昌马断裂带地震滑坡的展布特征

根据大量的野外地质调查和测量资料分析，讨论了地震滑坡沿昌马断裂带走向和倾向的展布特征。研究认为昌马断裂带地震滑坡主要发生在山坡坡度３０°－５０°的部位和山坡地形高差１００－３００ｍ的部位；地震滑坡规模、数量的分布特征与断裂活动强度的分布变化有密切的关系，这是地震滑坡与降水滑坡、人为滑坡和融冻滑坡的最大区别；最后讨论了地震滑坡最大水平滑距的规律，对地震滑坡灾害预测有很现实的意义。     

黑方台黄土滑坡类型与发育规律

20世纪60年代末期,为了安置刘家峡、盐锅峡库区移民,在黑方台建成了提水灌溉工程,造成地下水位上升,诱发了大量黄土滑坡.作者于2006-04～2007-09先后对黑方台黄土滑坡进行了野外调查.利用IKONOS影像对黄土滑坡进行了遥感解译,将其与研究区数字高程模型(DEM)进行叠加再现了滑坡场景.基于以上工作,首先对黑方台黄土滑坡进行了较为系统的分类,包括黄土泥流、黄土滑动、黄土-泥岩接触面滑坡、黄土-泥岩顺层滑坡和黄土-泥岩切层滑坡.黄土泥流集中发育于野狐狗北部凹地形处;黄土-泥岩滑坡受基岩倾向控制,分布于坡向150°～200°的塬边地段.农业灌溉补给地下水的增湿、软化作用是黑方台黄土滑坡的根本诱发原因.对黑方台黄土滑坡机制的研究进行了展望.     

基于InSAR技术的秦岭南部略阳县潜在滑坡灾害识别研究

秦岭山区因构造活动、人类活动、气候变化等多重因素作用而面临较高的地质灾害风险,由于地形高差大、坡度陡,植被覆盖率高,滑坡灾害识别调查难度高,急需发展先进的地质灾害监测识别技术体系,提升高植被覆盖山区地质灾害隐患详细调查识别能力。不同的InSAR技术和SAR数据有各自的优势,单一InSAR技术难以在高植被覆盖山区进行区域变形监测和地质灾害隐患识别。本研究结合多种InSAR技术和不同波段SAR数据的探测优势,对秦岭南部山区略阳县城关镇的110 km~2范围进行对地观测,综合光学遥感解译和野外调查,识别出滑坡地质灾害隐患点共52处。研究表明:(1)在高植被覆盖山区,D-InSAR技术和L波段SAR数据的应用,能够提升识别高植被覆盖山区潜在滑坡位置和范围的效率。而时序InSAR技术和Sentinel数据可应用于典型灾害点时间变形模式分析。(2)略阳县滑坡主要为黄土滑坡、堆积层滑坡、黄土基岩滑坡三类;不稳定斜坡主要有陡峭风化基岩不稳定斜坡、不稳定人工边坡,破坏形式主要为基岩崩塌、剥坠落及黄土斜坡崩滑、泥流等;本研究所识别的潜在地质灾害可为略阳县防灾减灾工作提供数据支持,提出的InSAR潜在地质灾害早期识别方法体系可为秦岭及类似高植被覆盖山区地质灾害监测识别提供方法参考。     

地块质量特征对西南山区梯田撂荒的影响——以贵州剑河县白都村为例北大核心CSCDCSSCI

为分析西南山区梯田撂荒地块质量特征及影响因素,厘清山区梯田撂荒与可持续利用机制,本文以贵州省剑河县白都村为例,综合运用农户调查数据与无人机高分辨率影像数据探讨梯田的撂荒规模、空间分布情况及地块质量特征;构建二元Logistic回归模型,对影响梯田撂荒的各地块质量因素作用大小进行定量分析。结果表明:①白都村样本农户的梯田面积为62.518 hm^(2),多集中分布于耕作高差、坡度和耕作距离较大区域,其撂荒面积为21.354 hm^(2),撂荒率为34.16%。②梯田的地块质量因素对其撂荒的贡献程度表现为:灌溉条件>动力使用状况>田埂坍塌状况>耕作面积>综合地形条件,其中灌溉条件、动力使用状况、耕作面积与梯田撂荒均呈负相关,田埂坍塌状况和综合地形条件与梯田撂荒呈正相关。研究结果对于推进西南山区梯田的可持续利用与管理具有重要的理论及实践意义。     

芦山地震重灾区崩塌滑坡易发性评价

2013-04-20 T08:02,四川省芦山县发生7.0级大地震,地震诱发了大量的次生山地灾害.在芦山、宝兴、天全三个地震重灾县6651.35 km2的区域内,采用震后遥感影像解译并结合野外调查的方法,共解译出1379处崩塌(含落石)滑坡.应用GIS技术,建立了芦山地震诱发崩塌滑坡灾害及相关地形、地质空间数据库,分析了岩性、断层、地震动加速度、高程、坡度等5个因素与崩塌滑坡分布的关系,应用崩塌滑坡数量百分比这一标准来分别衡量每个因素中各个级别对崩塌滑坡的影响程度;然后使用层次分析法对这5个参数进行权重分析;在GIS平台下对这些参数进行综合分析,以此将研究区内的崩塌滑坡按易发程度分为极高易发区、高易发区、中易发区、低易发区4类,极高易发区与高易发区面积约2149.89 km2,占研究区总面积的32.32％.     

芦山地震重灾区地形因子分析

地形条件与山地灾害的发育密切相关,是山地灾害危险性评价的重要因子.以四川省芦山县“4·20”7.0级强烈地震灾区的芦山、宝兴、天全3县为研究区,应用GIS技术计算研究区坡度、地形位指数与地形起伏度,通过流域水文分析方法实现宝兴县子流域划分并提取沟床纵比降,分析灾区地形因子特征,结合灾后崩塌滑坡遥感解译结果,探讨次生山地灾害分布与地形因子的关系.结果表明,研究区坡度大于25°的面积占区域总面积的73.89％,地形位指数大于0.4的区域面积占总面积的85.92％,起伏度大于500 m的占87.41％,各地形因子面积比率最大的区段分别为坡度35°～40°、地形位指数0.648 ～0.666、起伏度500～1 000 m;宝兴县子流域沟床纵比降数值集中于100‰ ～ 300‰范围内.坡度30°～50°的区域为崩塌滑坡的高发地段;崩塌滑坡的优势地形位处于地形位指数0.228～0.246和0.34～0.61之间的区域;起伏度在500～1 000m的区域为崩塌滑坡的集中分布区.研究结果可为灾害评估及灾后恢复重建提供参考依据.     

黄土高原勺状沟壑特征及发育过程

沟谷是黄土高原物质交换最频繁,形态变化最剧烈的区域。在内外营力的共同作用下,不同发育阶段的各类沟谷塑造了黄土高原“千沟万壑”的独特地貌景观。在黄土高原沟壑系统中,广泛分布着一类特殊的黄土勺状沟壑,目前对其成因、发育过程与机理以及空间分布特征等的认知明显不足。本文以高分辨率遥感影像和DEM数据作为数据源,在大量野外调查和专家知识的基础上,首先提出了黄土勺状沟壑的概念,指出黄土勺状沟壑是独立发育于黄土坡面上的永久性沟谷。其次,从沟壑形态、汇流关系、侵蚀过程、分布特征等方面分析了黄土勺状沟壑区别于其他已有沟壑的特点。进而,从发育形态、发育规模、发育部位等角度对黄土勺状沟壑进行了分类,深化了对勺状沟壑的认识。再次,基于空代时理论,定量分析了黄土勺状沟壑发育过程的形态演变特征,进一步探讨了黄土勺状沟壑发育过程,论证了黄土勺状沟壑是黄土切沟的初期阶段。最后,在系统梳理总结勺状沟壑的特征及分类的基础上,提出了黄土勺状沟壑的发育过程设想,指出勺状沟壑的形成离不开黄土陷穴和暗穴的生成和发育,勺状沟壑的进一步发育伴随着水力侵蚀和重力侵蚀过程。勺沟尾部变细甚至消失,不能发育成更大规模的切沟,与地下暗穴、黄土渗透率、降雨条件以及地表覆盖有关。本文成果期望为进一步完善黄土沟谷地貌发育和侵蚀过程与机理等认识做出贡献,同时对黄土高原水土保持工作提供参考。     

基于GIS的长江三峡库区滑坡影响因子分析

利用GIS技术和统计方法,对三峡库区选定的研究区域(面积4539km2)滑坡空间分布和地形、地质等滑坡内部因子之间相关性进行统计计算。在建立地质、地形数据库等滑坡因子空间数据库和滑坡空间分布数据库(数据比例尺均为1∶10000)基础上,从地形数据库提取25m分辨率DEM,再派生出高程、高差、坡度、坡向、平面曲率、剖面曲率等地形影响因子;从地质数据库提取地层和岩性组合影响因子。将各个定性的因子按一定规则进行重分类、转换为25m分辨率的栅格数据格式,在GIS中进行地图代数运算、统计计算滑坡和各影响因子相关性。结果表明,滑坡分布和Q4、J1x,J1z、S岩性岩组;90m以下、90～135m和135～175m三个高程带;15～20m局部高差;10°～25°坡度;北、南和西北方向及-1～1曲率范围等影响因子相关性等级都大于1,为滑坡发生的主要影响因子类属。研究的结果是进行滑坡易发性评价的基础,可以指导库区滑坡灾害管理、土地利用等。     

西南关坝地区地质灾害类型特征及分布规律研究

关坝位于西南山区,地形地质条件复杂,地质灾害现象频繁发生。为加大对关坝地区地质灾害的认识和提升防灾减灾效果,在对该地区文献调研、走访的基础上,对地质灾害进行野外地质灾害调查工作,查明其类型及特征,并研究其分布规律。结果表明,万盛关坝地区共具十六个较大地质灾害点,以滑坡和危岩为主,滑坡主要发育在黏土岩地层中;危岩发育在灰岩、砂岩地层中,与重力作用和构造发育密切相关;其次,泥岩、页岩及风化堆积层中多发崩塌;岩崩、坠石发育于强岩层,分布最广;局部地区发育地面差异沉降、岩溶塌陷和采煤沉陷,规模较小;泥石流和山洪是具高潜势的地质灾害。     

云南鲁甸地震甘家寨滑坡基本特征及失稳机制

甘家寨滑坡是云南鲁甸6.5级地震诱发的特大型滑坡,规模达到1×10~7m~3。滑坡堵塞沙坝河,形成堰塞湖,中断交通,造成32户民房掩埋、55人死亡与失踪,是鲁甸地震区规模最大、灾损最严重的滑坡之一。该滑坡是地震诱发陡峻山体上的石灰岩强风化堆积体滑动而形成的特大型岩土质滑坡,表层为10~20 m固结良好的白云质灰岩结构体,中下层为50~60 m具空隙结构的深厚灰岩风化堆积物。滑坡主要的触发因素有:断层滑动方向性效应、地形放大效应、近断层地震动作用、背坡面效应。滑动过程分为坡体震裂松动、后缘拉裂、整体下滑、减速堆积4个阶段,受滑坡体原有地形影响及滑坡动力过程控制,滑坡堆积体形成4级台坎,其中第二级台坎形成高差约2 m的反向堆积。结合野外实际调查数据与滑坡运动力学模型,估算滑体水平滑动至350 m左右处,速度达到最大4.4 m/s,滑动至砂坝河时滑坡前缘速度减至3.6 m/min,堆积于河道,形成堰塞湖。甘家寨滑坡堆积体地形陡峻、堆积物裂缝密集分布,强降雨条件下,容易再次滑动并成灾,建议进行滑坡体的综合治理,控制后缘地表径流、减轻坡体下渗、强化滑坡前缘工程治理,保障交通顺畅,减轻灾害损失。     

Size and spatial distribution of loess slides on the Chinese Loess Plateau

ABSTRACT

The size and spatial distribution of loess slides are important for estimating the yield of eroded materials and determining the landslide risk. While previous studies have investigated landslide size distributions, the spatial distribution pattern of landslides at different spatial scales is poorly understood. The results indicate that the loess slide distribution exhibits a power-law scaling across a range of the size distribution. The mean landslide size and size distribution in the different geomorphic types are different. The double Pareto and inverse gamma functions can coincide well with the empirical probability distribution of the loess slide areas and can quantitatively reveal the rollover location, maximum probability, and scaling exponents. The frequency of loess slides increases with mean monthly precipitation. Moreover, point distance analysis showed that > 80% of landslides are located < 3 km from other loess slides. We found that the loess slides at the two study sites (Zhidan and Luochuan County) in northern Shaanxi Province, China show a significant clustered distribution. Furthermore, analysis results of the correlated fractal dimension show that the landslides exhibit a dispersed distribution at smaller spatial scales and a clustered distribution at larger spatial scales.     

Spatial pattern and influencing factors of landslide casualty events

Analysis of casualties due to landslides from 2000 to 2012 revealed that their spatial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area, and Tianshan and Qilian Mountains. However, local distribution patterns indicated that landslide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China (LCEC) was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by landslides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories: poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk.     

中国地质灾害伤亡事件的空间格局及影响因素（英文）

Analysis of casualties due to landslides from 2000 to 2012 revealed that their spatial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area, and Tianshan and Qilian Mountains. However, local distribution patterns indicated that landslide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China(LCEC) was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by landslides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories: poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk.     

GIS and ANN model for landslide susceptibility mapping

1 IntroductionThe population growth and the expansion of settlements and life-lines over hazardous areas exert increasingly great impact of natural disasters both in the developed and developing countries. In many countries, the economic losses and casualties due to landslides are greater than commonly recognized and generate a yearly loss of property larger than that from any other natural disasters, including earthquakes, floods and windstorms. Landslides in mountainous terrain often occur a…     

GIS and ANN model for landslide susceptibility mapping

Landslide hazard is as the probability of occurrence of a potentially damaging landslide phenomenon within specified period of time and within a given area. The susceptibility map provides the relative spatial probability of landslides occurrence. A study is presented of the application of GIS and artificial neural network model to landslide susceptibility mapping, with particular reference to landslides on natural terrain in this paper. The method has been applied to Lantau Island, the largest outlying island within the territory of Hong Kong. A three-level neural network model was constructed and trained by the back-propagate algorithm in the geographical database of the study area. The data in the database includes digital elevation modal and its derivatives, landslides distribution and their attributes, superficial geological maps, vegetation cover, the raingauges distribution and their 14 years 5-minute observation. Based on field inspection and analysis of correlation between terrain variables and landslides frequency, lithology, vegetation cover, slope gradient, slope aspect, slope curvature, elevation, the characteristic value, the rainstorms corresponding to the landslide, and distance to drainage line are considered to be related to landslide susceptibility in this study. The artificial neural network is then coupled with the ArcView3.2 GIS software to produce the landslide susceptibility map, which classifies the susceptibility into three levels: low, moderate, and high. The results from this study indicate that GIS coupled with artificial neural network model is a flexible and powerful approach to identify the spatial probability of hazards.     

灌溉诱发突发性黄土滑坡机理研究

系统揭示黑方台突发性黄土滑坡物理力学机理,对滑坡防治具有重要的作用。自上世纪六十年代年黑方台常年的农业灌溉诱发了大量20~40 m厚的饱和突发性黄土滑坡。本研究在野外调查的基础上,通过分析滑坡的变形破坏特征,针对分布范围广、危害性较大的突发性黄土滑坡,利用室内GDS三轴试验和模型试验,分析研究了饱和黄土的应力应变特性及突发性黄土滑坡的力学机制。三轴试验结果表明,当围压小于300 kPa时,饱和黄土可产生完全液化,并处于流塑状态;当围压大于300 kPa时,饱和黄土仅产生部分液化,仍具有一定的抗剪强度。饱和黄土的应力—应变模式均表现为强烈的应变软化—剪缩型,并具有一定的稳态特性。模型试验表明突发性黄土滑坡的变形破坏过程可大致分为底部浸水饱和—毛细水上升—持续蠕动变形—突发性破坏4个阶段。斜坡发生突发性破坏时,孔隙水压力激增,但总应力仍大于孔隙水压力,黄土滑坡发生部分液化,饱和黄土仍具有一定的强度,为突发性黄土滑坡发生提供了应力和能量积累的力学条件。研究从有效应力原理的角度阐述了突发性黄土滑坡的力学机理,可以为滑坡的防治治理提供一定的理论依据。     

Qualitative landslide susceptibility assessment by multicriteria analysis: A case study from San Antonio del Sur, Guantánamo, Cuba

Geomorphological information can be combined with decision-support tools to assess landslide hazard and risk. A heuristic model was applied to a rural municipality in eastern Cuba. The study is based on a terrain mapping units (TMU) map, generated at 1:50,000 scale by interpretation of aerial photos, satellite images and field data. Information describing 603 terrain units was collected in a database. Landslide areas were mapped in detail to classify the different failure types and parts. Three major landslide regions are recognized in the study area: coastal hills with rockfalls, shallow debris flows and old rotational rockslides denudational slopes in limestone, with very large deep-seated rockslides related to tectonic activity and the Sierra de Caujerí scarp, with large rockslides. The Caujerí scarp presents the highest hazard, with recent landslides and various signs of active processes. The different landforms and the causative factors for landslides were analyzed and used to develop the heuristic model. The model is based on weights assigned by expert judgment and organized in a number of components such as slope angle, internal relief, slope shape, geological formation, active faults, distance to drainage, distance to springs, geomorphological subunits and existing landslide zones. From these variables a hierarchical heuristic model was applied in which three levels of weights were designed for classes, variables, and criteria. The model combines all weights into a single hazard value for each pixel of the landslide hazard map. The hazard map was then divided by two scales, one with three classes for disaster managers and one with 10 detailed hazard classes for technical staff. The range of weight values and the number of existing landslides is registered for each class. The resulting increasing landslide density with higher hazard classes indicates that the output map is reliable. The landslide hazard map was used in combination with existing information on buildings and infrastructure to prepare a qualitative risk map. The complete lack of historical landslide information and geotechnical data precludes the development of quantitative deterministic or probabilistic models.     

汶川地震灾区滑坡空间特征变化分析

“5.12”汶川大地震触发了大量滑坡,给人民群众生命财产和社会经济发展造成了巨大损失。基于GIS空间分析方法,结合震前和震后的滑坡编目数据,对滑坡与坡度、坡向、高程、岩土类型、道路、河流和断裂带等7个孕灾环境因素的空间分布关系进行统计分析。结果表明：滑坡与孕灾环境因素的空间分布关系受地震的影响比较大。相比于震前,震后滑坡发生的优势坡度、优势岩土类型、优势距离缓冲区等均发生了很大的变化;并且坡向、距道路距离、距河流距离等因素对滑坡有明显地趋势性影响。     

汶川地震灾区滑坡空间特征变化分析简

“5.12”汶川大地震触发了大量滑坡,给人民群众生命财产和社会经济发展造成了巨大损失。基于GIS空间分析方法,结合震前和震后的滑坡编目数据,对滑坡与坡度、坡向、高程、岩土类型、道路、河流和断裂带等7个孕灾环境因素的空间分布关系进行统计分析。结果表明：滑坡与孕灾环境因素的空间分布关系受地震的影响比较大。相比于震前,震后滑坡发生的优势坡度、优势岩土类型、优势距离缓冲区等均发生了很大的变化;并且坡向、距道路距离、距河流距离等因素对滑坡有明显地趋势性影响。     

基于空间密度函数的哈尼梯田世界遗产地滑坡时空格局变化

为探究哈尼梯田世界文化景观遗产地核心区滑坡灾害时空分布规律，以Google Earth 0.55 m分辨率的2005、2009、2015年3期遥感影像为基础，结合实地走访调查，建立滑坡数据库，在ArcGIS 10.2平台上计算滑坡点的最邻近指数、K函数曲线及密度分布。结果显示：1）哈尼梯田遗产核心区2005、2009、2015年的滑坡数量分别为184、337和285个，对应最邻近指数为0.556、0.603、0.628；最显著聚集的空间尺度为1 000 m，从聚集向离散分布转变的空间尺度阈值分别为2.9、3.9、3.6 km。2）3个年份滑坡点高密度区占比逐渐增加（2.3%→5.8%→8.3%），中密度区占比亦逐渐增大（15.7%→21.8%→27.9%），低密度区占比逐渐减小（82.0%→72.5%→66.8%）。3）需要重点防范滑坡灾害风险的区域为森林区的西段和东段，村寨区的多依树、硐浦、勐品、水卜龙等地，以及阿勐控河和碧猛河流域内的梯田区。综上，研究区2005－2015年滑坡空间格局发生了显著变化，随着人类活动对地表景观干预程度不断加大，滑坡灾害风险增加了更多的不确定性。