avalanche

Avalanche is the fast and downward movement of large masses of snow and avalanches can endanger human lives and cause huge financial losses. Therefore, zoning and evaluating areas prone to avalanches is one of the necessities of environmental planning to prevent crises and The reduction of human and financial losses in different regions. The connection road between Khalkhal and Shahrood sector has attracted special attention due to the development of the communication network in the region and its economic, tourism, and transit importance. This route is located in a mountainous area with special geomorphic and geological conditions, and the occurrence of avalanches in this area has caused many human and financial losses every year. For this reason, the evaluation and zoning of avalanche-prone areas on the Khalkhal Road to the Shahrood section is very important.One of the most basic stages of conducting any research is collecting data and information. In this research, various data and information have been used, including a geological map of Ardabil province with a scale of 1.250000, from which the information about faults was extracted, topographic map of Khalkhal. With a scale of 1/20000, the road map is extracted from this map, the field data of the avalanche points has been collected through the field survey and GPS device, and the important remote sensing data and information include vegetation, land use, elevation map, slope map, slope direction map It was calculated from the images of Sentinel 2 and ALOS-PALSAR satellites. This research is based on field, analytical, and statistical works. Arc GIS, SPSS Modeler, and ENVI software were used to prepare the layers and implement the research model.According to field studies and analysis of satellite images to identify factors affecting avalanches on the road from Khalkhal to Shahrood, 8 layers in order: 1- Height 2- Vegetation 3- Slope direction 4- Distance from the fault 5- Distance from the road 6- Snow area 7- Land use 8- Slope was used with the standard raster format and all the layers were collected together after production and a single raster image was created. After finishing the classification process, modeling was done in SPSS Modeler software with 8 input neurons, 8 intermediate neurons and 1 output, and 70% of the data were allocated for model training and 30% of the data for model testing. The type of algorithm of SVM and MLP model is after error propagation. At the same time, this algorithm is very efficient and makes the model learn as well as possible, and the model process is completed when the minimum amount of error is reached.The results show that in the support vector machine model, the highest weight value for the snow layer is 0.26 and for the slope layer and the distance from the road is 0.18 and 0.15, respectively, which indicates that avalanches and hazards It is more dependent on these variables. Also, in the multi-layer perceptron model, the highest weight value was assigned to the snow area factor with a value of 0.20, followed by the layers of the distance from the road, both values of 0.17 and 0.13.Also the area of risk classes shows that in the support vector machine model, the most class in terms of risk is 36.34 square kilometers and in the multi-layer perceptron model it is 45.83 square kilometers, which shows that the multi-layer perceptron model is better than the volume vector machine model. A large part of the area is classified as high-risk class. Also, in the support vector machine model, the value of 61.57 square kilometers for the high-risk class and 49.32 square kilometers for the multi-layer perceptron model is classified, which shows that there is a big difference between the area values of the models that the support vector machine model had a realistic performance and was able to correctly identify the areas where there was an avalanche process and the risks arising from it, while the multilayer perceptron model did not have a good performance in the high-risk section. In the medium risk section, the results of the gear mark area values are that the support vector machine model with an area of 23.93 and the multilayer perceptron model with a value of 25.83 square kilometers are classified and there is not much difference between the values of the areas, but in the low risk category, the multilayer perceptron model with The area of 15.73 square kilometers is slightly different from the area of the support vector machine model with an area of 14.87 square kilometers.According to the results of two models regarding avalanche risk zoning in Khalkhal axis to Shahroud, also according to the mechanism of avalanche and the risks arising from it, it has been found out by field studies that the morphology of the slopes overlooking the road, the slopes of the central part in the area of Eskistan village due to the angle A slope of 20 to 35% and too close to the sacred road with snow and its accumulation during the winter seasons with the least mobility causes avalanches. The occurrence of avalanches in the region is in the form of slides and masses and does not have a powder state, because the length of the range and also the road factor have a great impact on the occurrence of this avalanche model. The cause of this provocation is known to be the avalanche. The results of the support vector machine model with relatively few deviations from the multi-layer perceptron model have high reliability and have been able to identify dangerous areas well. . Also, the overlap of the identified areas with real points is high in both models, but the results related to the identification of avalanche-prone areas in the support vector machine model have better performance than the multilayer perceptron and can identify the areas realistically and carefully. Therefore, both of these models can be used to identify areas prone to avalanches.

The studied area on the Haraz Road from Poldakhter to Vana is prone to avalanches due to its cold mountain climate. The purpose of this research is to determine the most important factors affecting the occurrence of avalanches and its risk zoning using LNRF and Shannon Entropy models. For this purpose, the criteria of snow cover, elevation, slope, aspect, slope curvature, landuse and distance from the road have been used. The results of determining the most important factors affecting the occurrence of avalanches in the studied area using Shannon's Entropy model showed that the aspect, landuse, distance from the road and snow cover with weights of 0.541, 0.143, 0.129 and 0.083 respectively are more important. Avalanche risk zoning maps show that the highest avalanche risk is due to the location of these areas at an altitude of 2100-2700 meters and a slope of 30-60 degrees with the direction of the northeastern and northern slopes. Evaluation of avalanche risk zoning maps using the empirical probability index (P) indicates the appropriateness of Shannon entropy and LNRF models in the region, but the application of Shannon entropy has led to an increase in map accuracy up to 97%.

Avalanche is one of the dangerous phenomena in snowy areas. Haraz mountain road is one of the most dense communication axes in the north of the country, and due to special geomorphological conditions, parts of its route are at risk of avalanches. So that since the beginning of the construction of this road, it has led to many financial and human losses. Therefore, it is known as the most news-making road in Iran. The purpose of this thesis is to identify the factors influencing the formation of avalanches and to identify the places where they occur, as well as to prepare an avalanche risk zoning map in the region with the help of geographic information system (GIS) and remote sensing (RS). In order to achieve the goal of the research, GIS software was used to draw maps of elevation classes (hypsometry), the amount and direction of the slope of the domain, geomorphology and other related maps. Then, by examining the relevant information sources, scoring tables of the effective factors of avalanches were formed. These tables include 5 main criteria (amount of slope, direction of slope, height, temperature and precipitation). Each of them is divided into indicators and the corresponding points are listed according to the type of factor and the degree of influence in the occurrence of avalanches. By combining the said information in the form of Bolean model, weighted according to the degree of their influence, and combining these layers together, the avalanche risk zoning map of the studied area was prepared, and finally, the results obtained from the maps were compared with the control results. The field was compared.

One of the concerns of people in the mountainous areas is snow avalanche. In this article avalanche zoning as a hazard using artificial neural networks and hierarchical analysis has been acting. AHP to improve the training sample is conducted in GIS. This method applied at basin sirvan in the South West of kurdistan province that have high potential for avalanche risk,. For this purpose, First it was necessary avalanche pathways that in them avalanche was happened, Field visits were conducted and their coordinates were taken. A literature review was conducted to identify factors affecting this process. Based on studies slope, aspect, elevation, convexity and concavity, distance from roads and land use were selected. Map of hierarchical classification analysis of each class of 20 samples were used to train the neural network. Perceptron neural network to assess these variables with the six input layer, a hidden layer, six nodes per layer with learning rate 0.01 with two linear sigmoid function as the optimal structure by trial and error be accepted. Evaluation of these variables using neural networks shows that more than 86 percent of the study area is among the areas with high potential risk of avalanche. In order to validate these models from observational data available that demonstrates the success and effectiveness of both function but with low priority for linear function.

Risk is an inevitable part of life, every day people are somehow at risk. Different risks in various forms and perspectives have different functions. Kurdistan province, with various heights and relatively good rainfall, It results the country's cold spots. Since most of seasonal rainfall occurs in winter, Snow cover is often the domain and passes it hillsides. One of the concerns of people in the mountainous area is a snow avalanche phenomenon. Sudden loss of massive snow is avalanche snow that may include rocks, soil, plants or ice. It seems that the name of the snow avalanche adopted from the eleventh month of the solar year. The possibility of snow in mountainous areas during this month of year is more than other months. Snow avalanches every year around the world, especially in alpine impose huge human and financial losses. Statistics and local evidence also show that the province of Kurdistan expect or accept to soil erosion and destruction of infrastructure and natural resources had a casualty. Actually, this is the most vital reason why zoning area danger avalanche was conducted in this study.
First, avalanche pathways was recognised and selected as a field visit by department of urban development The purpose of the visit was to extract the geography’s coordinates of the avalanche. The Background of the study shows some of the land criteria are more important than others. For this purpose we performed a literature survey to explore indicators that had a significant impact on avalanche snow like such as; slope, aspect, elevation, convexity and concavity, distance to roads and land. To facilitate greater accuracy, all criteria were used in geographic information system (GIS) for mapping. Thereafter, produced map can be categorised into four classes of low, moderate, high and very high. In the next step. Analytic hierarchy process (AHP) and Analytic Network Process (ANP) model were used for weighting and ranking all criteria (slope, aspect, elevation, convexity and concavity, distance to roads and land use) by using pairwise comparisons with judgments that represent the dominance of one element over another with respect to a property that they share. The Analytic Hierarchy Process (AHP) is a method for decision making which includes qualitative factors. In this method, ratio scales are obtained from ordinal scales which are derived from individual judgments for qualitative factors using the pairwise comparison matrix. The Analytic Network Process (ANP) is a more general form and extension of Analytical Hierarchy Process also uses a pairwise comparison matrix to obtain ratio scales. The difference between these two methods appears in modelling the problem and computing the final priorities for the criteria from ratio scales previously obtained. The ANP feedback approach replaces hierarchies with networks, and emphasizes interdependent relationships among all decision criteria were used in this study).
Based on the resultant Maps, AHP and ANP had a good overlap with visited points and with high accuracy lay in areas of high risk and very high risk. According to the map provided by Analytic Hierarchy Process from the total number of 30 hillsides, thirteen of them lay in very high risk and seventeen of them in the area of high risk. Thereafter, resultant maps of Analytic network Process shows from the total number of 30 hillsides twelve of them lay in very high risk area and eighteen of them in the high risk area.
The results of (AHP) indicates that from the total area of Kurdistan province, about 1049.7 square kilometres is classified in the low risk area, 11.392 square kilometres in moderate, 14.341 in the high risk area and 2009.1 square kilometres in very high risk area, respectively . In view of the process of the network as map about 978 square kilometres is in low risk area, 10245 square kilometres in moderate risk area, 15410 square kilometres in the high danger area and 2158 square kilometres is located in very high danger area. Therefore, we can use ground data for snow avalanche zoning areas along with Analytic Hierarchy Process and Analytic Network in zoning areas avalanche risk which is applicable. Weather parameters like snow, wind and temperature have an important role in terms of snow avalanche. Decreasing rainfall from west to east of study area. The number of freezing and snowing days indicates the critical situation for snow avalanche in the highlands and the pathways. More prevailing wind direction in the cities are in the Southern west, Southern and in area with high elevation blowing from western direction. Looking at the range of high and very high can be seen, mostly in the North and South and North East which show the impact of prevailing wind upon snow and putting snow in hillsides that can produce snow avalanches
The hillsides show most of avalanche dangers are at west, northwest and south of Kurdistan thus they are compatible with rainy areas. To build any recreation centred including, winter sports, road construction and expansion, snow avalanche risk areas should be considered. Now pathways don’t have any risk signs warning about avalanches. The warning signs of avalanche at the pathways are essential.In the hierarchical model 198 villages lay at low-risk areas and 20 villages in the area were extremely dangerous. Also in the network model 184 villages in low-risk areas and 23 villages in the area were very dangerous.

One of the natural hazards in mountainous areas, which always cause great losses of life and financial damages, is the avalanche fall. Since, survey the avalanche-prone areas for prevention the probable damages is considerably important, especially when the avalanche paths affect the residential areas or roads. In this research, based on local information, one of the avalanche paths in the Chaharmahal and Bakhtiari province is identified. Then in the field works, all parts of it visited and the geomorphology and land use characteristics investigated. After that, using geographical information system, hypsometry, slope and aspect maps produced. Using these maps and the information obtained from the field works, the avalanche accumulation zone, the avalanche tracks, run-out zone of the avalanche, starting zone of the avalanche and profile of the main track are extracted.

Iran due to high climatic variability, was always exposed to various natural hazards.
One of the disaster, avalanche areas is Brfkhyz in place, considerable damage has been inflicted on the body of the Economic and Social.
Therefore, the preparation of maps for different parts of the area on February evaluate risks is very important. In this paper, by using maps of elevation, slope, aspect, land use and geomorphology and climatic factors, and considering the avalanche field visit any part of the basin was Which shows the high capabilities of geographic information systems in the avalanche is to identify pathways. The results of this study showed that seventeen crossing the Persian month Bahman identified six pathways regulating basin, Roads and residential areas that affect administrators should make necessary arrangements for controlling the crossings.