Subaqueous density flow processes and deposits of an island volcano landslide (Stromboli Island, Italy)

Stromboli is a 3000 m high island volcano, rising to 900 m above sea-level. It is the most active volcano of the Aeolian Archipelago in the Tyrrhenian Sea (Italy). Major, large volume (1 km³) sector collapses, four occurring in the last 13 kyr, have played an important role in shaping the north-western flank (Sciara del Fuoco) of the volcano, potentially generating a high-risk tsunami hazard for the Aeolian Islands and the Italian coast. However, smaller volume, partial collapses of the Sciara del Fuoco have been shown to be more frequent tsunami-generating events. One such event occurred on 30 December 2002, when a partial collapse of the north-western flank of the island took place. The resulting landslide generated 10 m high tsunami waves that impacted the island. Multibeam bathymetry, side-scan sonar imaging and visual observations reveal that the landslide deposited 25 to 30 × 10⁶ m³ of sediment on the submerged slope offshore from the Sciara del Fuoco. Two contiguous main deposit facies are recognized: (i) a chaotic, coarse-grained (metre-sized to centimetre-sized clasts) deposit; and (ii) a sand deposit containing a lower, cross-bedded sand layer and an upper structureless pebbly sand bed capped by sea floor ripple bedforms. The sand facies develops adjacent to and partially overlying the coarse deposits. Characteristics of the deposits suggest that they were derived from cohesionless, sandy matrix density flows. Flow rheology and dynamics led to the segregation of the density flow into sand-rich and clast-rich regions. A range of density flow transitions, both in space and in time, caused principally by particle concentration and grain-size partitioning within cohesionless parent flows was identified in the deposits of this relatively small-scale submarine landslide event.     

Location of the source and shallow velocity model deduced from the explosion quakes recorded by two seismic antennas at Stromboli volcano

The seismic wavefield associated to the ongoing eruptive activity at Stromboli volcano (Italy) is investigated using data from two small-aperture, short-period seismic arrays deployed on the northern and western flanks, located at about 1.7 km from the active craters. Two distinct approaches are used to analyze the recorded signals:

• 1.1) the zero-lag cross-correlation method is used to analyze the explosion quakes data, to estimate slowness and backazimuth as a function of lapse time;
• 2.2) multiple filter technique and phase matched filtering are used to estimate Rayleigh wave dispersion, to obtain a shallow velocity model of the two sites.

Estimates of slowness vectors at the two different array sites show a primary (volcanic) source located at shallow depth beneath the crater region. Secondary sources associated with path effects are located in close proximity of the sector graben of Sciara del Fuoco and of the old parasitic cone of Timpone del Fuoco. The shallow velocity structure derived for the western flank depicts striking resemblance with that previously inferred for the northern flank of the volcano.     

Application of large-scale ring shear tests to the analysis of tsunamigenic landslides at the Stromboli volcano, Italy

The island of Stromboli (Southern Italy) is a 4,000-m-high volcanic edifice about 900 m above sea level. Most of the NW flank is formed by a wide scar (Sciara del Fuoco) filled by irregular alternations of volcaniclastic layers and thin lava flows. Between 29 and 30 December 2002, a submarine and a subaerial landslide involved the northernmost part of the Sciara del Fuoco slope and caused two tsunami waves with a maximum run-up of 10 m. Mechanisms of the rapid submarine landslide and the preceding deformation of the subaerial and submarine slope were investigated using large-scale ring shear tests on the saturated and dry volcaniclastic material. The shear behaviour of the material under different drainage conditions was analysed during tests conducted at DPRI, Kyoto University. Pore pressure generation, mobilised shear strength and grain crushing, within a range of displacements encompassing the different stages of evolution of the slope, were considered. Experimental results suggest that even at larger displacements, shear strength of the dry material explains the virtual stability of the slope. Conversely, full or partial liquefaction can be invoked to explain the submarine failure and the subsequent long runout (more than 1,000 m) of the failed materials.     

Numerical model of the Stromboli volcano (Italy) including the effect of magma pressure in the dyke system

Summary  The Stromboli island, in the Aeolian archipelago (Italy), is one of the most active volcanoes in Europe. In the last 13,000 years, its growth has been complicated by four sector collapses affecting the NW flank, the latest of which resulting in the formation of Sciara del Fuoco (SdF) horseshoe-shaped depression. Slope instability phenomena are represented not only by giant deep-seated gravitational slope deformations, but also by more frequent large landslides, such as occurred in December 2002–January 2003, and shallow landslides, involving loose or weakly cemented deposits, that constitute a natural hazard and affect residential and tourists safety. It is noteworthy that in volcanic environment the instability factors are manifold and much more complex than in other non-volcanic contexts. This paper deals with the Stromboli NW flank instability, and focuses on the effects of magma pressure in the feeding system. Two main objectives have been pursued: (1) to test a methodological approach, in order to evaluate a complex instability process; (2) to contribute to the understanding of volcano deformation and collapse mechanisms and associated hazard. A numerical model was developed by the Finite Difference Method and the FLAC 4.0 code, considering a cross-section of the entire volcano, orthogonal to the SdF and including both subaerial and submerged slopes. The stability of the volcano was analysed under gravity alone, and by introducing the magma pressure effect, both related to magmastatic and overpressure components. The results indicate that gravity alone is not sufficient to affect the stability of the volcano slopes, nor is the magmastatic pressure component. If an excess magma pressure component is introduced, instability is produced in accordance with field evidences and recent slope dynamics. Correspondence: Tiziana Apuani, Dipartimento di Scienze della Terra “A. Desio”, via Mangiagalli 34, 20133 Milano, Italy     

Large landslides triggered by caldera collapse events in Tenerife,Canary Islands

Landsliding is a significant process on volcanic edifices, with individual events exceeding several cubic kilometres in volume. The causes of such mass movements and their relationship with volcanic activity are still poorly understood. Landslide events are an important factor in the evolution of volcanic islands such as Tenerife, where vertical and lateral collapses have occurred repeatedly. Subaerial and submarine processes related to landslide events strongly influence the morphology of the island. On Tenerife there are three very big valleys, Güimar, La Orotava and Icod, that have been created by large landslide events with ages ranging from Upper Pliocene to Middle Pleistocene. The landslides affect the northern flanks of the island and the slopes of a large central volcanic edifice, the Las Canadas volcano, which is truncated by the Las Canadas caldera, a multicyclic collapse depression, formed between 1.02 and 0.17 Ma. We have focused our studies on the potential for caldera collapse events to trigger large scale landslides. The available geological and morphological information has been incorporated into numerical models, which simulate the destabilising effects of a caldera collapse episode. The results of the numerical modelling indicate that processes associated with caldera collapse events can overcome the stabilising forces on the volcano flank and trigger landslides. We propose that caldera collapse events may have triggered large landslides on the slopes of the Las Canadas volcano.     

A GIS method for landslide inventory and susceptibility mapping in the Río El Estado watershed,Pico de Orizaba volcano,México

In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. In Mexico, numerous geographic information systems (GIS)-based applications have been used to represent and assess slope stability. However, there is no practical and standardized landslide mapping methodology under a GIS. This work provides an overview of the ongoing research project from the Institute of Geography at the National Autonomous University of Mexico that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using GIS. The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial orthophotographs and field work. Next, the landslide susceptibility is modelled by using multiple logistic regression implemented in a GIS platform. The technique and its implementation of each level in a GISs-based technology is presented and discussed.     

Landslide triggers along volcanic rock slopes in eastern Sicily (Italy)

A new dataset of landslides, occurred in a tectonically active region, has been analysed in order to understand the causes of the slope instability. The landslides we have dealt with took place along the volcanic rock cliff of S. Caterina and S. Maria La Scala villages (eastern Sicily, Italy), a densely inhabited area located on the eastern margin of Mt. Etna, where some seismogenic faults, locally named Timpe system, slip during moderate local earthquakes and also move with aseismic creep mechanisms. The results show that landslides are triggered by heavy rainfalls, earthquakes and creep fault episodes. Indeed, they occur along discrete fault segments, exhibiting a combination of both brittle failure, indicated by the earthquake occurrence, and aseismic creep events. The analysis of seismicity occurred on the Timpe fault system has shown that the active Acireale fault, in its southernmost segment, is subject to an aseismic sliding, which increases after the stick–slip motion in the nearby faults. Therefore, aseismic creep seems to concur in the predisposition of a rock to fail, since strains can increase the jointing of rock masses leading to a modification in the slope stability. Understanding the factors concurring to the slope instability is a useful tool for future assessments of the landslide hazard in densely settled areas, located on a volcanic edifice, such as Etna that is slowly sliding seawards, and where active faults, seismicity and heavy rains affect the deeply fractured slopes.     

A review of assessing landslide frequency for hazard zoning purposes

The probability of occurrence is one of the key components of the risk equation. To assess this probability in landslide risk analysis, two different approaches have been traditionally used. In the first one, the occurrence of landslides is obtained by computing the probability of failure of a slope (or the reactivation of existing landslides). In the second one, which is the objective of this paper, the probability is obtained by means of the statistical analysis of past landslide events, specifically by the assessment of the past landslide frequency. In its turn, the temporal frequency of landslides may be determined based on the occurrence of landslides or from the recurrence of the landslide triggering events over a regional extent. Hazard assessment using frequency of landslides, which may be taken either individually or collectively, requires complete records of landslide events, which is difficult in some areas. Its main advantage is that it may be easily implemented for zoning. Frequency assessed from the recurrence of landslide triggers, does not require landslide series but it is necessary to establish reliable relations between the trigger, its magnitude and the occurrence of the landslides. The frequency of the landslide triggers can be directly used for landslide zoning. However, because it does not provide information on the spatial distribution of the potential landslides, it has to be combined with landslide susceptibility (spatial probability analysis) to perform landslide hazard zoning. Both the scale of work and availability of data affect the results of the landslide frequency and restrict the spatial resolution of frequency zoning as well. Magnitude–frequency relationships are fundamental elements for the quantitative assessment of both hazard and risk.     

Regional assessment of landslide impact in the Three Gorges area, China, using ASTER data: Wushan-Zigui

This paper is focussed on the hazard impact of landslides in the Three Gorges, and represents the progression of our ongoing study on regional land instability assessment in the Three Gorges area using imagery data from the Advanced Spaceborne Thermal Emission Radiometer (ASTER). The key development here is the establishment of a model that integrates land instability with several factors that can relate hazard to human life, such as slope failures occurring in proximity to built-up areas and roads, and areas of high landslide risk along the bank of Yangtze and its major tributaries. The method correctly identifies some of the known destructive landslides in the region, like Qianjiangping and Huangtupo, as belonging to areas of potentially high landslide impact. Our results suggest that several population centres, including the towns of Wushan and Badong, are rated at high landslide hazard levels. This study highlights the importance of differentiating between landslide types within susceptibility assessment, and identifies those locations in the Three Gorges where the probability of landslide occurrence with negative impact to life and property is greatest.     

Evidence for carbonate platform failure during rapid sea‐level rise; ca 14 000 year old bioclastic flow deposits in the Lesser Antilles

Bioclastic flow deposits offshore from the Soufrière Hills volcano on Montserrat in the Lesser Antilles were deposited by the largest volume sediment flows near this active volcano in the last 26 kyr. The volume of these deposits exceeds that of the largest historic volcanic dome collapse in the world, which occurred on Montserrat in 2003. These flows were most probably generated by a large submarine slope failure of the carbonate shelf comprising the south‐west flank of Antigua or the east flank of Redonda; adjacent islands that are not volcanically active. The bioclastic flow deposits are relatively coarse‐grained and either ungraded or poorly graded, and were deposited by non‐cohesive debris flow and high density turbidity currents. The bioclastic deposit often comprises multiple sub‐units that cannot be correlated between core sites; some located just 2 km apart. Multiple sub‐units in the bioclastic deposit result from either flow reflection, stacking of multiple debris flow lobes, and/or multi‐stage collapse of the initial landslide. This study provides unusually precise constraints on the age of this mass flow event that occurred at ca 14 ka. Few large submarine landslides have been well dated, but the slope failures that have been dated are commonly associated with periods of rapid sea‐level change.     

Integration of statistical and heuristic approaches for landslide risk analysis: a case of volcanic mountains in West Java Province,Indonesia

Owing to fragile geo-morphology, extreme climatic conditions, and densely populated settlements and rapid development activities, West Java Province is the most landslide hazardous area in Indonesia. So, a landslide risk map for this province bears a great importance such as for land-use planning. It is however widely accepted that landslide risk analysis is often difficult because of the difficulties involved in landslide hazard assessment and estimation of consequences of future landslide events. For instance, lack of multi-temporal inventory map or records of triggering events is often a major problem in landslide hazard mapping. In this study, we propose a simple technique for converting a landslide susceptibility map into a landslide hazard map, which we have employed for landslide risk analysis in one ideally hazardous part of volcanic mountains in West Java Province. The susceptibility analysis was carried out through correlation between past landslides and eight spatial parameters related to instability, i.e. slope, aspect, relative relief, distance to river, geological units, soil type, land use and distance to road. The obtained susceptibility map was validated using cross-time technique, and was collaborated with the frequency-area statistics to respond to ‘when landslide will occur’ and ‘how large it will be’. As for the judgment of the consequences of future landslides, expert opinion was used considering available literature and characteristic of the study area. We have only considered economic loss in terms of physical damage of buildings, roads and agricultural lands for the landslide risk analysis. From this study, we understand the following: (1) the hazard map obtained from conversion of the susceptibility map gives spatial probability and the area of an expected landslide will be greater than 500m² in the next 2 years, (2) the landslide risk map shows that 24% of the total area is in high risk; 30% in moderate risk; 45% in low risk and no risk covers only 1% of the total area, and (3) the loss will be high in agricultural lands, while it will be low in the road structures and buildings.     

A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses

Bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the Cuyahoga River watershed, northeastern Ohio, U.S.A. The relationship between landslides and various instability factors contributing to their occurrence was evaluated using a Geographic Information System (GIS) based investigation. A landslide inventory map was prepared using landslide locations identified from aerial photographs, field checks, and existing literature. Instability factors such as slope angle, soil type, soil erodibility, soil liquidity index, landcover pattern, precipitation, and proximity to stream, responsible for the occurrence of landslides, were imported as raster data layers in ArcGIS, and ranked using a numerical scale corresponding to the physical conditions of the region. In order to investigate the role of each instability factor in controlling the spatial distribution of landslides, both bivariate and multivariate models were used to analyze the digital dataset. The logistic regression approach was used in the multivariate model analysis. Both models helped produce landslide susceptibility maps and the suitability of each model was evaluated by the area under the curve method, and by comparing the maps with the known landslide locations. The multivariate logistic regression model was found to be the better model in predicting landslide susceptibility of this area. The logistic regression model produced a landslide susceptibility map at a scale of 1:24,000 that classified susceptibility into four categories: low, moderate, high, and very high. The results also indicated that slope angle, proximity to stream, soil erodibility, and soil type were statistically significant in controlling the slope movement.     

Landslides in the North of Lisbon Region (Portugal): Conditioning and triggering factors

Detailed geomorphological mapping carried out in 5 sample areas in the North of Lisbon Region allowed us to collect a set of geological and geomorphological data and to correlate them with the spatial occurrence of landslide. A total of 597 slope movements were identified in a total area of 61.7 km², which represents about 10 landslides per km².The main landslide conditioning factors are: lithology and geological structure, slope angle and slope morphology, land use, presence of old landslides, and human activity.The highest landslide density occurs in Cretaceous marls and marly limestones, but the largest movements are in Jurassic clays, marls and limestones.The landslide density is higher on slopes with gradients above 20 °, but the largest unstable area is found on slopes of 10 ° to 15 °, thus reflecting the presence of the biggest slope movements. There is a correlation between landslides and topographical concavities, a fact that can be interpreted as reflecting the significance of the hydrological regime in slope instability.Concerning land use, the highest density of landslides is found on slopes covered with shrub and undergrowth vegetation.About 26% of the total number of landslides are reactivation events. The presence of old landslides is particularly important in the occurrence of translational slides and complex and composite slope movements.20% of the landslide events were conditioned by anthropomorphic activity. Human's intervention manifests itself in ill-consolidated fills, cuts in potentially unstable slopes and, in a few cases, in the changing of river channels.Most slope movements in the study area exhibit a clear climatic signal. The analysis of rainfall distribution in periods of recognised slope instability allows the distinction of three situations: 1) moderate intensity rainfall episodes, responsible for minor slope movements on the bank of rivers and shallow translational slides, particularly in artificial trenches; 2) high intensity rainfall episodes, originating flash floods and most landslides triggered by bank erosion; 3) long-lasting rainfall periods, responsible for the rise of the groundwater table and triggering of landslides with deeper slip surfaces.     

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.     

Structural and geomorphological aspects of the Kat landslides (Tokat—Turkey) and susceptibility mapping by means of GIS

Kat County, which is located in a slope of hilly region and constructed in the side of a mountain along the North Anatolian Fault Zone, is frequently subject to landslides. The slides occur during periods of heavy rainfall, and these events cause destruction to property, roads, agricultural lands and buildings. In the last few decades, a lot of houses and buildings have been damaged and destroyed. Settlement areas have remained evacuated for a long time. The slope instabilities in the study area are a complex landslide extending from north to south containing a lot of landslides. Field investigations, interpretation of aerial photography, analyses of geological data and laboratory tests suggest that some factors have acted together on the slopes to cause the sliding. In the wet season, the slopes became saturated. As the saturation of the earth material on the slope causesa rise in water pressure, the shear strength (resisting forces) decreases and the weight (driving forces) increases; thus, the net effect was to lower the safety factor. Previous failures have affected the rock mass, leading to the presence of already sheared surfaces at residual strengths. The relation between the joint planes and the instability of the slope in the study area was discussed and it was found that the potential slope instabilities are mainly in the directions of NW–SE, NE–SW and N–S. The landslide susceptibility map obtained by using the geographical information system showed that a large area is susceptible and prone to landslides in the northern part of the study area.An erratum to this article can be found at     

遗传算法优化BP网络在滑坡灾害预测中的应用研究

在陕西省宝鸡市附近长寿沟地区滑坡详细调查和遥感解译的基础上,完成了1∶10000滑坡编目图。通过使用GIS的水文分析功能,运用正反DEM技术,将长寿沟地区划分为216个自然斜坡单元,其中包括123个滑坡单元和93个未发生滑坡单元,分析滑坡发生与坡高、坡度、坡向、坡形、人类工程活动和水文地质条件影响因子之间的统计规律。利用经遗传算法优化后的BP神经网络对80个滑坡样本和40个未滑坡样本进行训练学习,然后再利用训练好的网络对预测样本进行评价分析。结果表明:43个已滑坡单元中只有3个被误判为无滑坡,正确率为9302%,53个未滑坡单元中有10个被预测为滑坡,正确率为8113%,总体正确率为8646%。通过对被预测为滑坡的10个斜坡单元进行分析,发现这些单元在坡形、坡高等影响因素的组合上已经具备了发生滑坡的条件,虽然目前没有发生滑坡,但作为潜在的滑坡危险区,可以为滑坡灾害预测预报和防灾减灾工作提供参考。     

Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model

A remote sensing and Geographic Information System-based study has been carried out for landslide susceptibility zonation in the Chamoli region, part of Garhwal Himalayas. Logistic regression has been applied to correlate the presence of landslides with independent physical factors including slope, aspect, relative relief, land use/cover, lithology, lineament, and drainage density. Coefficients of the categories of each factor have been obtained and used to assess the landslide probability value to ultimately categorize the area into various landslide susceptibility zones; very low, low, moderate, high, and very high. The results show that 71.13% of observed landslides fall in 21.96% of predicted very high and high susceptibility zone, which in fact should be the case. Furthermore, lineament first buffer category (0–500 m) and the east and south aspects are the most influential in causing landslides in the region.     

Distribution and characteristics of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 in Tohoku District, Northeast Japan

The Iwate–Miyagi Nairiku Earthquake in 2008, whose seismic intensity was M. 7.2 in Japan Meteorological Agency (JMA) scale, induced innumerable landslides on the southern flank of Mt. Kurikoma volcano allocated along the Ou Backbone Range in Northeast Japan. Most landslides are detected in a hanging wall side of the seismic fault. Those landslides are classified into five types: deep-seated slide, debris slide, shallow debris slide, secondary shallow debris slide, and debris flow. Most common landslide types induced by the earthquake are shallow debris slides and subsequent debris flows. They are intensively distributed along steep gorges incising a volcanic skirt of Mt. Kurikoma, consisting of welded ignimbrite of the Pleistocene age. Debris flows are also distributed even along gentle river floors in the southern lower flank of the volcano. The area of densely distributed debris slides, shallow debris slides, and debris flows is concordant with that of severe seismic tremor. Thus, genetic processes of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 are attributed to multiple causative factors such as geology, topography, and seismic force.     

机器学习及其相关算法综述

机器学习已经在滑坡易发性评价中大量应用且取得了较好的表现,但在进行大区域评价时,仍存在数据库样本需求量大,算力要求高;影响因素分级机械化,未考虑其与滑坡机理的相关性等情况。为减少数据库样本需求,本文提出了构建包含3种坡体状态的滑坡的数据库：已经发生过失稳的坡体、正处于失稳状态的坡体、失稳概率小的坡体,该数据库可以在数值上划分出临界值,便于模型更准确地识别滑坡,较大幅度地减小了数据量。针对影响因素分级机械化的问题,提出了基于频数分布图、累计曲线及其导数图的数理统计方式,更精细地描述因数与滑坡易发性的关系。以新疆滑坡灾害为例,验证了“包含3种坡体状态的数据库”与“基于数理统计的描述方法”的适用性,获得了新疆滑坡灾害易发性分区图。结果表明与传统数据库对比,在不明显改变精度的前提下,减少了90%以上的样本量;基于数理统计的描述方法可以绘制出更加细致的滑坡危险性分区图;活动性断裂和地形起伏度对新疆滑坡易发性起到重要的控制作用。     

基于确定性系数的降雨型滑坡影响因子敏感性分析

本文选择东南沿海地区具有典型降雨型滑坡的淳安县作为研究区,在完成全县地质灾害详细调查的基础上,选取高程、坡度、坡向、曲率、工程地质岩组、距断层距离、距道路距离、土地利用和植被等9个滑坡影响因子,利用GIS技术与确定性系数分析方法,对这9个影响因子开展敏感性分析。研究结果表明:(1) 寒武、震旦、石炭和白垩系是滑坡易发地层,侵入岩组、紫红色砂岩、碳酸盐岩夹碎屑岩、碳酸盐岩为主的岩组是滑坡高敏感性岩组;滑坡受断层影响总体上随着距离断层由近及远逐渐降低;(2) 坡度范围10°~35°是滑坡的易发坡度,30°~35°滑坡数量达到峰值;SE和S等朝南坡向是滑坡最易发坡向;高程范围为100~200m是滑坡最易发区间;凹坡最易发生滑坡,而凸坡则滑坡敏感性最差;非林地、茶叶、竹林和经济林等是滑坡高敏感植被类型;(3) 住宅用地、耕地、园地等与人类活动密切相关的用地类型是滑坡易发地类;距道路距离因子对滑坡敏感性低,相关性不明显。上述各滑坡影响因子最利于滑坡发生的数值区间确定,将为研究区进一步开展降雨型滑坡区域易发性评价及预测奠定基础。