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Showing 6 results for Landslide Hazard


Volume 1, Issue 2 (11-2003)
Abstract

(Paper pages 179-192) Artificial Neural Network (ANN), has many abilities which have increade its application in different fields of engineering and geosciences. In this paper, the application of ANN in geological engineering(prediction of landslide hazard) in Talesh area, north of Iran, is evaluated. The results are shown that, the system is able to process input data by selecting effective parameters of landslide and give the landslide hazard potential as a ANN output. By considering the landslide hazard zonation map of the area and by using the ANN system, it becomes clear that, the Talesh area is a landslide hazard prone area. The most effective factors of slope instability of the area, are land use and land cover conditions, ground water and surface water effects, river erosion and tectonics activities.
Sm Fatemiaghda, V Bagheri, Mr Mahdavi,
Volume 8, Issue 3 (12-2014)
Abstract

In the present study, landslides occurred during 1997 Sarein, Iran earthquake are discussed and evaluated. In order to meet the objectives, the Computing with Words (CW), an approach using fuzzy logic systems in which words are used in place of numbers for computing and reasoning is applied. Firstly, the necessary information which include disturbance distance, ground class, moisture, shaking intensity, slope angle, slope height, soil depth, terrain roughness, and land-use have been collected using air photos, LANDSAT satellite images, geological and topographic maps, and site investigation of the studied region. The data is digitized and weighted using ARCGIS software. At the next step, the hazard rate and predicted areal concentrations of landslides with respect to their types are calculated using CAMEL software (Miles & Keefer, 2007). CAMEL provides an integrated framework for modeling all types of earthquake-induced landslides using geographical information system(GIS). Finally, landslides hazard map is compared to landslides triggered by Sarein earthquake.
H Atapour, R Ahmadi,
Volume 9, Issue 3 (12-2015)
Abstract

In present research, landslide hazard zonation of Latian dam watershed area has been carried out using Analytic Hierarchy Process (AHP), Valuing area accumulation, Factor overlay and Information value methods. At first, different maps comprising slope, aspect, altitude, faults, drainage network, access roads, lithology, land use and friction angle maps were prepared digitally using GIS. Afterward affecting factors were evaluated using old landslides. The results of evaluation show that seven parameters are important effective factors on sliding in this area. These parameters were leaded to landslide zonation maps. These maps show that potentially high risk zones point of view landslides are located near the central and western boundaries of the reservoir. Performance of four used classification methods were evaluated and compared. The evaluation results show that Valuing area accumulation and Factor overlay are precise methods for evaluating landslide potential in the study area respectively
, M Fallah,
Volume 10, Issue 2 (11-2016)
Abstract

This paper presents landslide assessment and landslide hazard zonation of the Polroud Dam area. Polroud Dam is one of the largest dams that are in construction, 29 km south of Roudsar in Gilan Province. Considering to geomorphology and geological conditions of the area, the site is susceptible to landslide hazard. Field survey shows many evidences of the instabilities especially in the slopes overlooking to the dam and the reservoir. The historical record also demonstrates high potential of the region to slope instabilities. A large landslide that occurred in 1996 discern that the frequency of the hazard in the region. Therefore, Identification of the landslide potential hazard is vital before impounding the reservoir. In this study, we investigated landslide hazard in the site and we have prepared landslide hazard zonation map using the main parameters. These parameters include; slope percent, slope aspect, lithology, fault, roads, drainage catchment, elevation, vegetation and precipitation amount. Analytic Hierarchical Process (AHP) has been used to prepare and to cross the maps. The results show that about 26 percent of the slopes are situated in highly hazard zones. It was determined also that lithology and slope aspects play main role in occurring of the landslides in the study area.
 


N Salimi , M Fatemiaghda , M Teshnehlab , Y Sharafi ,
Volume 10, Issue 3 (2-2017)
Abstract

Landslides are natural hazards that make a lot of economical and life losses every year. Landslide hazard zonation maps can help to reduce these damages. Taleghan watershed is one the susceptible basin to landslide that has been studied. In this paper, landslide hazard zonation of the study area is performed at a scale of 1:50,000. To achieve this aim, layers information such as landslides distribution, slope, aspect, geology (lithology), distance from the faults and distance from rivers using artificial neural network-based Radial Basis Function (RBF) and perceptron neural network (MLP), has been studied. Principal of RBF method is similar to perceptron neural network (MLP), which its ability somewhat has been identified up to now and there are several structural differences between these two neural networks. The final results showed that the maps obtained from both methods are acceptable but the MLP method has a higher accuracy than the RBF method.


K Saberchenari, H Salmani, Ms Mirabedini,
Volume 11, Issue 4 (5-2018)
Abstract

Introduction
Landslides are natural events that one or more factors can effect in its occurrence that each of them plays a special role in this field. The hazard assessments of this phenomenon are a complicated problem due to the interference of the effective factors in its occurrence. The uncertainty that is due to ambiguous conditions of geology characteristics, hydrology, tectonics, land cover, rain, erosion, temperature fluctuations in the slope instability demonstrate the benefit of accurate methods in the study of slope instability. Since the prediction of the landslide occurrence is out of the power of current knowledge, identifying sensitive areas to landslide and ranking it can protect us from landslide dangers. According to preliminary estimates, annually 140 million dollar financial damages inflict by landslides over the country, while the loss of unrecoverable natural resources is not counted. In general, the ultimate goal of studying landslides can be found the ways that to reduce damages caused by them. Therefore, it is necessary to prepare the landslide hazard map.
The main goal of this research is landslide hazard zonation of Ziarat watershed using Dempster-Shafer. For this purpose, 13 modeling approach (using all factors and eliminating of individual factors) to prepare the hazard maps have used. Ultimately, the accuracy of the model has been evaluated using receiver operating characteristic (ROC) curves. The study area is one of the most prone areas to the landslide in the Golestan region. Sensitive lithology units, high diversity of topography and land-use changes have increased landslide susceptibility in this area. Therefore, investigation of effective factors in landslide occurrence and providing zonation maps to take management action in this area is necessary.
Material and methods
The study area is located in northern Iran, Golestan province. The Ziyarat watershed with an area of about 7800 hectares lies between longitudes 54º 10ʹ 13ʺE and 54º 23ʹ 55ʺE, and latitudes of 36º 36ʹ 58ʺN and 36º 46ʹ 11ʺN. At first, extensive field observations of the study area and aerial photos in 1:25000 scales have been used. So, a total of 50 sliding points are recognized and inventory map is produced (dependent variables). Then, 70% of total points (35 points) have considered for hazard zonation maps and 30% (15 points) for model validation.
In this research, twelve factors affecting (independent variables) landslide occurrence to provide hazard maps were applied. These factors include land-use, soil texture, geology, rainfall, slope, aspect, altitude, distance from faults, roads and rivers, stream power index (SPI) and plan curvature (CP). These factors can be divided into three broad categories which are topographical, geological and environmental conditioning parameters. The maps of these 12 factors have been produced using basis maps (DEM and Geology maps) in GIS software. The amount of Landslide density in each factor class have calculated from a combination of independent and dependent variables, and rating of classes have done based on Dempster-Shafer equations. Finally, the Landslide hazard zoning map has drawn from the summation of weighting maps in Arc GIS with 13 approaches. In this map, Value of each pixel is calculated by summing weight of all factors in that pixel. The pixel values are categorized based on natural breaks classifier into very low, low, medium, high and very high hazard zones. Then, an accuracy of zoning map has been evaluated by ROC.
Results and discussion
The result of effecting factors on landslide classification shows that Mobarak formation, forest and agriculture land use, areas with low distance from road and rivers, low altitudes, rainfall buffer of 550-650 mm, northwest aspect, clay-loam soil texture, areas with high stream power index, high slope amplitude and area with fault density lower than 2 km/km2 contain the most susceptibility to landslide. The result of model validation using ROC demonstrates that with eliminating lithology factor Dempster-Shafer model with 92.9% accuracy is located in the great class. Also, the model accuracy shows that with eliminating rain and altitude factors the model accuracy is decreased to 73.8% and 80.4%, respectively. So, these two factors were identified as the most effective factors in the occurrence of the landslide in the studied area. Based on the landslide zoning hazard map of the Ziarat watershed and landslide points (15 points) that are considered for model validation the 20, 40, 26.67, 13.33 and zero percent of landslides is situated in the very high, high, moderate, low and very low hazard classes.
Conclusion
In this research, susceptible areas to landslide in the Ziarat watershed have been mapped with the Dempster-Shafer model. For this purpose, 13 modeling approach to prepare the hazard maps have been used. The following conclusions are obtained from this study.
- The rain and altitude factors were identified as the most effective factors in the occurrence of landslide in the Ziarat watershed.
- Based on the landslide zoning hazard map of the Ziarat watershed 60 percent of landslides is situated in the very high to high hazard classes.
- The produced landslide hazard map is useful for planners and engineers to reorganize the areas which are susceptible for landslide hazard, and offer appropriate methods for hazard reduction and management. ./files/site1/files/0Extended_Abstract4.pdf 

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