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基于GIS的重庆市万州区滑坡灾害危险性评价 总被引：1，自引：0，他引：1
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. 相似文献
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为了弥补滑坡灾害危险性区划研究中影响因子和等级划分的不确定性,结合前人研究成果,依据斜坡几何形态、岩性、地质构造、河流侵蚀、土地利用类型、人类工程活动、降水条件等影响因子与研究区实际已发生的滑坡灾害数之间的关系,编制重庆市万州区滑坡灾害危险性评价标准,并基于GIS技术和信息量模型法,计算滑坡评价因子的信息量,就万州区滑坡危险性进行区划,最后基于乡镇行政区对该区滑坡危险性区划进行细化。结果表明：建设用地、坡高为90～200 m的地形、1 024～1 060 mm的年降雨量以及侏罗系中统上沙溪庙组岩层等因素对万州区滑坡发生影响较大;根据滑坡灾害危险性评价标准,万州区滑坡灾害被划分为高、中、低、极低等4个危险区;应用信息量模型法得到的万州区滑坡危险性区划与实际情况比较吻合;高危险区和中危险区面积分别为564.4 km2和848.6 km2,分别占万州区总面积的16.3%和24.5%,主要分布于长江干流及支流两岸的居民相对集中区以及公路干线地段;高危险和中危险乡镇主要分布在万州区经济较为发达的长江干流两岸,尤其是左岸的黄柏乡、太龙镇、天城镇、李河镇等以及万州主城区。 相似文献
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三峡库区重庆市丰都县滑坡灾害危险性评价 总被引：6，自引：10，他引：6
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。 相似文献
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危险性评价是滑坡灾害预防与减灾工作首要解决的重要内容.在地理信息系统技术支持下, 以山地灾害频发区——小江流域作为研究对象, 选取坡度、土体粘聚力和内摩擦角这3个评价指标构建滑坡危险性分级评价指标体系, 将投影寻踪技术运用到滑坡危险性等级评价中, 对评价样本的各指标因素进行线性投影, 以最优投影方向所对应的投影特征值作为评价依据, 建立了滑坡危险性等级综合评价模型, 绘制了滑坡危险性等级分布图.结果表明: 研究区极高危险区、高危险区、中等危险区、低危险区和极低危险区的面积比例为14.28∶9.41∶69.12∶7.00∶0.19;根据所建立的5级评价指标体系对研究区60个土质滑坡点资料进行了验证, 在占研究区总面积23.69%的高、极高危险区的小范围内, 实际发生土质滑坡数量45个, 占总土质滑坡数量的75.00%;中等危险性级别以上区域拥有的土质滑坡数量占全部土质滑坡的96.67%;不同危险性级别的滑坡体积方量统计结果表明, 滑坡体积方量密度随危险性级别的提高而迅速增加.对比评价结果及实测结果可知, 投影寻踪分级结果符合实际情况, 证实了该方法的正确性, 为滑坡危险性评价提供了一条新思路. 相似文献
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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。 相似文献
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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。 相似文献
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赵伯驹李宁幸夫诚向晗 《中国地质灾害与防治学报》2023,(5):32-42
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。 相似文献
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采用层次分析法,选取了地层岩性、地质构造、地形地貌、河流、植被、降雨量和人类活动7个一级指标,以及工程地质岩组、地震密度、地震动峰值加速度、坡度、坡向、河流、植被覆盖度、年降水量和公路9个二级指标,通过构建层次结构、构造判断矩阵、层次单排序和一致性检验,确定各评价指标权重。并利用GIS空间分析功能,对各个评价因子进行综合评价,得到陕西省地震次生地质灾害危险性等级区划图。最后,对评价结果进行了验证。研究结果表明:1)陕西省地震次生地质灾害危险性等级可以划分为不危险区、低危险区、中危险区和高危险区4个等级,其中不危险区面积39766.99km~2,低危险区面积74284.39km~2,中危险区面积63636.89km~2,高危险区面积27652.87km~2,所占比例分别为19.37%,36.18%,30.99%和13.47%;2)危险性等级自北而南逐渐增加,陕北黄土高原地震次生地质灾害以中低危险为主,关中渭河平原整体危险性较小,陕南秦巴山地高危区面积最大,高危险区主要分布在陕南秦巴山地和陕北黄土高原地区,尤其是秦巴山地,需要重点防控;3)危险区空间分布具有相对集中性和局地差异性的特点;4)所选取灾害点样本的分布与危险性等级区划具有一致性,86.62%的灾害点落在危险区内,具有一定的可信度,达到了预期的区划效果。 相似文献
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文章以MAPGIS6.7、MORPAS3.0和Geodas 4.0软件为平台,综合应用信息量法、证据权法和模糊证据权法,采用两级混合的预测方法对玉林—铁山港公路沿线崩塌、滑坡地质灾害进行了危险性区划,共划分为高度危险性区、中高度危险性区、中度危险性区和轻度危险性区4级。预测结果显示:研究区崩塌、滑坡灾害危险性级主要为轻度危险等级。中高度—高度危险区范围较小,且主要分布于研究区中北部AK51、AK60~AK65和AK95~AK105路段;上述区段水系发育,沟谷较多,山坡陡峻,岩土体结构多具中厚层状坚硬、较坚硬砂岩、粉砂岩、砂砾岩夹软质泥岩、页岩岩组特征,断裂构造发育,地表残坡积层厚度大,结构松散,夏季暴雨频发,崩塌、滑坡灾害条件基本具备,易于形成和诱发;因此,应重点加强上述区段的灾害监测和防治工作。 相似文献
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Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus 总被引：1，自引：0，他引：1
D. D. Alexakis A. Agapiou M. Tzouvaras K. Themistocleous K. Neocleous S. Michaelides D. G. Hadjimitsis 《Natural Hazards》2014,72(1):119-141
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. 相似文献
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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。 相似文献
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Mountain landslide has been an environmental geological problem and occurs frequently in China, especially in the karst region
of Guizhou Province, Southwest China. The data of karst mountain landslide are collected and analysed, which occurred in the
period of 1940–2002. The collection includes 321 events in the karst region of Guizhou Province. The characteristics of mountain
landslides may be classified as two types, namely natural mountain landslides (287 events) and the other induced by human
activities (34 events). The results indicate that natural mountain landslide causes especially high damage and is still the
main type of natural hazard in the study area owing to the extremely fragile karst geological environment. 相似文献
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This paper deals with the landslide susceptibility zonation of Tevankarai Ar sub-watershed using weighted similar choice fuzzy
method in a GIS environment. There has been a rapid increase in landslide occurrences in the Kodaikkanal town and area surrounding
the town specially in the settlements around the town and road links leading to and from the town. This necessitates a detailed
study of slope instability problems in this area. It is observed that these incidences occur frequently during the monsoon
and summer showers. Rainfall is identified as the prime triggering factor. Eleven physical factors that cause instability
are identified as causative factors from the field investigations and landslide occurrences. Land use pattern, slope gradient,
curvature and aspect, weathering index which are evaluated from the weathering ratios of different chemical constituents of
the three major lithological variations, soil type, hydraulic conductivity of soil and soil thickness, geomorphology, drainage,
and lineament have been utilized to prepare the spatial variation. A weighted similar choice fuzzy model which ranks a set
of alternatives by identifying the similarity between the outcome of alternatives and outcome of ideal alternatives is used
to rank the causative factors. Each causative factor is classified into sub-categories and rated based on their effect on
stimulating the landslide event using qualitative judgment derived from field studies and landslide history. The prepared
thematic maps of causative factors are integrated, utilizing the GIS software Arcmap. The outcome has projected the low, moderate,
high, and very high landslide susceptibility zones. The high-hazard and very high-hazard areas fall in the northwestern part
characterized by croplands and agricultural plantations, while the moderate hazard zones are seen in prominent settlements
and low-hazard zones are observed in the sparse settlements and zones of less agricultural activity. The model is verified
using the relative landslide density (R) index, and the susceptibility map is found to be consistent with the mapped landslide
incidences. The results from this study illustrate that the use of weighted similar choice fuzzy method is suitable for landslide
susceptibility mapping on regional scale in growing hill towns as Kodaikkanal town. 相似文献
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金沙江干热河谷区滑坡遥感解译研究 总被引：7，自引：1，他引：7
“三江”(即金沙江、澜沧江及怒江)地区自然条件恶劣,交通不便,解决该地区水电大开发地质灾害调查中一条切实可行的方法是利用遥感。论文分析了金沙江干热河谷气候环境和地形条件的特点及他们对滑坡解译产生的影响。通过研究这一地区的滑坡在多种遥感影像上的图斑特征配合实地考察,分析并列举了干扰滑坡识别的图斑,总结出该地区的古滑坡、活动滑坡和典型滑坡的识别特征。同时对该地区滑坡不发育,所占地质灾害比例低的现象进行了分析。指出当地气候、地形、构造特征、岩土类型对滑坡发育存在的影响。为该类型地区的遥感地质调查提供借鉴。 相似文献
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《地学前缘(英文版)》2023,14(3):101541
In this study, the future landslide population amount risk (LPAR) is assessed based on integrated machine learning models (MLMs) and scenario simulation techniques in Shuicheng County, China. Firstly, multiple MLMs were selected and hyperparameters were optimized, and the generated 11 models were cross-integrated to select the best model to calculate landslide susceptibility; by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard. Using the town as the basic unit, the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways (SSPs) scenarios in each town were assessed, and then combined with the hazard to estimate the LPAR in 2050. The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment. The distribution of hazard classes is similar to susceptibility, and with an increase in precipitation, the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes. The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability, whereas the northern towns of Baohua and Qinglin are at the lowest risk class. The LPAR increased with the intensity of extreme precipitation. The LPAR differs significantly among the SSPs scenarios, with the lowest in the “fossil-fueled development (SSP5)” scenario and the highest in the “regional rivalry (SSP3)” scenario. In summary, the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability. The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective. 相似文献
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滑坡预警判据初步研究--以三峡库区为例 总被引：17，自引：2，他引：15
在三峡库区典型地段滑坡灾害调查评价和统计分析的基础上,结合典型滑坡变形发展的阶段性变形现象、标志和临界诱发因素分析,初步提出3个层次的滑坡预警预报判据27条,包括:(1)滑坡空间预测识别判据11条,主要用于滑坡或潜在危岩体空间识别和危险性区划,是滑坡空间预测的基本判据;(2)滑坡状态判据7条,主要用于滑坡单体稳定性评价的亚临界-临界状态预警判据,是滑坡状态预警判据系统的重要组成部分;(3)滑坡临界时间预报判据9条,主要用于单体滑坡剧烈变形或临滑预报,是滑坡时间预报研究的关键判据. 相似文献
19.
以穿越汶川震区的成兰铁路龙门山关键段为例, 探索提出了强震扰动背景下重大工程场区多尺度滑坡危险性评估方法。利用信息量模型反演评估了汶川地震诱发的同震滑坡空间分布特征, 以此为前提开展了区域和局地两种空间尺度的滑坡危险性预测评估。在区域廊带尺度上, 分别利用可能最大降雨量预测方法和信息量模型, 进行了日超越概率10%的最大降雨量时空分布预测及其诱发滑坡的危险性评估; 同时, 结合地震危险性区划成果, 开展了50年超越概率10%的基本地震动诱发滑坡的危险性评估。在局地场站尺度上, 利用基于崩塌运动过程模拟的Rockfall Analyst软件, 开展了柿子园大桥周边崩塌运动学特征(Runout)模拟和危险性评估。滑坡和崩塌危险性评估的结果分别为铁路规划选线和场站防护设计提供了不同尺度的地质安全依据。 相似文献
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牛眠沟研究区位于2008-05-12汶川大地震线性震源的南端,受强烈地震力作用,区内山体遭受严重破坏,发生多处滑坡和泥石流灾害。根据已建立的暴雨滑坡、泥石流预测概念模型,暴雨滑坡、泥石流预测可视为判断滑坡形成的地质环境和确定触发滑坡的降雨特征。查明研究区地质环境及灾害特征,确定了产生滑坡、泥石流的必要地质环境因子,以数字滑坡技术获取这些因子数据,代入模型,即可评价研究区各处、各沟谷发生滑坡、泥石流的危险程度;与相似地质环境及气候条件进行类比,确定研究区触发滑坡、泥石流的降雨特征及降雨量阈值后,最终建立暴雨滑坡、泥石流预测模型。据此模型进行研究区暴雨滑坡、泥石流预测,实地验证表明滑坡、泥石流发生位置的准确率>90%。 相似文献