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1.
The crucial and difficult task in landslide susceptibility analysis is estimating the probability of occurrence of future landslides in a study area under a specific set of geomorphic and topographic conditions. This task is addressed with a data-driven probabilistic model using likelihood ratio or frequency ratio and is applied to assess the occurrence of landslides in the Tevankarai Ar sub-watershed, Kodaikkanal, South India. The landslides in the study area are triggered by heavy rainfall. Landslide-related factors—relief, slope, aspect, plan curvature, profile curvature, land use, soil, and topographic wetness index proximity to roads and proximity to lineaments—are considered for the study. A geospatial database of the related landslide factors is constructed using Arcmap in GIS environment. Landslide inventory of the area is produced by detailed field investigation and analysis of the topographical maps. The results are validated using temporal data of known landslide locations. The area under the curve shows that the accuracy of the model is 85.83%. In the reclassified final landslide susceptibility map, 14.48% of the area is critical in nature, falling under the very high hazard zone, and 67.86% of the total validation dataset landslides fall in this zone. This landslide susceptibility map is a vital tool for town planning, land use, and land cover planning and to reduce risks caused by landslides.  相似文献   

2.
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.  相似文献   

3.
Rainfall-induced landslides in Hulu Kelang area, Malaysia   总被引：5，自引：2，他引：3  
Hulu Kelang is known as one of the most landslide-prone areas in Malaysia. The area has been constantly hit by landslide hazards since 1990s. This paper provides an insight into the mechanism of rainfall-induced landslide in the Hulu Kelang area. Rainfall patterns prior to the occurrences of five selected case studies were first analyzed. The results showed that daily rainfall information is insufficient for predicting landslides in the area. Rainfalls of longer durations, i.e., 3–30 days prior to the landslides should be incorporated into the prediction model. Numerical simulations on a selected case study demonstrated that both matric suction and factor of safety decreased steadily over time until they reached the lowest values on the day of landslide occurrence. Redistribution of infiltrated rainwater in the soil mass could be a reason for the slow response of failure mechanism to rainfall. Based on 21 rainfall-induced landslides that had occurred in the area, three rainfall thresholds were developed as attempts to predict the occurrence of rainfall-induced landslide. The rainfall intensity–duration threshold developed based on the local rainfall conditions provided a reasonably good prediction to the landslide occurrence. The cumulative 3- versus 30-day antecedent precipitation index threshold chart was capable of giving the most reliable prediction with the limiting threshold line for major landslide yielded a reliability of 97.6 %.  相似文献   

4.
This study proposes a probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by combining a transient infiltration flow model and Monte Carlo simulations. The spatiotemporal change in pore water pressure over time caused by rainfall infiltration is one of the most important factors causing landslides. Therefore, the transient infiltration hydrogeological model was adopted to estimate the pore water pressure within the hill slope and to analyze landslide susceptibility. In addition, because of the inherent uncertainty and variability caused by complex geological conditions and the limited number of available soil samples over a large area, this study utilized probabilistic analysis based on Monte Carlo simulations to account for the variability in the input parameters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. To evaluate its effectiveness, the proposed analysis method was applied to a study area that had experienced a large number of landslides in July 2006. For the susceptibility analysis, a spatial database of input parameters and a landslide inventory map were constructed in a GIS environment. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. In addition, the probabilistic method exhibited better performance than the deterministic alternative. Thus, analysis methods that account for uncertainties in input parameters are more appropriate for analysis of an extensive area, for which uncertainties may significantly affect the predictions because of the large area and limited data.  相似文献   

5.
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.  相似文献   

6.
Landslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts.  相似文献   

7.
On October 23, 2004, a series of powerful earthquakes with a maximum M w = 6.6 located near the western coast of northern Honshu struck parts of northern Japan, particularly Niigata Prefecture; these earthquakes were known as the Chuetsu event. Thousands of landslides, as a secondary geotechnical hazard associated with these earthquakes, were triggered over a broad area; these landslides were of almost all types. The purpose of this study was to detect correlations between landslide occurrence with geologic and geomorphologic conditions, slope geometry, and earthquake parameters using two indexes based on Geographic Information Systems (GIS). In the study area, the landslide–area ratio (LAR), which is defined as the percentage of the area affected by landslides, was 2.9%, and the landslide concentration (LC), the number of landslides per square kilometer, was 4.4 landslides/km2, which is much more than other reported cases of seismic activity with the same magnitude. This was possibly due to heavy rainfall just before the Chuetsu earthquakes. Statistical analyses show that LAR has a positive correlation with slope steepness and distance from the epicenter, while LC is inversely correlated with distance from the epicenter. The Wanazu Formation had the most concentrated landslide activity, followed by the Kawaguchi, Ushigakubi, Shiroiwa and Oyama Formations, although the Wanazu Formation occupied only 4.5% of the total area of geological units. With 8.2% of the area affected by seismic landslides, the Kawaguchi Formation had the highest LAR. It was followed by the Shiroiwa, Ushigakubi and Wanazu Formations with LAR ranging from 4.6% to 6.0%. For lots of geological subunits, landslides are more frequent in a range of slope angles between 15° and 40°. The susceptibility to landsliding of each geologic unit was thus evaluated to correlate with slope steepness. It was also noted that the effects of the earthquakes were made far worse by antecedent rainfall conditions induced by a␣typhoon, and further research emphasizing the role of antecedent rainfall was discussed.  相似文献   

8.
The governing factors that influence landslide occurrences are complicated by the different soil conditions at various sites.To resolve the problem,this study focused on spatial information technology to collect data and information on geology.GIS,remote sensing and digital elevation model(DEM) were used in combination to extract the attribute values of the surface material in the vast study area of SheiPa National Park,Taiwan.The factors influencing landslides were collected and quantification values computed.The major soil component of loam and gravel in the Shei-Pa area resulted in different landslide problems.The major factors were successfully extracted from the influencing factors.Finally,the discrete rough set(DRS) classifier was used as a tool to find the threshold of each attribute contributing to landslide occurrence,based upon the knowledge database.This rule-based knowledge database provides an effective and urgent system to manage landslides.NDVI(Normalized Difference Vegetation Index),VI(Vegetation Index),elevation,and distance from the road are the four major influencing factors for landslide occurrence.The landslide hazard potential diagrams(landslide susceptibility maps) were drawn and a rational accuracy rate of landslide was calculated.This study thus offers a systematic solution to the investigation of landslide disasters.  相似文献   

9.
We developed a real-time forecasting system, aiNet-GISPSRIL, for evaluating the spatiotemporal probability of occurrence of rainfall-triggered landslides. In this system, the aiNet (a kind of artificial neutral network based on a self-organizing system) and GIS are merged for integrating the rainfall conditions into various environmental factors that influence the landslide occurrence and for simulating the complex non-linear relationships between landslide occurrence and its related conditions. Zhejiang Province (101,800 km2 in area), located in the southeast coastal region of China, is highly prone to the occurrence of landslides during intensive rainfall. Since 2003, the aiNet-GISPSRIL has been used to predict landslides during the rainy seasons in the region. The aiNet-GISPSRIL uses the regional 24-h forecast rainfall information and the real-time rainfall monitoring data from the rain-gauge network as its inputs, and then provides 24-h forecast of the landslide probability for every 1 × 1-km grid cell within the region. Verification studies on the performance of the aiNet-GISPSRIL show that the system has successfully predicted the dates and localities of 304 landslides (accounting for 66.2% of reported landslides during the period). During the period from 2003 to 2007, because the system provided the probability levels of landslide occurrences up to 24-h in advance, gave locations of potential landslides, and timely warned those individuals at high-risk areas, more than 1700 persons living in the risk sites had been evacuated to safe ground before the landslides occurred and thus casualty was avoided. This highly computerized, easy-operating system can be used as a prototype for developing forecasting systems in other regions that are prone to rainfall-triggered landslides.  相似文献   

10.
A large landslide occurred at Maierato (Vibo Valencia District), Southern Italy, on 15 February 2010, when rapid failure was produced after several days of preliminary movements. The landslide can be classified as a rotational slide with flowing of the mass. It occurred within a larger deep-seated gravitational movement area and was preconditioned for failure by the intrinsic geological weakness of the area. Actually, the in situ survey showed the presence of several ancient movement surfaces all around the urban area. The landslide-triggering factor was the increase in the groundwater flow, consequent to a period of heavy and prolonged rainfall. The aim of the paper is to explain the mechanism of occurrence of the February 2010 composite landslide, in order to assess the landslide hydrogeological susceptibility in the whole urban area of Maierato. For this reason, the present paper deals with: (1) identification of the landslide mechanism and triggering factors (2) slope stability back-analysis using a finite-difference-based shear strength reduction method, and (3) 3D groundwater flow modelling extended to the whole urban area both in pre- and post-failure conditions. The results show that the February 2010 composite landslide was triggered by a water table increase of about 15 m uphill the landslide scarp. This hydrogeological condition could be reached after the period of heavy and prolonged rainfall preceding the landslide event. Finally, based on the groundwater modelling in post-failure condition, a landslide hydrogeological susceptibility map was drawn for the all urban area of Maierato, showing the presence of extended areas exposed to hazard.  相似文献   

11.
The article draws a comparison between different ways of landslide geometry interpretation in the scope of the statistical landslide hazard and risk assessment processing. The landslides are included as a major input variable, which are compared with all of the input parametric factors. Based on the above comparison the input data are classified and the final map of landslide susceptibility is constructed. Methodology of multivariate conditional analysis has been used for the construction of final maps. Unique condition units was developed by combination of geological map (lithological units) and slope angle map. Lithological units were derived from geological map and subsequently reclassified into 22 classes. Slope angle map was calculated from digital elevation model (contour map at a scale 1:10,000) and reclassified into nine classes. As a case study, a wide area of Horná Súča (western Slovakia) strongly affected by landsliding (predominantly made of Flysch) has been chosen. Spatial data in the form of parametric maps, as well as final statistical data set were processed in GIS GRASS environment. Four different approaches are used for landslides interpretation: (1) area of landslide body including accumulation zone, (2) area of depletion zone, (3) lines of elongated main scarps, (4) lines of main scarp upper edge. For each approach, a zoning map of landslide susceptibility was compiled and these were compared with each other. Depending on the interpretation approach, the final susceptibility zones are markedly different (in tens of percent).  相似文献   

12.
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.  相似文献   

13.
Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multi-temporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10  years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.  相似文献   

14.
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.  相似文献   

15.
Landslides are a major natural hazard in the Bamenda highlands of Cameroon, and their occurrence in this region has most often been studied using qualitative methods. The aim of this research is to quantitatively assess the spatial probability of landslides using GIS and the informative value model. Landslide inventory was done through literature review, aerial photo-interpretation, participatory GIS and field survey. Six geo-environmental factors including slope, curvature, aspect, land use, lithology and geomorphology were used as landslide conditioning (static) factors. The susceptibility of the area to future landslide events was assessed by making a correlation between past landslides and geo-environmental factors using the informative value model. The landslide inventory involving 110 landslides was divided into two equal groups using random division criterion and was used to train and validate the model. The analysis showed that slope and land use are the most important causal factors of landslides in the area. The susceptibility index map predicted most landslides to occur around the steep slopes of the Bamenda escarpment that is being used for multiple anthropic activities. The training model had a success rate of 87%, and the validation model had a prediction rate of 90%. The prediction rate curve shows that 44, 32, 18 and 6% of future landslides will occur on 3, 8, 21 and 68% of the study area. The model correctly classified 89% of unstable areas and 81% of the stable areas with an accuracy rate of 0.90. This quantitative result complement other qualitative assessment results that show the Bamenda escarpment zone as a high-risk area. However, the area susceptible to landslide in this study goes beyond what earlier studies had indicated as houses and other infrastructure were found on old landslide sites whose scars have been eroded by human activities. This new input thus improves the quality of information placed at the disposal of civil protection units and land use managers during decision making.  相似文献   

16.
In this paper, we propose a methodology for landslide susceptibility assessment at a regional scale in Yunnan, southwestern province of China. A landslide inventory map including 3,242 landslide points was prepared for the study area. Five factors recognized as correlated to landslide (namely, lithology, relative relief, tectonic fault density, rainfall, and road density) were analyzed and mapped in geographic information system. An index expressing the correlation between each factor and landslides [called class landslide susceptibility index (CLSI)] was proposed in the study. While analyzing landslide distribution in a large area, point aggregation might be expected. To quantify the uncertainty caused by aggregation, class landslide aggregation index was proposed. To account for the importance of each of the factors in the landslide susceptibility assessment, some weights were calculated by means of analytic hierarchy process. We propose a weighted class landslide susceptibility model (WCLSM), obtained by the combination of CLSI values of each factor with the correspondent weight. WCLSM performance in the study area was evaluated comparing the results obtained by first modeling all landslides and then by performing a time partition. The model was run including only landslides that occurred before 2009 and then validated with respect to landslides that occurred after 2009. The prediction–rate curve shows that the WCLSM model provides a good prediction for the study area. Of the study area, 21.4 % shows very high and high susceptibility and includes the 87.7 % of the number of landslides that occurred after 2009.  相似文献   

17.
The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years.  相似文献   

18.
 The expansion of Caramanico Terme in this century has led to the urbanization of marginally stable valley slopes, and this has coincided with the apparent acceleration of landslide processes. Recent landslides on man-modified slopes were caused, but not necessarily triggered, by heavy precipitation (antecedent moisture was a more critical factor than the amount of storm rainfall). Because no important landslides on natural slopes in the same period were reported in the Caramanico area, a clear distinction must be made between natural settings and those modified by man when determining rainfall thresholds for predictive purposes. In recently urbanized mountainous environments, the thresholds used to assess landslide hazards should not be weighted too heavily on old historical records of precipitation and associated mass movements. Instead, more weight ought to be given to the period following the occurrence of any major anthropogenic and natural (e.g. high-magnitude earthquake) modification of slope setting. Received: 19 October 1996 · Accepted: 25 June 1997  相似文献   

19.
We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.  相似文献   

20.
本文以汶川地震强震区北川县典型研究区为例,利用高分辨率航片、SPOT5卫星图像对北川县典型研究区进行了512地震之后和924降雨之后诱发的滑坡解译,解译结果显示:512地震诱发滑坡1999个,924强降雨诱发滑坡828个,924强降雨导致原有地震滑坡面积扩大的滑坡150个。研究表明:地震和强降雨都是诱发滑坡的动力成因,924强降雨诱发的滑坡面积是512地震诱发滑坡面积的1/4倍,强降雨诱发滑坡的数量增加了41.4%; 强降雨不仅诱发新的滑坡,而且促使原来地震滑坡复活,并扩大其面积,强降雨导致地震诱发的滑坡面积扩大了原面积的68.7%。同时,在遥感解译数据基础之上,开展地震诱发滑坡与降雨诱发滑坡规模对比和控制因子耦合分析及地震与降雨耦合灾害链模式研究,为进一步分析研究地震灾区滑坡的产生、发展趋势、危险性和风险评价等预测预报提供科学依据,也为汶川震区恢复重建中的减灾防灾提供决策参考。  相似文献   

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