Geomorphology
Fariba Esfandyari Darabad; Ghobad Rostami; Raoof Mostafazadeh; Mousa Abedini
Abstract
In the current study, the risk of landslides in the Zamkan Watershed, located in Kermanshah Province, was evaluated. Two machine learning models, Support Vector Machine (SVM), and Logistic Regression, were used to prepare a landslide susceptibility map. Toward this, 13 informational layers including ...
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In the current study, the risk of landslides in the Zamkan Watershed, located in Kermanshah Province, was evaluated. Two machine learning models, Support Vector Machine (SVM), and Logistic Regression, were used to prepare a landslide susceptibility map. Toward this, 13 informational layers including elevation, slope, aspect, Melton ruggedness number, terrain convexity, stream length, valley depth, topographic wetness index, precipitation, geological formations, distance from rivers, distance from roads, and vegetation cover were utilized as independent variables. Approximately 70% of the watershed's landslide pixels were used for model training, and 30% for model validation. Model validation was performed using ROC curves. The results indicated the higher performance and accuracy of the radial basis function (RBF) kernel of the SVM model for generating landslide hazard maps in the study area. The area under the curve (AUC) for the RBF kernel was approximately 0.951 for model training and 0.944 for model testing. The results suggest that slope with a coefficient of 0.28, precipitation with a coefficient of 0.27, lithology with a coefficient of 0.26, and elevation with a coefficient of 0.22 are the main controlling factors for landslides occurrence in the Zamkan Watershed. Both the SVM model and logistic regression confirmed the deterministic effects of selected factors on landslides. About 35% of the study area as classified as highly susceptible to landslides, primarily in the eastern half of the watershed. Factors such as high elevation, steep slopes, heavy precipitation, and the Kazhdomi Formation's composition were identified as key contributors to this susceptibility.
Geomorphology
Gholam hassan jafari; zinab barati
Abstract
The analysis of some geological features and structures can be used to determine Quaternary developments. Analyzing the types of landslides, their density, and scale is the key to identify the evolution of landforms. Based on this, the current research was carried out with the aim of spatial analysis ...
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The analysis of some geological features and structures can be used to determine Quaternary developments. Analyzing the types of landslides, their density, and scale is the key to identify the evolution of landforms. Based on this, the current research was carried out with the aim of spatial analysis of landslides that occurred in different lithologies of Mo’alem-Kelayeh basin, a part of eastern Alamut basin, between the longitudes 50°26'00″ to 50°31'20″ and the latitude 36°22'00″ to 36°30'00″, based on topographical, geological conditions, vegetation, the condition of waterways, and the proximity of different rocks in the area. According to the results, the Karaj, Rute, Shamshek and Neogene and destructive sediments are the most erodible formations in the studied area, which are the most important factors involved in the occurrence of mass movements on a micro and macro scale under the Mo’alem-Kelayeh basin. The nonresistant lithology is more extensive in the geographical levels downstream of the rivers. In such areas, in addition to the loosening of the lithology in wide sections, the material and energy flowing in the river also increases, if due to the lower slope of the slopes, the effect of the river on movements of the slopes becomes more limited. In the terrestrial levels close to the ridge line, matter and energy are less and lithology is more resistant; But due to greater slope of the slopes and the involvement of physical weathering in the porosity of rocks, the effect of river on the occurrence of surface slope movements increases.
Geomorphology
leila aghayary; sayyad Asghari Saraskanrood; Batool Zeynali
Abstract
Text Landslides are one of the types of large-scale processes that cause many human and financial losses in many parts of Iran and the world every year. The increase in population and the expansion of human settlements in mountainous areas, the difficulty of predicting the occurrence of landslides ...
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Text Landslides are one of the types of large-scale processes that cause many human and financial losses in many parts of Iran and the world every year. The increase in population and the expansion of human settlements in mountainous areas, the difficulty of predicting the occurrence of landslides and the numerous factors influencing the occurrence of this phenomenon, reveal the necessity of landslide risk zoning. Identifying the effective factors in the occurrence of this phenomenon and its risk zoning is one of the basic and practical methods to achieve its forecasting, control and monitoring solutions. By using field studies, geological and topographical maps, and by reviewing the researches and studies done in this field, as well as examining the existing conditions in the studied area, 9 factors of elevation, slope, slope direction, lithology, distance from the fault. , the distance from the river, the distance from the communication roads, land use and rainfall were investigated as factors affecting the occurrence of landslides. Therefore, the purpose of this research is to investigate and analyze the most important factors involved in creating the risk of landslides in Garami city and to identify the prone areas that will probably be involved in landslides in the near future. In this research, the zoning of prone areas was done with the Aras multi-criteria algorithm in the Edrisi software environment, and according to the results of landslide risk zoning; The criteria of land use, slope, and lithology are the most important factors involved in creating the risk of landslides in the study area with weight coefficients of 0.187, 0.152, 0.152, and 0.142, respectively, and are 361.99 and 450.32, respectively. A square kilometer of the area has a very high probability of danger. Finally, it can be said that the most important factor involved in increasing the amount and potential of landslides in Germi city is the change of land use and the increase of agricultural land and livestock pastures.
Hydrogeomorphology
Alireza Ildoromi; Mehdi spehri
Abstract
In this researchlandslide sensitivity was zoned using statistical models intheKurdistan Dam watershed and the most appropriatemodel was introduced.First, the studied area was determined and with field observations, the number of 9 landslides was recorded and a landslide distribution map was prepared. ...
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In this researchlandslide sensitivity was zoned using statistical models intheKurdistan Dam watershed and the most appropriatemodel was introduced.First, the studied area was determined and with field observations, the number of 9 landslides was recorded and a landslide distribution map was prepared. In the next step, the factors affecting the occurrence of landslides including geology, rainfall, land use, distance from the river, distance from the fault, slope and height were identified and then a map of these factors was prepared. To determine the rateof each of the effective factors in the occurrence of landslides, the map of each information layer of the effective factors is integrated with the distribution map of the landslide and using AHP, BWM and FUCOM statistical modelsseparate information layers are weighted and By overlapping different layers, the final landsliderisk zoning mapswere prepared and compared.The results showed that land use in AHP and BWM methods and rainfall lines, in addition to land use inFUCOM method have the greatest effect and the criteria of heightdistance from the fault and slope respectively in the three AHP, BWM and FUCOM methods have the least effect on the occurrence of landslidestheresults showed that the lithological variable has a great role on the occurrenceof landslides in the studied area.In generalthe results showed that in AHP and BWM methods, the numberof required pairwise comparisons increases significantly with the number of compared parameters, and in this case, the uncertaintyof opinions increases, which shows the superiority of the FUCOM method over It showswell in other ways.
Mohamad Sharifi Paichoon; Kourosh Shirani; Mayedeh Shirani
Abstract
1-Introduction Landslide as a process of change in the stress-strain state of a slope occurs under the influence of natural and human parameters leading mass separation and its movement to down slopes. However, the relationship between the sliding mass and the slope remains constant. Accordingly, the ...
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1-Introduction Landslide as a process of change in the stress-strain state of a slope occurs under the influence of natural and human parameters leading mass separation and its movement to down slopes. However, the relationship between the sliding mass and the slope remains constant. Accordingly, the mechanism of formation and development of a landslide is a systematic sequence of changes in the stress-tension state of a slope influenced by natural and anthropogenic parameters. This event is destroying human settlements and infrastructures and causing financial losses and many deaths around the world annually. The rapid population growth in the last half-century, the expansion of settlements towards steep mountainous areas on the one hand, and the false human being intervention in the destruction and changes of slopes, on the other hand, increased the frequency of landslides and this has led to an increase in damages. Iran has favorable natural conditions for a wide range of landslides with mainly mountainous topography, high tectonic and seismic activity as well as diverse climatic and geological conditions. Therefore, landslide studies on understanding factors and parameters affecting it, and identifying high risk and vulnerable areas in the world as well as in Iran have received serious attention. This research mainly aims to investigate the parameters affecting the landslide in the Vahregan catchment which located in the Sanandaj-Sirjan construction zone. Where metamorphic rocks, marl and shale, as well as wide area of quaternary sediments, have provided very favorable conditions for landslide occurrence. 2-Methodology Multiple linear regression method was used to perform this research. Thus, the scatter map of the landslides of the region as dependent variable and twelve factors includes elevation, slope, slope direction, lithology, fault, precipitation, drainage network, road, land use, vegetation, TWI and SPI as independent variables were considered. To prepare landslide distribution map of the study area, aerial photographs of 1994 with a scale of 1: 40,000 were used and interpreted. Accordingly, the landslides area and their location in Google Earth software were determined. Then, 138 landslides occurred in the Vahregan catchment were determined with field studies, with the help of available maps and information, and the use of GPS system. It was then mapped using GIS software. After converting all the factors to information layers in GIS, these layers were adapted to the scattering map of the landslides of the region and were calculated the percentage of region located within the landslide area for all factors. 3-Results and Discussion The results showed that the most effective factors in Vahregan catchment landslides based on multivariate regression method are distance from road, lithology, precipitation, land use, slope direction, distance from drainages, distance from faults, SPI drought, elevation, slope and TWI, with coefficient of 0.851, respectively. Their coefficient of R is 0.851 which is acceptable. The results showed that although natural factors can alone cause landslides, human factors are currently the most important parameters in causing landslides in the study area. Accordingly, most new landslides occur in close proximity to roads. In other words, it can be said that the downstream cutting of slopes by human being has increased the frequency and magnitude of landslides. Therefore, results showed that the road with 0.411 standard coefficient was the most important factor in creating landslide so that much of the landslide has occurred within less than 3 km of roads. Then, the natural factors includes lithology and precipitation with a standard coefficient of 0.362 and 0.299 and land use with a standard coefficient of 0.286 played the most role. However, vegetation factor and the TWI index with a standard coefficient of 0.103 and 0.127, played the lowest role in the landslides of the Vahregan catchment. According to the final landslide zoning map, more than 50% of the area has located in a high risk area. 4-Conclusion The study area has great potential for landslides in terms of natural features such as lithology, precipitation, elevation, Permanent River, and slope. The landslide map with 382 landslides indicates this. However, in the last two to three decades, environmental changes such as drought and consequently changes in vegetation covers on the one hand, and false human intervention, including the construction of multiple roads and the geometrical change of slope, on the other hand, have increased the frequency and magnitude of landslides in the studied area. The results of the final mapping showed that more than 50% of the basin is in high and very high risk areas. Accordingly, special attention should be paid to the extent of landslide risk and its threat in all human activities, especially environmental planning and management.
Sayyad Asghari; Rasool Hasan zadeh; Soheil Raoofi
Abstract
1-Introduction Instability of natural slopes is one of the geological and morphological phenomena that has a significant role in changing the form of surface of the earth, and when it affects human activities, it can become a dangerous phenomenon (Esfandiari, 2006: 113). Landslides as geological events ...
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1-Introduction Instability of natural slopes is one of the geological and morphological phenomena that has a significant role in changing the form of surface of the earth, and when it affects human activities, it can become a dangerous phenomenon (Esfandiari, 2006: 113). Landslides as geological events related to the transportation of soil / heavy rock materials and assessment of its sensitivity, is an important task for local authorities to plan and reduce the land (Xialong Deng, 2017: 2). Therefore, many attempts have been made to assess the dangers of mass movements, and it is suggested to have its reduction methods based on the key characteristics of the slip, including scope and extent, volume, startup mechanism and recurrence, and subsequently, make decisions (Kuo Jeong Chank et al., 2018: 700). (Hemati and Hejazi 2017: 24-7) evaluated the landslide hazard zonation of Lavasanat watershed using logistic regression statistical methods and the result was stated in this way that in the studied area, areas with high risk of zoning, had a large share of the area amount of the region. Aliabad basin with the southwest - northeast trend in the geographical coordinates of - located in the east and - located in the north latitudes of the northeast of East Azarbaijan Province and southeastern part of Horand County.(Figure1) Figure (1): Geographic location of Aliabad watershed 2-Methodology 1- Topographic map (1: 50000) and geological map of Kaleybar region (1: 100000). 2- Landsat satellite images of 8 OLI sensors 3- GPS devices 4- Maps of the faults, slopes, isohyet, isotherm, evaporation, land use, elevation and hydrology 5- Envi 5.3 software 6- Statistical software of SPSS, version 16. For zoning the risk of rock falls, nine layers of information including slope, hypsometry of the region, isohyet, isotherm, evaporation, distance from the fault, distance from the river, land use and lithology were used as independent variables and to prepare the layers in Arc GIS, 1,500,000 topographies and 1.100000 geology maps were utilized, and Landsat 8 satellite imageries were used with the OLI sensor to produce the land use layer. So, after preparing the considered data, the layers were classified as raster, and in their descriptive table, a column called the standard weight was added and the classes related to each layer were calculated using a sum ranking method. In this research, the rock fall layer was considered as the dependent variable and the 9 presented layers were considered as independent variables and all layers had been evaluated in the normalization of the weight between zero and one per pixel; based on the proportion table method, each layer, having 500 weighted pixels that overall included 5000 pixels, was entered into the SPSS environment and regression analysis was performed thereof. Independent variables, including 9 variables, consisting of three PhDs in geomorphology and two Phd in geology were selected based on exports opinions considering their importance in creating and strengthening the dependent variable were weighted between zero and one numbers. 3-Results and Discussion The Chi square test for each of the independent variables, separately, showed that there was a significant relationship between the independent variables and the dependent variable, and the effects of these variables on the dependent variable was acceptable. The numerical value of R was 0.953, and if the R value was closer to one, it would indicate the high validity of the test. The numerical value of the coefficient of determination of the independent variables relative to the dependent variable was 0.909, which indicated the high validity of the significance of the test, because it was closer to number one. Of course, it is clear that the value of the determination coefficient in Pseudo R Square was determined to be good, so the adjusted coefficient of determination was considered whose numerical value was 0.907. These findings indicated that roughly 90 percent of rock falls occurred in the Aliabad basin have been affected by these 9 estimated independent variables. Given that the statistical analyzes confirmed the validity of the effects of independent variables on the dependent variable according to the weightings of the experts in terms of zero and one for each variable as well as the importance of the variables in relation to each other as a binary comparison, the zoning of the risk of rock fall for the Aliabad watershed of the Horand basin was done using Arc Gis software, and in this zonation, five falling risk classes were used including very high, high, medium, low and very low . 4- Conclusion lithology and the distance from the fault and river and foot slopes were the most important factors in the formation of rock falls since the drainage system of the basin exactly followed the fault zone. The reason for this issue can be analyzed in the way that the longitudinal distance of the highest parts of this region, from the basin to the Aliabad River was lower, which has caused the slope of the basin to perform deep slices to achieve a balance in the slopes and hydrology. The southern parts of the basin are considered as one of the most susceptible basins in the geomorphologic phenomenon of rock falls and destructive cones due to the existence of alluvial formations and the lack of proper slopes and the relative reduction of the fault to the northern and eastern parts despite having significant heights and very low and low status of zonation in the risk of rock falls, and in the southwestern part of the basin, a presence of rocky outcrops in the presence of permeable cones has been also observed. This issue should be addressed to the authorities in order to avoid serious damages to the lives of the inhabitants of the basin, so that the potential risks of this phenomenon could be controlled as much as possible including: threatening communication routes and threatening rural villages and damaging electrical and telecommunication facilities, therefore, infrastructure solutions should be applied in this regard.
Mehdi Teimouri; Omid Asadi Nalivan
Volume 6, Issue 21 , March 2020, , Pages 155-179
Abstract
1-IntroductionThe main objective of this research is to prioritize the factors affecting the occurrence of landslide and its susceptibility zoning in Lorestan province using the maximum entropy and MaxEnt models. To do this research, 11 factors affecting the occurrence of landslide including height, ...
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1-IntroductionThe main objective of this research is to prioritize the factors affecting the occurrence of landslide and its susceptibility zoning in Lorestan province using the maximum entropy and MaxEnt models. To do this research, 11 factors affecting the occurrence of landslide including height, slope, aspect, surface curvature, distance from the stream, fault and road, lithology, land use, rainfall, and topographic humidity index have been used. In this research, 30, 40, 50, 60 and 70 percent of landslides were evaluated for validation to determine the sensitivity and accuracy of the model. For evaluation of the model, the relative recognition function curve (ROC) was used. From the total of 176 landslides, 70% of the data was used as the test data and 30% as the validation data using Mahalanobis distance method and the accuracy of the model in the testing and validation stages based on the curve level was reduced. The results showed that 35.5% of the province of Lorestan has a landslide sensitivity. Based on jackknife diagram, rainfall, distance from road, lithology and land use layers were the most important factors influencing the sensitivity of landslide. The AUC level based on the relative function recognition curve indicated a 90% accuracy (excellent) of the maximum entropy method at the training stage and 83% (very good) at the validation stage to determine the landslide susceptibility. The results of this study will be suitable for provincial administrators and managers in order to land planning and reduce the damage caused by landslide occurrence.Mass movements, including landslide, is one of the most important issues in natural hazards, because its occurrence can cause many human and economic losses, especially in mountainous areas (Symeonakis et al., 2016). Regarding the destructive effects of landslides on natural resources, as well as human habitats and erosion of significant volumes of valuable soils, the identification of susceptible areas and zoning of potential occurrence or landslide susceptibility is vital and very important (Zhang et al., 2019). In recent years, the use of GIS and remote sensing along with machine learning methods has created a new step in the zoning of landslide occurrences. Lorestan province is a vulnerable area to landslide hazard due to the mountainous and wetness conditions. Therefore, the main objective of this research was to prioritize the factors affecting the occurrence of landslide and its susceptibility zoning in Lorestan province using the maximum entropy and MaxEnt model.2-MethodologyLorestan province with an area of 2829612 hectares is one of the major provinces in the west of the country. To do this research, 11 factors affecting the occurrence of landslide including altitude, slope, aspect, surface curvature, distance from the stream, fault, and road, lithology, land use, rainfall, and topographic humidity index have been used. The required maps were prepared using GIS and RS techniques. In this research, 30, 40, 50, 60 and 70 percent of landslides` division were evaluated for validation to determine the sensitivity and accuracy of the model. For evaluation of the model, the relative recognition function curve (ROC) was used. Using Mahalanobis distance method, from the total of 176 landslides, 70% of the data was used as the test data and 30% were utilized as the validation data for having the best classification. The difference of the current research with other similar studies was that in this study, use was made of Mahalanobis distance method for classification of validation data and training instead of random classification. The Mahalanobis distance helps to classify data richness and prevents random selection of points for validation. Maximum entropy method (MaxEnt model) is one of the methods of machine learning and one of the main advantages of MaxEnt model is the ability of this model to identify the most important variables and sensitivity analysis of variables using Jackknife method, which has been investigated in the current study.3-ResultsThe results showed that 35.5% of the province of Lorestan had landslide susceptibility. Based on Jackknife diagram, rainfall, distance from road, lithology and land use were, respectively, the most important factors influencing the susceptibility of landslide. The AUC level, based on the relative function recognition curve, indicated 90% accuracy (excellent) of the maximum entropy method at the training stage and 83% (very good) at the validation stage to determine the susceptibility of landslide occurrence.4-Discussion and conclusionLandslide is considered as one of the most dangerous natural disasters in the world. In this study, taking into account the affective environmental and human factors, and using the maximum entropy method, the map of landslide susceptibility of Lorestan province was prepared. The results showed that factors such as rainfall, distance from the road, lithology, land use, distance from the fault and slope were the most important factors influencing landslide susceptibility with the participation of over 60%, regarding which, land use management and road construction principles need human activity interventions. The drawn ROC curve showed that the accuracy of the model in the estimation of landslide susceptibility regions both in the stage of the test and in the validation stage was excellent and very good, which meant the excellent performance of the model. According to the obtained results, it can be said that MaxEnt model had a high ability to determine areas with landslide susceptibility and due to the speed and accuracy of the model,it is suggested that in similar researches, especially in developing countries, due to the lack of facilities and financial resources, as well as the time consuming of identifying areas with landslide susceptibility, it can be used. In addition to natural factors, some human factors such as road construction, play an important role in the occurrence of landslide, which requires avoiding ecosystem change as a disaster risk factor to reduce relative risks. The results of this research can be applicable to the decision making and management of provincial lands as well as urban planning, and they can have a significant role in preventing and reducing the damage caused by landslide.
Asad'ollah Hejazi Hejazi; Zahra Zanganeh Tabar; Zahra Zamani
Volume 6, Issue 20 , December 2019, , Pages 121-140
Abstract
1-IntroductionMaterials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around ...
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1-IntroductionMaterials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around the world in different parts of the country. The rapid population growth, the expansion of cities in mountainous areas, the difficulty of predicting the occurrence of landslide events and the multiple factors affecting this phenomenon reveal the necessity of zoning the risk of landslide. Since prediction of the precise time of mass movements is very difficult, identification of these areas is very important (Mosafaei et al., 2009). Using the zoning of the risk of a landslide event, it is possible to identify vulnerable areas with potential risk, and by providing appropriate management approaches and techniques, to some extent prevent the occurrence of landslides or damage caused by them reduced. Accordingly, the purpose of this study is to identify areas susceptible to landslide in the Sarpolzahab Basin. The Sarpolzahab Basin is one of the mountainous regions of the western part of the country which is prone to various types of slopes due to special geomorphological conditions. In this research, for the potential estimation of areas susceptible to landslide, two models of WLC and OWA for zoning and an analysis of the network (AHP) model for weighting into layers have been used.2-MethodologyThe research methodology is based on software, library and analytical methods. In this research, eight layers of information were used to identify landslide susceptibility. Information layers include: 1 elevation, 2 slopes, 3 slopes, 4 rivers, 5 faults, 6 lithology, 7 communication paths and 8 land use areas. The general trend of the present research is that in order to identify the susceptible landslides, information layers were first provided (the choice of information layers was based on the purpose of the research and according to the experts' opinion), and then these layers were based on the opinion of the experts (5 geomorphologist) and using the network analysis model (AHP). After weighing the information layers, the weight is applied to each of the layers, and then, in order to combine and combine the information layers, three methods of fuzzy logic, WLC and OWA have been used.3- ResultsIn this research, in order to achieve the desired goals, information layers are first provided. After providing information layers to combine information layers, layers are standardized using fuzzy area. Layer standardization is based on expert opinion and research objectives. For layers of elevation and gradient, gradient and high-lying areas of value near 1 and low-gradient and low-lying areas are considered to be close to zero. For layers of slope directions, the northern directions are worth close to 1 and the southern directions are close to zero. Also, areas near the lines of the fault, the river and the communication path are worth close to 1 and the distant areas are close to zero. For the land use, the uncovered areas are close to 1, and areas with dense vegetation are close to zero. For the lithology layer, areas with low resistance to lithology such as marl, lime and alluvium have a value of close to 1, and areas with more resilient lithology (basalt areas) are close to zero. 4- Discussion and conclusionThe results of this study indicate that the studied basin has high potential for slippery slopes movement. In fact, the existence of hurdles and the availability of other parameters have led to a relatively large and large part of the eastern basin. Comparison of potentiometric methods suggests that in all three methods, the eastern regions have the highest and western regions with the least potential for landslide occurrence. In the fuzzy logic method, the potential class has the highest potential of 195 km2, and the average potential class with the 121 km2 has the smallest extent, which mainly includes the western regions and the outlet of the basin. In the OWA method, the relatively large potential floor area has a maximum area of 210 square kilometers, which mainly includes the central and eastern heights of the basin. In this method, the high potentiality class with the area of 116 km has the lowest status, and mostly you are the northern and central areas of the basin. In the WLC method, the relatively high potential class with 180 and a high potential floor area of 120 km2 has the highest and the smallest extent.
Mahsa Ariapour; Mehdi Bashiri; Ali Golkarian
Volume 6, Issue 19 , September 2019, , Pages 57-77
Abstract
Introduction Mass movement, according to their nature, variety, hazards for human lives, and properties, have always been a matter of interest to various scholars. Considering that the occurrence of this phenomenon has a complex mechanism and complex factors and variables can affect it, extensive studies ...
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Introduction Mass movement, according to their nature, variety, hazards for human lives, and properties, have always been a matter of interest to various scholars. Considering that the occurrence of this phenomenon has a complex mechanism and complex factors and variables can affect it, extensive studies to identify the effective factors, classification, zoning, and modeling of this process have been conducted. In this study, landslides of three watersheds in the southeast of Neishabour city were investigated and the hazard zonation map was prepared, using bivariate statistical methods of the information value and area density. There are few studies regarding the application of different data mining methods to determine the effective variables in the occurrence of landslides and most studies are based on other statistical methods. Data mining is called as knowledge discovery in databases and is a way to discover new and beneficial information through a lot of data. Some of the most important data mining algorithms include the decision tree, random forest, boosting aggregate demand, support vector machine, logistic regression, and neural network algorithm. The data mining extracts useful information from large volumes of data and has shown a good performance. Therefore, the aim of the present study was to prioritize Methodology The present study aimed to investigate the factors affecting the occurrence of a landslide and its zoning in three watersheds including Kharv, Harimabad and Grineh watersheds in the Razavi Khorasn province. First, 99 landslides were identified in the area and the landslide distribution map was prepared. Then, all effective factors on watershed landslides, in 15 information layers including the altitude, slope, aspect, climate, land use, pedology, vegetation cover, geology, evaporation, temperature, rainfall, land type, distance from road, distance from fault, and distance from river were digitized in the ArcGIS environment. Then, using data-mining algorithms in R software, the preferable algorithm and effective factors on landslide occurrence, were introduced. Finally, the landslide hazard zonation in the GIS software was done using bivariate statistical models. Results The results showed that the random forest algorithm with an accuracy of 92% is the best one and the variables of geology, climate, aspect, distance from road, altitude, pedology and land type are the most important variables in algorithms modeling. The most probability of occurrence of watershed landslides placed in areas with west and northwest directions, slopes higher than 30 degrees, dominant type of the environmental factors affecting the occurrence of a landslide including the altitude, slope, aspect, climate, land use, pedology, vegetation cover, geology, evaporation, temperature, rainfall, land type, distance from road, distance from fault, and distance from river using data mining algorithms, zoning its sensitivity, and bivariate statistical models of information value and area density in three watersheds including Kharv, Harimabad, Grineh watersheds in Razavi Khorasan province. mountains, the semi-humid climate, 1500 to 2000 mm evaporation class, entisols, dense vegetation, the gardens, bushes and shrubs land uses, being close to the roads and faults and being far from the rivers, and the altitudes of 2000 to 2500 m with the phyllite, boulders and sandstone formations. The results of the zoning map evaluation using the information value and density area methods showed that 45.45% and 55.55 % of landslides were respectively located at the high and very high risk zones and the rest were in very low, low, and moderate risk zones. As a result, in both methods, most of landslides were in the high and very high risk zones that indicated the suitable accuracy of the model. Discussion and Conclusions According to the results of this research, variables including the geology, climate, aspect, distance from road, altitude, soil science, and land type were considered as the most important factors in the occurrence of a landslide. In addition, factors such as slope, land use, vegetation cover, distance from fault and distance from river were identified as the most important factors influencing the development of landslide and classified as natural factors, which could be influenced by human factors. The comparison of two mentioned methods showed that the area density method was more appropriate than the information value method for the study area.
Mehdi Bashiri; Seyedeh-Maedeh Kavousi Davoudi; Ali Afzali
Volume 5, Issue 14 , June 2018, , Pages 157-178
Abstract
Introduction
The mass movement of materials on steep slopes under the influence of gravity and motivation factors such as earthquakes, floods and torrential rains called landslide. Landslide similar the other natural phenomena is an important natural disaster that occur every year in the mountainous ...
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Introduction
The mass movement of materials on steep slopes under the influence of gravity and motivation factors such as earthquakes, floods and torrential rains called landslide. Landslide similar the other natural phenomena is an important natural disaster that occur every year in the mountainous and highland areas of our country. By risk assessment of landslide occurrence, the sensitive areas with a high potential risk can be identified. Also the effect of different environmental factors on the pattern of high-risk areas can be used in risk management, practically.
Methodology
One of the basic measures for achieving methods for mass movements control and management is identifying the effective factors in occurrence of this phenomenon. Also, in countries involved in the landslide, there is an increasing tendency for risk and damage assessment of this phenomenon. Therefore, at the present study, using fractal geometry, the effects of land use, geology and geomorphology on the landslide patterns were evaluated in the Tooye-Darvar watershed, Semnan province. Because the fractal theory studies and recent reviews in the earth science indicate that some geological processes such as mineralization, sedimentation, deposition, volcano, morphology and etc have self-similar characteristics. First, using aerial photo interpretation, field surveying and recording the position of landslides using GPS, the landslide distribution map prepared. Then, information layers for each slope, aspect, elevation, geology, geomorphic units, soil erosion class, distance from fault, distance from road, distance from stream and land-use factors prepared.in the ArcGIS software environment using digital elevation model (DEM) of the region with a pixel accuracy of 20 meters. Also the landslides information layer prepared according to the field studies and rasterized. Then, different layers overlapped and table of combined properties for merged layer includes the information of each pixel, extracted and entered into the Excel environment. In Excel, the relative importance (or frequency ratio) calculated for each different class of information layers.
Statistical analysis
After collecting and recording data and creating the database, the SPSS v.23 used for data analysis. In the first stage, the normalization checked using Kolmogorov-Smirnov test at the 5% confidence level. Then, the effect and significance of each measured variable investigated in landslide occurrence.
Calculating the fractal dimension
The landslide areas available in each unit extracted as a polygon and the resulting image transmitted to the Fractalyse software and its fractal dimension calculated using box-counting method. Then, the fractal dimension of landslides placed in work units transferred to the SPSS environment and statistical comparison performed with the aim of investigating the geometric or morphologic differences of sliding zones in different land uses and geologic and geomorphic units. Then to compare the different landslide hazard classes, the density or compression ratio of landslide used in each hazard class. The density ratio calculated by dividing the landslide density in a particular hazard class to the average density of landslides based on the area density or the number of landslides.
landslide susceptibility zonation
In order to zonate the landslide susceptibilityusing bivariate statistical methods, the information value and the area density, each of the factors affecting landslide occurrence include slope and elevation maps, slope aspect, soil erosion class, geomorphic type, geological unit, land use, distance from the stream, distance from the road and distance from fault in GIS environment digitized and classified. Then, based on the two above mentioned methods, the weight of each factor and its related classes determined. The weighted maps of effective factors combined and using natural breaks method, the obtained maps classified in very low, low, moderate, high and very high hazard classes. In order to evaluate the implemented model in the region , 2/3 of landslide points and 2/3 of landslide areas used for modelling and the remaining 1/3 of each one used to evaluate the model.
Discussion
The results of fractal dimensions study in 146 landslide areas using box counting method showed an average of 1.987. Study of the spatial features in landslide areas include landuse, slope aspect, soil erosion class, geological unit, geomorphic type, height and slope class, distance from road, distance from fault and distance from stream showed that only the effect of geomorphic types on geometric dimension of landslide areas is significant and this significance is caused by high difference (sig=0/000)between mountains and plateaus and upperterraces types. Finally, the density ratio for landslide areas and points in each class of spatial characteristics for landslide occurrence, calculated and the effects of these variables on landslide occurrence severity, presented and analyzed. Also, in the landslide susceptibility zonation about 1/2 of landslides located in the high and very high risk classes that indicates the high potential for landslide in this region.
Conclusion
The results showed that the surface erosion has no significant effect on occurrence of large landslides but it has affected the landslide points. Also, the presence of marl and lime in study area that is a geological unit susceptible to dissolution can be effective in landslide occurrence. Geomorphologically, the mountain and hill types have been effective, which could be due to the high slope of these types. In the case of landslides occurrence in the vicinity of roads, faults and streams, it can be concluded that the small landslides has been affected by road, but it has no significant effect on the occurrence of large landslides. But the existence of fault in the area and proximity to the fault led to the occurrence of extensive landslides. Finally, the presence of stream in the area has also been effective in occurrence of large landslides, but the landslide points, has not been affected by existence of stream in their buffers. Also, high potential for landslide in the study area represents the being endangered for regional installations, agricultural lands, engineering structures and buildings.
Abolghasem Amir Ahmadi; Mahnaz Naemi Tabar; Bahar Gholkar ostadi
Volume 4, Issue 11 , September 2017, , Pages 105-125
Abstract
Absract:
Introduction
Landslide is one of the natural phenomena causing many financial losses and casualties in Iran every year (Kamranzadeh, 2014: 101). This phenomenon occurs when the force of materials’ weight is higher than the shear strength of the soil shear force (Memarian et al. 2006: ...
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Absract:
Introduction
Landslide is one of the natural phenomena causing many financial losses and casualties in Iran every year (Kamranzadeh, 2014: 101). This phenomenon occurs when the force of materials’ weight is higher than the shear strength of the soil shear force (Memarian et al. 2006: 105). The Shannon entropy is a function of probability distribution and standard for measuring uncertainty in the information content of a parameter, and by considering occurrence frequency of subgroups of that parameter, it shows heterogeneity level. As a result, it calculates the effect of each parameter on the results of the system (Hosseinpour Mil Arghadan et al. 2014). Objectives of the present study are the selection of criteria and standards, preparation of digital factors layers, preparation of the landslide hazard zonation map, diagnosis of high risk points via the Shannon entropy, presentation of strategies appropriate for preventing possible risks and solutions to reduce damages in the study area. Bajgiran is the central district of Bajgiran County and a part Doulatkhaneh Rural District of Ghouchan Township. According to climate divisions, Bajgiran has a moderate mountainous climate. Geologically and structurally, it is a part of Kopeh Dagh Sedimentary Basin. In terms of stratigraphy, outcrops from the Jurassic rock units to the present era can be observed in the study area.
Materials and methods
In the present study, first of all factors affecting the occurrence of landslide including height, precipitation, slope, slope direction, slope shape, distance from the waterway, distance from the road, distance from the fault, land cover and lithology were identified as factors affecting the occurrence of landslides, and the mentioned maps were digitized in GIS. to this end, using the topographic map on a scale of 1:50000, the Digital Elevation Model Map (DEM), factors of slope degree, slope direction, slope shape, height level, distance from the waterway, and distance from the road were prepared. Using the land-use map on a scale of 1:25000, information layers of land use were extracted. To draw the lithological map, the distance from the fault of the geological map on a scale of 1:50000 was used. To draw the precipitation map, statistics of the rain gauge stations of five Daroungar, Mohammad Taghi Beig, Aman Gholi, Kikan, Hey Hey Ghouchan, and Bahman Jan Stations were used. The information content available in the decision matrix in entropy process is calculated via equation 1:
Equation 1: Ej = -K
Where Ej is the entropy value and Pi,j is the decision matrix.
Equation 2: Pij =
Where rij is the value or the special score assigned to each layer.
Equation 3: K= (lnm)-1
Where k is the fixed coefficient and m is the number of landslides.
After the formation of the decision matrix and extraction of the value of Ej, the value of Vj can be calculated via equation 4:
Equation 4: Vj = 1- Ej
Where Vj is the deviation degree of uncertainty.
And finally, to calculate the final weight of all factors (Wj), equation 5 is employed.
Equation 5: Wj =
To prepare the final map, equation 6 is used:
Equation 6:
Where Hi is the landslide hazard occurrence coefficient, Wj is the final weight of all factors, rij is the weight of each factors (Moghimi et al. 2012: 82).
Results and discussion
After converting criteria into integers and the formation of the initial matrix, the value of Pij was calculated via equation 1 and the value of K was calculated via equation 2. To calculate Ej for each criterion, equation 2 was used. The results are indicated table 2. In this equation, the value of E which is a function of n, for each n where Pi is equal, the value of E becomes maximum which is statistically calculated via probability distribution of Pi. Then, uncertainty or degree of deviation of each criterion (dj) obtained from the fraction of the value of Ej from 1 were calculated per each indices effective on landslides of the study area (table 2). After that, using equation 5, the weight of each parameters used in the entropy matrix of landslides (Wj) including height (0.02113), precipitation (0.031142), shape of slope (0.0116110), slope (0.011342), distance from the waterway (0.045161), distance from the road (0.113401), distance from the fault (0.099871), land use (0.997110), and lithology (0.095148) were obtained. Therefore, the regional model of the landslide hazard degree in the area was obtained via equation 6. Hi is the landslide hazard degree in the area (equation 7).
Conclusion
The aim of the present study was to prioritize factors affecting the occurrence landslides and zone their sensitivity in Bajgiran Region via the Shannon entropy. The results of the study shows that the most important factors affecting landslides in the study area are slope layers, slope direction, lithology, distance from the fault, and height. After weighting parameters and formatting the entropy matrix, the zonation mapping were conducted. To this end, information layers were prepared in Arc GIS and converted into Raster formats. With regard to zoning maps obtained from the entropy model, 15 landslides have occurred in the area among which 9 landslides have occurred in a high risk zone (42%), 4 landslides in a moderate risk zone (31%), and 2 landslides in a low risk zone (27%). Regarding the factor of slope, it can be said that the most landslides have occurred in slopes with 60%. It may because the lack of the soil-formation process prone to slippery movements. In case of the factor of slope direction, the most landslides have occurred in northern domains and in heights with 1600 m high. This results is compatible with the faults and calcareous, marl, and Pyura Chilensis organizations of the area. The results of the present study also show that the entropy model has appropriate performance in identifying risk areas and their zonation. In addition, the results can be used in decision making and management of land use and urban planning.
Sharam Roostaei; Davood Mikhtari; Zahra Hosseini; Mahdi Etmani Hagviran
Volume 2, Issue 4 , January 2017, , Pages 101-123
Abstract
Shahram Roostaei[1]* Davood Mokhtari[2] Zahra Hosseini[3] Mahdi Etmani Hagviran[4] Abstract The management of natural disasters requires locational information in order for prepareness against riske and perils and to decrease them. In this regard it is necessary to eualuate the occurance potential of ...
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Shahram Roostaei[1]* Davood Mokhtari[2] Zahra Hosseini[3] Mahdi Etmani Hagviran[4] Abstract The management of natural disasters requires locational information in order for prepareness against riske and perils and to decrease them. In this regard it is necessary to eualuate the occurance potential of land slides in region which is suseptable for landsliding due to its geographic situation and human construction operations. The case study locates in Dehloran city of Ilam provience in Zarinabad district with 33· 1΄ 30΄ to 33· 19΄ northern latitude. Mimeh river catchment because of having a particular Lithologic ,climate and land use conditions,enjoys young (new) roughness with high altitude variations and sensitive steep slops. On the other hand, human interferences has been increased in this region,therefor,more studies become a necessity. In the study of landslide occurances in the area of Mimeh river catchment,network analysis process (ANP) was applied. In this research some indicators like slop,slop side, lithology, land use, raining,distance form the river, distance form the road and levations were applied in order to determine prone areas. Methods based Analysis of standards in software Super Decision criteria in overlapping layers of information and then integrating the software ARCGIS and, network analysis process(ANP) and the overlap index. The findings showed that ANP has 81/69proportionate with transmittal map of landslides, also coefficients interpretation proved that raining, lithology,and elevation indicators play significant role in landslide. [1]-Professor; Faculty of Geomophology; University of Tabriz (Corresponding author), Email:tabrizu.ac.ir@roostaei. [2]- Associate Prof.; Faculty of Geomorphology; University of Tabriz. [3]- M.A Student; Faculty of Geomorphology; University of Tabriz. [4]- M.A Student; Faculty of Geomorphology; University of Tabriz.
Fariba Esfandiyari Darabadi; Ebrahim Beheshti Javid
Volume 3, Issue 8 , December 2016, , Pages 93-111
Abstract
Received: 2015.12.13 Accepted: 2016.10.29 Fariba Esfandiyari Darabad[1]* Ebrahim Beheshti Javid[2] Abstract ...
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Received: 2015.12.13 Accepted: 2016.10.29 Fariba Esfandiyari Darabad[1]* Ebrahim Beheshti Javid[2] Abstract Landslide is one of the morphodynamic processes including significant hazards in terms of fatalities, financial casualties and the number of happening. In this research, Zoning of potential landslide occurrence is studied in Heyran Defile region. To do this the combination of multi-criteria (Analytical Network Process) and statistically (Bayes' theorem) models and accompanied by 12 natural and human parameters including, Slope, aspect, land use, lithology, precipitation, vegetation density index (NDVI), slope length (LS), topographic wetness index (TWI), stream power index (SPI), distance to road, distance to fault and distance to river were used. The layer of occurred landslides in the study area have been used to the obtaining weight of each landslide susceptibility parameters classes and validation of the final map which seventy percent of the landslide for running the model and another 30 percent is used to the model validation. The result is a map classified in five categories that respectively to be included Zones with very low, Low, Moderate, High and very High potential. According to the result map 26.3 percent of the area case study has been predicted as a region with high and very high potential for the landslide occurrence. These areas primarily to be included marginal areas of the Ardebil- Astara road. Most landslides also occurred in these areas because of the high construction in bordering the road, disrupt the natural slope of the land for the road construction and broaden it. Land use in these areas is mainly sparse forest, rangelands and agriculture which is located on the slopes. Evaluation of zoning map was done using 30 percent of the occurred landslide. According to the results of this evaluation and placement of a considerable percentage of landslides in the high and very high sensitivity classes (77.6 %), it can be concluded that the accuracy of used models in the landslides susceptibility zoning is acceptable. [1]- Associate Professor and Faculty Member of Mohaghegh Ardabili University, (Corresponding Autor), Email:fariba.darabad@gmail.com. [2]- Geomorphology Ph.D. student, mohaghegh Ardabili University (Corresponding Autor).
