Saeid Hamzeh; Afshin Amiri
Abstract
Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide ...
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Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide susceptibility maps provide important and valuable information,including time scale of possible future landslides, which are usedfor predicting landslide hazards. Since predicting the time of landslide occurrence is beyond the capability of science and knowledge, identifying areas susceptible to landslide and ranking them can extensively restrict the damages caused by landslide. Therefore, it is essential to zone landslide risk and identify factors affecting it. Analytic Network Process(ANP) is aGIS-based Multi-Criteria Decision Analysis(GIS MCDA) method successfully applied to many decision-making systems. The present study seeks to evaluate landslide risk and achieve a zoning map for the sub-basin under study using ANP and Weighted Overlaymethods. Materials and Methods Based on the literature and using different experts’ viewpoint, criteria affecting landslide risk were identified and five major criteria including topography, land use and land cover, geology, hydrometry and infrastructure were selected. The selected criteria include the following sub-criteria: slope, slope direction, curvature, elevation, lithology, soil type, land use, vegetation density, distance from roads, distance from habitat, river and drainage density and precipitation. The effective factor layers were standardized and a specific scale was defined for their units.Then, each layer was assigned a weight based on its role and importanceusing Analytic Network Process.Proposed to modify Analytic Hierarchical Process(AHP), this method (ANP) relies on the analyses of the human brain for complex and fuzzy problems.Network Analysis Process generally includes the following steps: determining indicators, criteria and options;classifying identified criteria into clusters and elements; determining the relationship between clusters, elements and options; performing pairwise comparisons between clusters, elements and options, and finally calculating the final weight of elements and options. UsingWeightedOverlaymethod, these elements were then integrated with their related coefficients and the final landslide risk map was obtained. Results and discussion Each criteria and sub-criteria were weighted using Analytic Network Processmethod.Topographic and land cover criteria had the most and hydrographic criteria had the least impact on the landslide occurrence. According to the final map, most landslides have occurred in eastern and southern slopes at an altitude of 500 to 2,200 meters. Moreover, 17/31% of the study area was located in the very high-risk class and 33% in the high risk class (about half of the area has high potential of landslide). Previous landslide data were used to assess the landslide zoning map results. Results indicate that most landslides have occurred in the high risk class (about 35% of landslides) and only about 4% of landslides have occurred in the very low risk class. Conclusion Landslide is one of the natural hazards causing serious harms and problems for human life. Identifying the factors affecting landslide and zoning its hazard is especially important for the identification of risky and susceptible areas.So, landslides were selected as one of the main topics of the study with the aim of controlling and managing its hazards.The ANP network analysis method was used to model and predict landslide risk in this research.Each criteria and sub-criteria were weighted and overlapped to producethe map of relative landsliderisk.The lowest risk was observed in the northern parts of the region, and the highest landslide risk was observed in the northern hillsides with higher humidity.WeightedOverlaymethod and network analysis model were effective in predicting landslide susceptibility and producing landslide zoning map.
Reza Aminataei; Sahar Akhavan; Amirhooshang Nezamivand chegini
Abstract
Extended Abstract Introduction Due to mainly mountanous topography, specific geographical conditions, various geological formations, neo tectonical activities, and seismicity, Iran is potantially prone to landslides.Gilan and Roudbar region in the southern part of this province are among areas potentially ...
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Extended Abstract Introduction Due to mainly mountanous topography, specific geographical conditions, various geological formations, neo tectonical activities, and seismicity, Iran is potantially prone to landslides.Gilan and Roudbar region in the southern part of this province are among areas potentially susceptibleof landslides, rock falls, and other events associated with seismichillsides. Landslide results in severe erosions and sometimes leads to financial losses or loss of lives. Therefore, it is important to investigate the causes behind this phenomenon and determinezones prone to land sliding. Materials and methods In this study, we tried to usea sample of trenches and boundaries offaultslocated inRoudbar sliding slopes in order to characterize the sliding soils. Following this field investigatation,soil samples were obtained from 10 landslide zones. Then, factors affecting the sliding slopes were identified and a digital map was produced for each factor. Nine data layers including direction and degree of slopes, geology, landuse, precipitation, relative changes in elevation, distance from roads, rivers and faults were used in GIS environment to prepare the weighted maps. Afterwards, LNSF statistical method was used for data analysis in GIS environment and the study area was divided into 5 zones with very low (1), low (2), moderate (3), high (4), and very high (5) sliding susceptibility. Following the integration and analysis of layers using LNSF model, 26 zonation mapswere calculated, and the best map was selected using success rate curves. Then, the zone with highest potentiality for landslide occurrence was selected for further studies from the five zones mentioned before. Hydrometry, Atterberg limits and direct shear tests were performedin the Soil Mechanics Laboratory of Gilan University with the aim of identifying physical and mechanical properties of soil samples. Results and discussion Results indicate that with LNSF method, it is possible tozone a vast area (12814.2 hectaresin this research) based on landslide potentiality and then focus on the most critical area (very high landslide potentiality) toinvestigate factors and conditions resulting in the occurrence of landslides or prevention strategies. Success rate charts helps us to determine the most optimal landslide zoning map (i.e. a map inwhich the highest percentage of landslide pixels occur in the “very high potentiality” zone). Following the selection of final zonebased on success rate graphs, from the 26 zoning maps, it was concluded that the landslide zone with very high potentiality encompasses 282.6825 hectares or 2.2% of the total area under study.At the weighting stage, the highest weight was allocated to the seventh category of the land use layer, which at the final zoning stage covers nearly the whole area with very high potantiality of landslides. Therefore, there is a direct relation between the allocated weight in the subject categories and the percentage of its occupancy level in the final zoning.Zoning the results of granulation experiments by Thiessen Polygon, it was concluded that CL type soil coversnearly half of the area with very high landslide potentiality. Determining the static reliability coefficient of the area with very high landslide potentiality, we found that in case soil reaches saturation, unstability of hillsidesin a large part of the study areacanbe expected. Conclusion Dispersion of landslides in Iran is mainly concentrated in Southern Gilan Province. Based on the investigation of the situations in the study area,geology, landuse, distance from highway are identified as the most affective factors in theoccurance of landslides.Following the weighting stage with LNSF method, rated layers were prepared in GIS enviornment, final overlapping was performed, and landslide zoning map of the study area was produced. Based on the landslide risk zonning map, the study area was divided into 5 subsections: 2.21% of the study area had very high sensetivity, 26.43% high sensetivity, 42.28% avarage sensetivity, 25.25% low sensetivity, and 3.83% very low sensetivity. Considering the zonning map produced, it properly overlaps with identified landslides in the area, and help governmental policy makings. It specifically helps Organization of Roads in construction of new roads.
Mohammad Fallah Zazuli; Alireza Vafaei Nezhad; Ali Asghar Alesheikh; Mahdi Modiri; Hossein Aghamohammadi
Abstract
Extended Abstract Introduction Landslide is one of the most important types of natural disasters,which endangers lives and financial security of many people and destroys environment and natural resources.With the present population growth and expansion of urban areas towardsteep areas and hillsides, ...
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Extended Abstract Introduction Landslide is one of the most important types of natural disasters,which endangers lives and financial security of many people and destroys environment and natural resources.With the present population growth and expansion of urban areas towardsteep areas and hillsides, landslide-related losses can be catastrophic. For an instance, landslides in Badakhshan Province in Afghanistan killed around 2,700 people in 2014, and a landslide in China (Shan’xiprovince)resulted in the disappearance of 64 people in 2015.Therefore, assessingthe possibility of landslides occurrence seems to becrucial. Providing zoning maps is one of the measures which makes identification of areas prone to future landslides possible. Inferences drawn from these maps can be used for land use planning, prevention of unauthorized construction activities, infrastructure development, refurbishment and restoration. Materials & Methods The present research selectsEast Rudbar-e Alamut (a district of Qazvin province), which is affected by landslides and instability of hillsides, as the study area. It takes advantage of Shannon entropy and information value models to develop landslide susceptibility map of the study areain GIS environment.Shannon entropy theory has been used in extensive researcheswith the aim of prioritizinginfluential factors in the probable occurrence of natural disasters such as landslide. Information value (IV) model is one of the statistical models drawn from information theory with a widespread application in the modeling of geological hazards and disaster risk assessment. Information value model aims to find a combination of significant factors anddeterminetheir impacton theoccurrence oflandslide in an area.To implement this model, relevant data and its related criteria maps were prepared. In this regard, the location of previous landslide events in the study area was determined based on the information received from Forests, Range and Watershed Management Organization. 49 landslides were identified in this way. Then, data was randomly divided into 2 categories: training data and validation data. Thus, 70% of data (35 landslides) were used to produce the models and the remaining 30% (14 landslides) were used for validation purposes. In addition to previous landslides, a collection of topographic, environmental and climatic characteristics of the study area including seven criteria of lithology, slope, distance from faults, land use, precipitation, slope-direction and elevation were selected as the most effective independent variablesto produce criteria maps with 30-meter spatial resolution. Basic information used to map these seven influential factors was obtained from Forests, Range and Watershed Management Organization, as well as the SRTM Digital Elevation Model (DEM), and used after some modifications. Considering the capability of ArcGIS in spatial data analysis, thissoftwarewas used to produce information layers and implement the models. Results & Discussion Prioritizing influential factors using Shannon entropy model introducesthree factors (i.e. land use, elevation and precipitation)as the most significant factorsin the occurrence of landslides in the study area. Factors of slope angle, distance from faults (almost equal to slope angle), lithology and slope-direction were in the next influential factors.Also, results of information value model indicate that looking from lithology perspective, the category of marl, calcareous sandstone, sandy limestone and minor conglomerate has an information value of 1 and thus, the highest probability of landslide occurrence. Category of basaltic volcanic rocks, along with category of well bedded green tuff and tuffaceous shale have the lowest probability of landslide occurrence with information values of -2.03 and -1.70, respectively.Only two categories of theslope angle criterionhave a positive-index. The highest information value (0. 93) in this category occurs in the class of 5-12 degrees, followed by the class of 12-20 degrees. The lowest information value occurs in slopes of more than 30 degrees. Based on this observation, it can be clearly concluded that the slope angles of 5 to 20 degrees are most prone to landslides. Distance to faults criterion indicate that the category of500 to 1000-meter distance to faultshave the highest information value (1.67). Regarding land use criterion, three land uses of garden, agriculture and garden-agriculture have the highest information values of 2.16 and 1.59 and 1.11, respectively. Regarding precipitation, average annual rainfall of less than 400 millimeters have the highest information value (1.50). Regardingslope-direction criterion, most landslides occur in southwest, south and eastdirections.Northeast, west, and northwest directions have the lowest probability of landslide occurrence, respectively. In terms of elevation, the information value is reduced as the height increases, and the maximum information value is related to the elevations of less than 1200 meters.After assigning a weight to each criterion and related classes, the landslide risk zone map was generated based on Shannon entropy and information valuemodels. The resulting zoning map produced based on natural breaks methods dividesthe area into five classeswith very high, high, moderate, low and very low risk. Resultsof Shannon entropy modelindicate that out of 14 landslides considered as the validation data, 3, 7, 2, 1, 1 landslideshave occurred in very high, high, moderate, low and very low risk zones, respectively. Resultsof the information value modelindicatethat 8, 4, 0, 1, 1 landslideshave occurred in very high, high, moderate, low and very low risk zones, respectively. Conclusion Evaluation of results using experimental probability index indicates that with 86% experimental probability,both models of Shannon entropy and information value are effective inidentification of landslide hazard in the East Rudbar-e Alamut region. Also, considering the number of landslides in very high and high risk zones, Shannon entropy and information value modelshave an experimental probability index of 72% and 86%, respectively, which prove higher efficiency of information value model. In Shannon entropy model, total area of very high, high and moderate risk zones covers 34% and 56% of the study area,respectively. In information value model,total area of very high and high risk zones covers 20% and 29% of the study area, respectively. Based on the landslide risk zone map, high and very high risk zones are mainly located in the west of the study area.
Reza Mansouri; Amir Safari
Abstract
Parts of the earth's crust have tectonic motions in the present time and will be susceptible to danger in the future. Therefore, geomorphologicforms are very sensitive to the tectonic activities and change by this movements. The assessment of tectonic activities using some quantitative indicators ...
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Parts of the earth's crust have tectonic motions in the present time and will be susceptible to danger in the future. Therefore, geomorphologicforms are very sensitive to the tectonic activities and change by this movements. The assessment of tectonic activities using some quantitative indicators plays an important role in identifying these activities and helpsto interpret the tectonic condition of the areas
Research Methodology: In this research, indices such as Stream length gradient index (SL), Valley floor-valley height ratio (VF), Asymmetric factor (AF), Topographic inversion symmetry (T), Drainage basin shape ratio (BS), and meanders of rivers (S)have been used to determine the tectonic activities in Frahzad basin in north of Tehran metropolis. The research method is based on the analytical method. The Physical and conceptual tools used in this research include the topographic and geological maps of the study area, satellite images and GIS software in the form of ARC GIS 10. Also, the quantitative results obtained during several stages of fieldwork were evaluated Discussion and Results: This basin, with an area of 35.8 kilometersis one of the sub-basins of the mountainous area in north of Tehran city which is considered to be an appropriate place to evaluate the relative tectonic activity due to the occurrence of the foothill processes (mainly sliding and falling). Farahzad River of this basin comes from the eastern heights of Imam ZadehDavood.
Conclusion: The results of the research indicate that the Farahzad basin is in active status based on the SL, VF, AF, T, SMF, EU, FD and S indices, and is only in Semi-active status based on the BS index.
The analysis of these quantities in general indicate the activity of this basin in the present time and the basinis classified in Class 1 based on the IAT(Index of relative active tectonics)index. These results are consistent with geomorphological evidences including landslide occurrence in the region.
Eghbal Mohammadi; Mamand Salari; Hiva Shirzadi
Volume 20, Issue 79 , November 2011, , Pages 58-60
Abstract
The major part of Iran's land is mountainous. One of the dangers that always threatens these areas is hillside instability. The occurrence of this phenomenon entails a great deal of damage to the hillside lands exploited by human beings every year. In this context, one of the most dangerous instabilities ...
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The major part of Iran's land is mountainous. One of the dangers that always threatens these areas is hillside instability. The occurrence of this phenomenon entails a great deal of damage to the hillside lands exploited by human beings every year. In this context, one of the most dangerous instabilities is the landslide phenomenon. Kurdistan province and specially the studied area (Baneh) as a part of the province, is one of the areas susceptible to landslide due to certain geological, topographic and climatic conditions along with human factors in some places. Gardaneh Khan, Savan, Sabadlu and finally Alut can be referred to as being amongst the most important of these landslides. Therefore, identifying the landslide process along with identifying, investigating and determining the causes of landslides in the regions of the country seems to be necessary. In this study, firstly, the nature of landslide phenomenon and their occurrence factors and then the introduction of landslides in Baneh city are discussed. At the surface of the study area, the role of lithologic factor such as sensitivity of loose formations, degradation of vegetation, fall of snow and rain, permeability, lateral digging of rivers with high flow rate, road construction, and proximity to the main faults (young Zagros fault and Piranshahr fault) are among the factors causing landslides.
