对滑坡本底因子和承灾体因子在滑坡发育中的贡献率进行统计后,通过贡献率均值化、规一化处理,利用权重转换模型计算出每一个因子内部的权重——自权重W和因子相互之间的权重——互权重W＇。将滑坡因子、承灾体因子和两者的自权重、互权重分别相乘迭加,得到滑坡危险度和易损度区划结果,再将2项结果相乘得出滑坡风险区划。     

滑坡危险度区划方法及其应用

在滑坡研究的基础上总结了滑坡危险度区划的研究方法。建立了综合因素分析和本底因素评价的指标体系,提出了综合因素叠加法、本底因素贡献权重叠加法和本底因素模糊判别推理法的区划模型,介绍了这些方法的应用及试验结果。还对滑坡危险度区划研究中存在的3个主要问题进行了讨论：评价指标数量选择、最佳权重确定方法和危险性等级划分的标准。     

关于地质灾害孕灾因子权重确定的探讨

地质灾害易发区划模型中,不同地区孕灾因子权重不同。因子权重的确定、求解权重的准确性将直接关系到区划结果的可靠度。本文根据地质灾害点在不同孕灾因子分区中的分布频率,推出不同孕灾因子对地质灾害发育的贡献率的相对大小。不同因子对地质灾害发育的贡献率实际上就是各因子在地质灾害易发模型中的权重,因此通过以上分析可得出不同孕灾因子的相对权重,再利用层次分析法(AHP法)得出孕灾因子的权重。通过统计分析得出各因子相对权重的方法弥补了层次分析法确定权重的人为随意性,提高了区划的准确度。     

杭州市滑坡地质灾害危险性区划与评价

基于证据权法构建滑坡地质灾害评价模型,进行杭州市滑坡地质灾害危险性区划研究。主要数据源包括1930－2009年杭州市域采集到的1 905个地质灾害个例以及杭州市地质图、土地利用数据及数字高程模型（DEM）等。利用Arcgis空间分析及信息提取功能,筛选强降水、地层岩性、坡度、坡向、坡高、河网与道路缓冲等证据因子,并运用证据权法客观确定各因子权重, 最后通过Arc-WofE扩展模块对多种优选因子的叠加,计算任意格网单元的滑坡发生概率,实现对潜在滑坡点位的空间预测。经分离样本法验证,区划准确率为88.3%,分析结果与现有滑坡的分布情况比较吻合。据此表明证据权法在多指标评价及其权重确定等方面具有普适性,值得在滑坡地质灾害危险性区划等方面推广应用。     

汶川地震灾区滑坡风险区划研究

地震滑坡是在地震瞬间诱发的滑坡灾害。本文讨论了汶川地震灾区滑坡风险区划与常规滑坡风险区划的区别,认为地震滑坡风险区划应该在危险度区划中增加与地震相关的指标因子,如滑坡震中距和滑坡断层距。从而反映地震动能量对地震滑坡发育的贡献作用。而易损度区划中是难以体现地震因素作用的,这里采用滑坡密度、人口密度、道路密度、建筑物密度、耕地密度这5个指标进行易损度评价。最后采用权重叠加法进行了汶川地震极震区10个县市(面积26175.77km2)的滑坡风险区划,其中高、较高风险区分别占全区面积的9.03%和14.61%。说明震后灾区依然存在一定的滑坡风险。汶川地震极震区中,北川、青川、都江堰、彭州4地应该成为滑坡风险防御的主要地区。对滑坡风险区划结果进行了实地抽样检验,证明区划结果基本符合汶川极震灾区的情况。由此可见,本文介绍的地震滑坡风险区划方法是可靠的。     

湖南雪峰山地区降雨型滑坡灾害敏感性区划

雪峰山地区是湖南省降雨型滑坡灾害较为发育的地区之一,滑坡灾害给该地区社会及经济发展造成严重影响,给人民生命财产造成严重损失.本文选择影响滑坡发生的关键地质因子,即坡向、高程、工程岩组、斜坡类型和坡度等5个因子,通过确定性系数（CF）与层次分析法（AHP）的融合,解决评价中各因子指标的排序赋值和各评价因子叠加的权重问题.在给定因子权重的基础上,采用因子权值与因子赋值相乘后相加的方法,求得雪峰山地区降雨型滑坡综合敏感度值,并根据敏感性指标对研究区进行敏感性区划.     

基于证据权与Logistic回归模型耦合的滑坡易发性评价

滑坡灾害易发性研究对地质灾害风险管理及减灾防灾有着重要的现实意义。目前,多模型耦合的评价方法在国内外应用较为广泛,但将证据权与其他方法相结合用于滑坡易发性评价的研究却较少。鉴于此,本文以浙江省永嘉县为例进行滑坡易发性评价,选取高程等9个因素作为滑坡易发性的评价因子。利用证据权模型计算得到的证据权对比度与分级栅格比、滑坡栅格比进行比较,实现各评价因子状态分级处理;再运用Logistic回归模型算得各评价因子的权重。综合两种模型确定的状态分级权重和评价因子权重,基于GIS的栅格运算功能得到各评价单元的滑坡发生概率,实现研究区滑坡易发性分级区划。研究结果表明,证据权与Logistic回归耦合模型的评价结果的合理性与精确度均优于两种单一模型;且极高易发区和高易发区主要分布在水系延展区、断层密集区、岩组软弱区。研究结果对滑坡灾害风险管理及城市防灾规划具有一定的参考价值。     

基于贡献率权重法的区域滑坡影响因子敏感性分析

滑坡影响因子是区域滑坡危险性评价的基础,而因子的敏感性直接反应评价过程中权重大小,因此因子敏感性的精度将影响着评价结果的精度。本文以平昌县滑坡灾害为例,选取坡度、地层、高差、高程、坡形五个因子作为滑坡灾害的敏感性分析因子,采用贡献率权重法对研究区滑坡灾害影响因子的内部敏感性及因子间敏感性进行分析,该评价方法结构简单,不受地域限制,能客观的反应出各评价因子间以及因子内对地质灾害的敏感性。分析结果显示:选取的5个指标敏感性大小依次为:坡形坡度地层高差高程;在各评价指标内部中,坡度10°~30°、侏罗系下统蓬莱镇组上段地层、高差4.94~12.36 m、高程300~800 m、凸形与直线形坡是滑坡发生的高敏感区间。     

加权信息量模型在滑坡易发性评价中的应用以湖北省恩施市为例

信息量模型物理意义明确、操作简单,在滑坡易发性评价中得到广泛应用,但该模型未考虑各评价因子的权重。本文提出了基于层次分析法的加权信息量模型,并以湖北省恩施市为例,采用基于GIS的空间分析方法,分析了地形、断裂、水系、工程地质岩组等因子对研究区滑坡的影响,利用加权信息量将研究区划分为高易发区、中易发区、低易发区和极低易发区。     

降雨型滑坡危险性区划方法

降雨诱发的滑坡等地质灾害分布广、危害大,开展地质灾害危险性区划是减轻地质灾害损失的有效途径之一。以湖南省为例,根据地质灾害调查成果,选取3 412处滑坡,分析了区域降雨型滑坡的发育特点和分布规律,建立了危险性区划指标体系,利用不确定性推理中的确定性系数法,对滑坡与工程地质岩组、坡度、坡向、植被和年均降水量5个评价因子进行了相关性分析,建立了Logistic多元回归模型;采用不规则网格单元划分方法,形成了湖南省滑坡灾害危险性区划图。     

基于逻辑回归模型和确定性系数的崩滑流危险性区划

崩滑流是崩塌、滑坡和泥石流地质灾害的总称。本文根据逻辑回归模型和贵州省崩滑流地质灾害发生的确定性系数CF,统计贵州省内崩滑流发生概率与其影响因子之间的函数关系; 并利用GIS技术编制贵州省崩滑流地质灾害危险性区划图。首先根据影响因子子集中已发崩滑流灾害面积和影响因子子集面积来计算崩滑流地质灾害发生的确定性系数CF; 其次将灾害是否发生作为因变量,影响因子子集发生崩滑流地质灾害的确定性系数CF作为自变量,应用逻辑回归模型统计分析它们之间的函数关系; 然后利用GIS技术计算研究区内各独立属性单元发生崩滑流地质灾害的概率p,按p值10等分标准将研究区划分为10个危险性等级区,并绘制贵州省崩滑流地质灾害危险性区划图; 最后用已发崩滑流地质灾害的分布数据来检验危险性区划的效果。研究结果表明:本文根据逻辑回归模型和崩滑流地质灾害发生的确定性系数CF,将贵州省分为Ⅰ～Ⅹ的10个崩滑流地质灾害危险性等级区与实际情况基本符合,能够良好地反映贵州省境内发生崩滑流地质灾害的难易程度。     

Regional-scale landslide activity and landslide susceptibility zonation in the Nepal Himalaya

Landslide susceptibility zonation mapping is a fundamental procedure for geo-disaster management in tropical and sub-tropical regions. Recently, various landslide susceptibility zonation models have been introduced in Nepal with diverse approaches of assessment. However, validation is still a problem. Additionally, the role of various predisposing causative parameters for landslide activity is still not well understood in the Nepal Himalaya. To address these issues of susceptibility zonation and landslide activity, about 4,000 km² area of central Nepal was selected for regional-scale assessment of landslide activity and susceptibility zonation mapping. In total, 655 new landslides and 9,229 old landslides were identified with the study area with the help of satellite images, aerial photographs, field data and available reports. The old landslide inventory was “blind landslide database” and could not explain the particular rainfall event responsible for the particular landslide. But considering size of the landslide, blind landslide inventory was reclassified into two databases: short-duration high-intensity rainfall-induced landslide inventory and long-duration low-intensity rainfall-induced landslide inventory. These landslide inventory maps were considered as proxy maps of multiple rainfall event-based landslide inventories. Similarly, all 9,884 landslides were considered for the activity assessment of predisposing causative parameters. For the Nepal Himalaya, slope, slope aspect, geology and road construction activity (anthropogenic cause) were identified as most affective predisposing causative parameters for landslide activity. For susceptibility zonation, multivariate approach was considered and two proxy rainfall event-based landslide databases were used for the logistic regression modelling, while a relatively recent landslide database was used in validation. Two event-based susceptibility zonation maps were merged and rectified to prepare the final susceptibility zonation map and its prediction rate was found to be more than 82 %. From this work, it is concluded that rectification of susceptibility zonation map is very appropriate and reliable. The results of this research contribute to a significant improvement in landslide inventory preparation procedure, susceptibility zonation mapping approaches as well as role of various predisposing causative parameters for the landslide activity.     

模糊综合评判法分析地震滑坡启程能量转换

地震滑坡启程能量转化分析对于后期滑坡动力学研究极为重要,因其影响因素较多,具有模糊性,目前还没有准确的定量计算公式。模糊综合评判法分析模糊问题具有明显的优势,能够综合考虑各种因素给出总体评价。选取地震加速度、岩体结构类型、控制性结构面特征、岩体完整程度、地层岩性、地下水、不利结构面与临空面的夹角7个因素作为地震滑坡启程剧动能量转换大小划分的主要因素,详细分析各个因素对能量转化的影响。采用逻辑分区法确定隶属函数,应用模糊层次分析法（FAHP）确定各因素的权重。在此基础上,运用模糊数学综合评判方法得出能量转化率等级,半定量地确定能量转化率大小。以东河口地震滑坡为例,应用模糊综合评判法对其启程能量转换分析结果客观合理,表明该方法是科学可行的,在同类理论研究中可以借鉴。     

Rainfall event-based landslide susceptibility zonation mapping

Landslide susceptibility assessment is a major research topic in geo-disaster management. In recent days, various landslide susceptibility and landslide hazard assessment methodologies have been introduced with diverse thoughts of assessment and validation method. Fundamentally, in landslide susceptibility zonation mapping, the susceptibility predictions are generally made in terms of likelihoods and probabilities. An overview of landslide susceptibility zoning practices in the last few years reveals that susceptibility maps have been prepared to have different accuracies and reliabilities. To address this issue, the work in this paper focuses on extreme event-based landslide susceptibility zonation mapping and its evaluation. An ideal terrain of northern Shikoku, Japan, was selected in this study for modeling and event-based landslide susceptibility mapping. Both bivariate and multivariate approaches were considered for the zonation mapping. Two event-based landslide databases were used for the susceptibility analysis, while a relatively new third event landslide database was used in validation. Different event-based susceptibility zonation maps were merged and rectified to prepare a final susceptibility zonation map, which was found to have an accuracy of more than 77 %. The multivariate approach was ascertained to yield a better prediction rate. From this study, it is understood that rectification of susceptibility zonation map is appropriate and reliable when multiple event-based landslide database is available for the same area. The analytical results lead to a significant understanding of improvement in bivariate and multivariate approaches as well as the success rate and prediction rate of the susceptibility maps.     

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.     

Inclusion of earthquake strong ground motion in a geographic information system-based landslide susceptibility zonation in Garhwal Himalayas

Garhwal Himalayas are seismically very active and simultaneously suffering from landslide hazards. Landslides are one of the most frequent natural hazards in Himalayas causing damages worth more than one billion US$ and around 200 deaths every year. Thus, it is of paramount importance to identify the landslide causative factors to study them carefully and rank them as per their influence on the occurrence of landslides. The difference image of GIS-derived landslide susceptibility zonation maps prepared for pre- and post-Chamoli earthquake shows the effect of seismic shaking on the occurrence of landslides in the Garhwal Himalaya. An attempt has been made to incorporate seismic shaking parameters in terms of peak ground acceleration with other static landslide causative factors to produce landslide susceptibility zonation map in geographic information system environment. In this paper, probabilistic seismic hazard analysis has been carried out to calculate peak ground acceleration values at different time periods for estimating seismic shaking conditions in the study area. Further, these values are used as one of the causative factors of landslides in the study area and it is observed that it refines the preparation of landslide susceptibility zonation map in seismically active areas like Garhwal Himalayas.     

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.