davood mokhtari

Azarshahrchai basin, located on the western slope of Sahand Mountain, is one of the flood-prone basins that every year, with the onset of spring rains, water flows in the valleys and floods occur in this basin. Thus, investigating and identifying flood-prone areas is a fundamental step to managing and reducing flood damage in this basin. The main goal of this research is to determine the effectiveness of the two-variable statistical method EBF (witness-belief function) by using the effective variables in flood occurrence and geographic information systems (GIS). In order to achieve this goal, 82 floodgates were first prepared, of which 57 points were randomly used for model training and 25 points for validation. In the next step, 14 parameters effective in the occurrence of floods, including elevation, slope, aspect, slope curvature, distance to river, distance to road, river density, TWI (Topographic Wetness Index), lithology, soil type, Stream Power Index (SPI), rainfall, Land-use, and NDVI were selected to prepare flood risk map. The results of the analysis of the parameters showed that the height classes of 1289-1500 meters, areas with a slope of 0-15 degrees, flat slope direction, areas with slopes with concave curvature, and areas near waterways and roads have a high potential for flooding. The evaluation of the accuracy of the research model using the ROC curve and the area under the curve (AUC) showed that the EBF model, with a value of 0.973, had an excellent performance in preparing the flood risk potential map in the study area. Therefore, the prepared map can be a reference framework for planners to improve and reduce flood risks along with flood risk management activities in this basin

Rivers are environmental forms that react strongly to changes in their bed, tectonic is the most important factor affecting morphology of the river, causing significant changes in river systems. In this study, using the digital elevation model (DEM), Geographic Information System (GIS) and Global mapper 13, we investigated the effect of tectonic activity on river systems in the eastern slopes of Mullah Daghi, southeast of Zanjan province, this The area is drained by Abhar river. Using the Digital Elevation Model (DEM) in the Arc Gis 10.2 software environment, required maps including geological maps, topography and…, Geological map of 1: 250,000 leaves of Zanjan was used to prepare the fault map. In order to achieve the research objectives, tectonic activity indicators including: are Mountain front sinuosity, basin shape, drainage density, longitudinal gradient of the river, River maze, basin asymmetry, hypersometric integral, the topographic symmetry of the basin and the width of the valley floor to the height. The combination of these indicators is achieved by the tectonic activity index (IAT). The results obtained through the Iat index indicate the activation of tectonic and neotectonic in the watershed of Ardejin and Abhar and the moderate activities in the basin of the zareh bash basin. The impacts of these activities on river systems that are different from the tectonic indexes in the studied basins, such as river meanders(main stream), coniferous formation (Ardejin watershed basin),  tilt watersheds  abhar and Ardejin and  the shape of the basins (Basin elongation zareh bash)

Road transport network is facing a wide range of natural and human disasters, because of geographical extent and functional diversity. In addition to direct damage to road transport networks, accidents can cause indirect damage to road network users and even entire community. Present research is an attempt for assessing potential areas of road accidents in highways of East Azerbaijan province. In this regard, four main criteria (climate, environmental, topographic and road factors) and fourteen sub-criteria were used. The weights of each criterion and their sub-criteria were computed using ANP model. In doing so, the final map of proposed sites for road accidents was prepared by integrating them with standard layers. The results of this study revealed that road safety criterion has the most importance in road accidents and the sub-criterion of the crash is also of paramount importance. Furthermore, the segment of Koshksaray-Marand was the most dangerous area and segment of Jolfa-Norduz was the least risky area in terms of the probability of occurrence of road accidents in highways of East Azerbaijan province.

Urmia Lake is one of the largest saltwater lakes in the world, which unfortunately is drying up and has caused many dangers and concerns, especially in relation to salt dust in its dried areas. Therefore, in this research, we tried to investigate the relationship between vegetation and dust in the cities around Lake Urmia. Salinity in plants causes physiological disorders, salt stress causes growth, photosynthesis, protein, respiration, energy production, premature senescence, water reduction in plants. Considering these effects, it was tried to evaluate the overall health of plants by using related indicators including NDVI, CIre, GCI, CRI2, NDWI, NDII, MSI, PSRI. These indicators evaluate the amount of plant water, plant water stress, photosynthesis capacity, plant growth and water deficit, the amount of chlorophyll, nitrogen and pigments, which are related to plant energy and health. According to these indicators, the health of plants is generally in a favorable condition, and mostly the highest numerical values of the indicators were assigned to gardens. Using Landsat and Sentinel 2 images and the NDVI index, the vegetation changes of the region were determined in the period from 2010 to 2020, and then using the MERRA-2 database, the amount of dust concentration was also extracted for the mentioned years. The results showed that the average NDVI in the studied area follows a constant trend with an overall average of 0.2957 and sometimes it increases or decreases due to the influence of external factors such as dust. Based on this, the highest (0.3495) average NDVI is related to 2018 and the lowest (0.2579) is related to 2013. Also, two methods of linear and logarithmic regression were used to investigate the relationship between vegetation cover and dust, and the results showed that based on the linear (0.7703) and logarithmic (0.7915) regression, the highest coefficient of explanation between the two mentioned indicators was in May. have been.

In addition to their importance and role in providing water resources, karstic water resources also have a high potential for vulnerability, which is why these resources are always exposed to pollution. Given the importance of the issue, this study identifies vulnerable areas in Ravansar basin. The research data includes 1:50,000 topographic maps, 1:100,000 geological maps, a 10-meter-high digital model, and digital layers from various organizations like soil layer. After collecting the required data, using COP and EPIK methods, the areas vulnerable to contamination were identified and then the results were compared and evaluated. The results estimated by COP and EPIK methods showed that Ravansar basin has a high potential for vulnerability, so that based on the results of both methods, many parts of the region are vulnerable. Based on COP method, 27.8% of the area has a very high vulnerability potential, and based on EPIK method, 29.5% of the region has a high vulnerability potential. Moreover, in terms of spatial distribution of vulnerabilities, based on the results obtained from both methods, the northern regions have the highest vulnerability potential and the southern regions have the lowest vulnerability potential.

In recent years, tourism has emerged as a smoke-free industry and has become a substantial source of income for many countries in world trade. It is also an important element in improving and regulating the trade balance and balance of payments. Therefore, strategic planning for the development of this industry has become crucial in most countries. The purpose of this study is to identify effective drivers in the strategic planning of tourism development in Tabriz. The research method used in this study is both applied and descriptive-analytical. The statistical population of the study includes approximately 2000 people, which comprises managers, officials, urban experts, and academic elites of Tabriz. The sample size was estimated at 340 based on the modified Cochran model. The research data was analyzed using the partial least squares model in Warp-PLS software. The findings indicate that the most important drivers of tourism development with a focus on historical-cultural tourism are related to legal-political, economic-marketing, and managerial drives, respectively. The coefficients extracted based on the structural model of the research for each driver are 0.71, 0.65, and 0.53. Among the sub-variables, the most influential ones are related to measures such as correcting negative perceptions and eliminating Iranophobia to increase motivation for traveling to Iran, enhancing international tourism cooperation, removing barriers such as bureaucratic regulations and accommodation issues, providing proper information and advertising in target markets, building institutional interaction and trust between public and private bodies, using participation, establishing accommodation facilities that comply with international standards, and providing facilities based on the nationality and culture of tourists through an appropriate needs assessment of their preferences.

One of the new approaches in the direction of urban sustainability is the concept of livability, which emphasizes on improving the quality of various economic, social, environmental and physical indicators in the city. In this study, which was conducted with the aim of assessing the livability situation in 10 areas of Tabriz, the descriptive-analytical method and questionnaire tools (at both levels of citizens and experts) were used. In this regard, one-sample t-test in SPSS software environment, Vicker multi-attribute decision model and interaction / structural analysis method using Mick Mac software for data analysis have been used. The statistical population of this study was the residents of 10 districts of Tabriz, and the statistical sample was selected based on stratified sampling method and the proportion of population share of the regions using simple random sampling method. The results show that according to both experts (3.04) and citizens (3.20), the average of the four dimensions of livability of Tabriz metropolis is higher than the average (theoretical average of 3). According to the opinions of the citizens of District 9 and according to the opinions of experts, District 1 is in the first place. The results of Vickor analysis also show the first rank of Region 2 in terms of viability. Regarding the influential factors resulting from Mick Mac software, "creating employment and sustainable income" is the most important known factor. The results show that the factors of job creation and sustainable income, renovation of worn-out texture, improvement of suburban texture, provision of suitable housing, development of green and open spaces and provision of infrastructure services are key factors, respectively. Considering this, it can be said that among the 10 areas of Tabriz metropolis, we are witnessing a spatial imbalance in terms of livability, and the optimal management of the mentioned cases plays an important role in eliminating this spatial imbalance.

The results of studies conducted in this region show that the climate of the region is semi-arid and cold, and its rainfall regime is in the Mediterranean. Its geomorphology is young and its topography is directly related to geological structures, i.e., most folds and fractures make up the heights. The lithology of the formation, along with the action of tectonic processes that have led to the dissolution and creation of joints and cracks in the rocks, has provided the necessary conditions for the formation of less developed karst forms. The region's most significant karst forms are Karen, pinnacles, channels, dissolution doline and dissolution cavities, karst springs, and caves that have spread along joints, cracks, and faults and indicate the connection between these landforms and the region's tectonic structures. In this study, to find out the relationship between tectonics and karst formation, the dip and strikes of fractures (joints and faults) were measured in 7 areas. The results obtained from field studies and their comparison with the information contained in remote sensing documents show that the direction of most joints in the region is consistent with the direction of faults. It has also been found that more Karst landforms have formed along these joints. On the other hand, most of the valleys are consistent with the geological structures of the region, i.e., faults and folds. Therefore, tectonics has played an effective role in creating Karst landforms and their hazards in the region. According to the rockfall risk zoning map, 3.77% of the total area is in the high-risk zone.

The term geosite is a new concept in tourism land and is very important in understanding the geological history and historical geological evolution of a region. Geosites are landforms that have gained special value over time due to human awareness, thus creating the necessary context for the development of tourism activities and special infrastructure in an area. Geosites may exist individually or in broader perspectives. They may be altered, damaged, or even destroyed by the effects of human activities. Different regions have different potentials in terms of geosite diversity and consequently the development of geotourism depends on geological, geomorphological, and hydro-climatic factors. One of the areas that has high potential in the development of the geotourism and tourism industry is the karst areas. Kamyaran city in Kurdistan province is one of the areas located in karst formations. Kamyaran city, despite having developed karst areas, types of landscapes, rivers, and springs, has a high potential for the development of the geotourism industry and geostourism. Despite the natural conditions in the region, it seems that more attention has been paid mainly to cultural issues. Due to the importance of the issue, in this study, the geotourism situation of Kamyaran city is studied and optimal geotourism models in this city have been presented.

In this research, in order to achieve the desired goals, library information, interviews, field visits, the digital model height of 30 meters, geological maps 1: 100000 and topographic maps 1: 50000 have been used. ArcGIS and SPSS software are the research tools. Also in this research, the Kubalikova model has been used to evaluate geosites and fuzzy logic and ANP models have been used to identify areas prone to geotourism development. This research has been done in three stages. In the first stage, using field visits, interviews, and library studies, the geosites of the region were identified and evaluated using the Kubalikova method. In the second stage, 9 parameters (the distance from the river, landscape, urban areas, communication lines, cultural sites, distance geosites, altitude, slope as well as vulnerability potential) and fusion logic integrated model and AHP were used to identify areas prone to geotourism development in Kamyaran city. In the third stage, based on the results obtained from the previous stages and the location of geosites, appropriate models for visiting geosites were presented.

The results of the evaluation of geosites based on the Kubalikova model indicate that among the geosites of the region, Palangan valley has the highest score with a total of 10.25 points, followed by Gavoshan dam, and Tangivar River with 10 and 75 points, respectively. The results also indicate that the geosites of the western regions of Kamyaran city had the highest score in terms of the Kubalikova method. In this study, after evaluating geosites, areas prone to geotourism development have been identified. Based on the results, the southern and western parts of Kamyaran city due to the distribution of potential geosites, the presence of permanent rivers, proximity to cultural sites, and proximity to communication lines had a great potential for geotourism development goals. According to the results, Palangan and Tangivar River geosites have the highest potential for geotourism development goals because they have a high score in terms of evaluation methods and are also in classes prone to geotourism development. Also, in this study, based on the location of geosites in the study area, 6 patterns were presented for visiting and planning for geotourism development goals. The results of evaluating the scores of geosites obtained in different models indicate that the total averages percentage of scores of the visited geosites were 26.25, 33.75, 30.75, 23.25, 13, and 71.75 in the second, third, fourth, fifth, and sixth patterns, respectively.

In this study, the effect of protuberance on the thrust vector of a supersonic jet was investigated as a new method in thrust vector control. For this purpose, a convergent-divergent nozzle was designed and fabricated. This nozzle is such that the nominal Mach number in the nozzle exit in full expansion condition is 2. The wall of the nozzle is equipped with pressure holes to measure pressure variations. Also, there is a hole on the nozzle wall to apply a protuberance inside the nozzle. Pressure sensors for pressure measurement and also the Schlieren system are used to check the outlet flow field. The total pressure in all experiments is constant and equal to NPR=6.6. Three-dimensional and multi-block numerical code is used for flow modeling. Also, the turbulence model k-ε, RNG is used to model the nozzle flow. An unstructured mesh has been used for modeling the flow field within the nozzle and the outside domain. The results of this study show that the depth of penetration of the protuberance in the flow field has a significant effect on the amount of deviation and even the direction of the jet stream exited from the convergent-divergent nozzle. The maximum deviation of the jet outlet from the nozzle is 9.8 degrees, which is equal to a penetration ratio of 0.4. In addition, these results indicate that with the increase in protuberance penetration within the nozzle, the nozzle axial thrust has slightly decreased.

Human’s activities on the Earthchr('39')s atmosphere have changed significantly during the past century. Increasing the concentration of greenhouse gases leads to global warming and climate extremes which accordingly resulted the changes of the profiles. Therefore, studying the limit values in planning and policies in the agricultural sector and managing the water resources is very considered to be very critical.  Within this research, daily observations of precipitation, maximum and minimum temperature of 4 synoptic stations (located in West of Iran) were analyzed statistically during 2016-1960. For this goal,, modeling the distribution of temperature and precipitation in the region extreme was carried by extreme Generalized Extreme Value Distribution (GEV) in the base period  offrom1990 to1961. In the next step, frequency changes and extreme amounts from each station were compared in the recent observation period 2016-1991. Finally, the values of variables for different return periods were estimated. The results indicated that in the base period, the rainfall season series distribution, the hot and cold furnaces (except the Hamadan Station) are of the Gombel Type.  According to results, in the recent period, the distribution of cold temperatures except Kermanshah Station seems the base period as Gombel Type. however, the distribution of extreme temperatures in the recent period has changed from Gombel toWeibull type.. In relation to the extreme precipitation in the period of 2016-1991, the shape parameter has tended to be positive in all stations. While, its 95% confidence intervals include zero like the base period. Thus, its distribution follows the Gumbel Type like the base course. In the recent period, except Khorramabad Station, Ferrin precipitation amounts increased in the period of 5 and 10 years returns at the rest of the stations compared to the base period

Urmia Lake is one of the largest saline lakes in the world, which has greatly decreased in recent years. It has created many dangers and concerns especially concerning salt dust in its arid areas. Therefore, this research aimed to investigate the relationship between vegetation and dust in the cities around Lake Urmia. For this purpose, first, using MODIS images and NDVI index, changes in the vegetation of the region in 2010 to 2020 were determined, and then, using the MERRA-2 database, the dust concentration was extracted for the mentioned years. The results showed that the mean NDVI in the study area follows a steady trend with a total mean of 0.2957 and sometimes increases or decreases due to the influence of external factors such as dust. Accordingly, the highest rate (0.3495) of the average NDVI is related to 2018 and the lowest rate (0.2579) is related to 2013. Furthermore, to investigate the relationship between vegetation and dust, two methods of linear and logarithmic regression were used. Based on linear regression (0.7703) and logarithmic (0.7153), the findings showed that the highest determination coefficient between the two indicators was in May.

A tourist destination for achieve a high competitive advantage, must be ensure that all the tourist attractions and experiences it has offered so far are different from other destinations that a tourist intends to experience. Therefore, the quality of a tourist destination is one of the most basic competitive advantages for attracting tourists and sustainable tourism development. The purpose of this study, is to evaluate and conceptualize the quality of selected geomorphosites by the citizens of Tabriz metropolis in East Azerbaijan province. This research is applied in terms of purpose and in terms of collecting information descriptive and survey. The statistical population of the study was 384 citizens living in the metropolis of Tabriz and the Cochran pattern was used to determine the sample size. To collect data to select prominent geomorphoses, the interview method was used and a survey questionnaire was used to measure the closed-ended questionnaire for 28 tourism-oriented brands. Based on, 12 geotouristic destinations were selected for review and final evaluation of its quality based on reference questionnaires. For reliability of the questionnaire from Cronbach's alpha coefficient and For the narration, the views of prominent experts and professors in this field have been used. The results of this study showed From 12 selected geomorphosites, Asyab kharabe (Jolfa region) Geomorphosite with a weight of 0.854, Aoun Ibn Ali mountain of Tabriz  (Ainali) with a weight of 0.823 and Payam pass  (Marand region) with a weight of 0.806, The first to third ranks in terms of desirability in the quality of geomorphosites.

Slope instabilities are one of the major natural hazards in mountainous areas that cause significant damage to human activities each year. The purpose of this study was to compare the artificial neural network model with the logistic regression model to evaluate the risk of mass movements and amplitude instability and to identify the effective factors in this phenomenon in Ojan Chay basin. The purpose of the results of the statistical models is to determine the regions with potential of occurrence of instability and finally to prepare a hazard zoning map for the study area. And then the layers are prepared. Distribution map of slope instabilities that occurred in the basin was prepared and integrated with the map of factors affecting the movements and slope distribution map of the slope. Distance from fault, land use, distance from village and road, distance from drainage network were calculated in ArcGIS software environment. ROC, Pseudo R square and Chi Square coefficients were used to evaluate the outputs of the models used. The results showed that the percentages of high risk zones in neural network model and logistic regression were 10.32% and 5.06%, respectively, which mainly include the lithologically restricted zones of these areas. . Also the neural network model with ROC value is 0.89 more efficient than logistic regression for zoning the occurrence of domain instabilities; based on zoning using neural network model, respectively, 40.32, 22.15, 18.32, 8.89,10.32 of the area is classified as very low, low, medium, high and very high risk classes

The 2012 Ahar-Varzegan earthquake and its aftershocks have not only caused huge damage with a severe loss of life and property but also induced many geo-hazards with the major type of collapse, creep, slip, debris flow, and fallings that are generally considered as landslide in this study which can cause continuous threats to the affected region. in this study, a semi-automated geo-hazard detection method has been presented to determine the Landslides due to 2012 Ahar-Varzaghan earthquake in area from Ahar to Varzaghan by the use of bi- temporal Landsat images from before and after the earthquake. The accuracy of the results was checked out using field observations, Google Earth images and the error matrix. The results of the visual validation with the Google Earth images showed that the used method can detect landslids with relatively high accuracy.The images of landsat5 and 8 Because of their multispectral advantages can be used as a suitable data source for research on Instabilities. Finally, the validating results obtained by using the error matrix showed the total accuracy of 92.1% and kappa coefficient was 0.99. So based on the results obtained from the above method, the landslides were distributed mainly in slopes between 15 and 40 degrees and the height distribution of instabilities of 1420 to 2000 meters. Also based on vegetation indices, density of landslides have been increased after the earthquake. Generally unstabel slopes are located along river valleys and roads in mountain regions with deep valleys and steep slopes. According to the nature of present study, the obtained result can be useful for environmental planners and project developers.

Mass movements of the earth's surficial materials downward the slopes is called slope instability, which is affected by the earth gravity, while the rate of material mobility increases by the presence of water in the sediments. Each year, slope instabilities cause enormous economic damages to roads, railways, power transmission and communication lines, irrigation and watering canals, ore extraction, as well as oil and gas refining installations, infrastructures in cities, factories and industrial centers, dams, artificial and natural lakes, forests, pastures and natural resources, farms, residential areas and villages or threaten them. Nowadays, many instabilities are resulted by human intervention and manipulations. One of the effective human factors in instability occurrence is the construction of roads. Road construction, especially in mountainous areas, increases the probability of occurrence of various types of instabilities, as it changes the natural balance of the slopes and causes deformations in the land. Each year, lots of casualties and financial losses are imposed by the occurrence of various types of instabilities in the slopes overlooking the roads, which also cause the destruction of many natural resources in the country. However, the construction of roads, highways and freeways is necessary and unavoidable in today’s life. The Karaj-Chaloos road and the Tehran-North highway are two routes that connect the Iran’s capital Tehran with the southern shores of the Caspian Sea, but suffer frequent slope instabilities.

In tourism industry, attitude is considered as the main concept in selecting destination. Motivation specifies the reason of the tourists for travel or doing a specific activity during trip. Evaluation of the tourists’ motivations allows us to know their needs and preferences. This research aimed at investigating the relationship between tourism motivations of the Tabriz metropolitans’citizens and their tourism destinations in East Azerbaijan by geo tourism approach. For doing so, 28 important tourism destinations in East Azerbaijan province were selected and their relationship with touristic motivations was analyzed. The research method was descriptive analytical and correlative. The statistical population consisted of approximately 1800000 citizens of Tabriz metropolitan. The research sample was determined 384 individuals via Cochran formula. Accordingly, 400 questionnaires were distributed and 384 acceptable questionnaires were returned. For analysis of the demographic characteristics descriptive statistics and in the inferential statistics, Pearson Correlation Test and multivariate regression were used. The results showed that there is a positive and significant relationship between the geo-touristic destinations and the citizens’ touristic motivation. Among the tourists’ motivation, circulation in the nature has the most powerful dimension relative to other motivations in the geo touristic destinations.

The enemy's first goal is to attack and invade a country in its military centers and military installations Passive defense is a set of plans, designs and actions that reduce vulnerability to enemy threats. Therefore, an approach to organizing military centers in a country leads to the establishment of these places in such a way as to provide maximum security and defense capabilities to the country. Locating is an activity in which specific capabilities and abilities of the region are appropriate for the existence of adequate land and its relationship with other urban and rural applications to select the appropriate location for the desired purpose. The purpose of the present research is to find suitable and optimal locations for military garrison locations in East Azarbaijan Province with a climatic approach. To do this, the GIS and the network analysis process were used and nine points were proposed for the military garrison to be located.

One of the most influential factors in the occurence of a flood in the spillway basins is proposed to be the unsuitable or exorbitanceuse use of lands. One of the flood management solutions is to optimize the land use allocation by considering multiple objectives and parameters. In this regard, GIS capabilities could be applied as one of the novel scientific and technical methods along with taking the advantage of Artifcial intelligence capabilities, such as multi-objective genetic algorithm. This research aimed to model the land use allocation in GIS platform using NSGA-II algorithm to monitor flood crisis.

In the designed model, using the interruptive method, land’s ecological capability was extracted and then using NSGA-II algorithm capabilities, optimal applications were obtained for various parts of the area in order to decrease the flood height as well as to increase the economic profit with the least difficult change of utilities. In the designed model, the curve number parameter (CN) was usedto investigate the role of land use on the flood.

The results of the designed model are represented in several optimal patterns that have the same applicable value. Based on the present conditions of the studied region and the expert’s opinion, the optimal model could be executed. To evaluate the capability of the designed model, the Taleghan basin was selected which is located in Alborz Province; CN range of the study area was 83 in the searching space, while in designed output models, the lowest amount of CN, with 11% decrease compared to the current situation, was about 74.5%. Also, the economic profit growth was 52.19% in this land synthetic pattern.

The results and achievements of this study include proposing a land use optimization model based on a multi-objective genetic algorithm for flood reduction, integrated river basin management, as well as programming in an expansive form to use in future studies.

Extended Abstract: In general, satellite data classification with digital interpretation method is separation of similar spectral sets and classification of images into groups or classes placed in each class, spectrum or a value (not being separable statistically). In other words, when a classification is carried out on data sets or images, in fact spectral classification is conducted and in the new image, every class or category is indicator of a specific phenomenon with a unit spectral value. The base for data classification is comparison of spectral value of picture pixels with the samples introduced by its interpreter or with initial classes and   categories, constituted automatically in the time of digital interpretation. Hence, the pixels, values of which are not statistically significant, are placed in the same spectral group or class. So, preparation of land use maps by digital classification of remote data sensing depends on the methods used in classification, land coverage condition and environmental condition of the area. The aim of the present research study is to compare pixel-based classification algorithm (maximum likelihood) with object-based method (support vector machine) to prepare land use maps with the aid of SPOT5 satellite HDR image sensor and Landsat 8 satellite OLI image sensor in Ahar Chai basin from Ahar area to Varzegan. Methods and materials: In this research study a SPOT5 satellite HDR image sensor dated back to August 23, 2006 with four spectral bands and separation power of 10 m with path and passage 138-272, 138-273, 139-272 and 139-273 and Landsat 8 satellite OLI image sensor dated back to 2017/07/21 with route and passage 168-33, isolation power of 30m, increased to 15m through combination with band 8 were used to collected the necessary data. Topography map at scale 1/50000 and geological maps of 1/100000, land control data harvested by GPS, Garmin model and ArcGIS 10.4.1 and ENVI 5.3 software were used in this study. Information extraction from remote sensing data especially land cover can be obtained by digital classification. In practical some people are more comfortable using visual interpretation to retrieve land cover information. However, it is highly influenced by subjectivity and knowledge of interpreter, also takes time in the process. Digital classification can be done in several ways, depend on the defined mapping approach and assumptions on data distribution. The study compared several classifiers method for some data type at the same location. Maximum likelihood Classifiers (MLC) which use pixel-based and object-based classification using advanced supervised machine-learning algorithms such as Support Vector Machine (SVM).Therefore, the aim of the present research is to compare maximum likelihood in pixel-based processing and support vector machine algorithm in object-based processing in order to evaluate their performance in classification of LANDSAT 8 and SPOT 5   satellite images.  The necessary pre-processing including geometrical corrections and atmosphere corrections were conducted on the image. Discussion and Findings of the study indicated that both support vector machine algorithm in object-based classification and maximum likelihood in pixel-based classification enjoy higher and appropriate accuracy in classification and exploration of land use maps for Ahar-Varzegan area. However, considering the results obtained from the two algorithms used in this research, it can be concluded that   support vector machine algorithm in object-based classification of satellite images provide the conditions for higher accuracy compared to maximum likelihood in pixel-based method. One of the main reasons of achieving higher accuracy in support vector machine algorithm classification is that in this algorithm, in addition to spectral data the data related to contexture, shape, position and content are also used in classification process, hence classification accuracy is increased significantly. After doing classification procedure using both algorithms of pixel and object-based method we proceeded on evaluation of the results reliability in them The results showed that, Findings obtained from both classification algorithms indicated higher accuracy of object-based classification with total accuracy of 94.99 % and Kappa coefficient for exploration of land use of Ahar-Varzegan area, this is while pixel-based classification with total accuracy of 89.39% and Kappa coefficient of 0.89% indicated acceptable level of classification. So that Feizizadeh et.al (2009) in exploration of East Azerbaijan land use with the aid of the two pixel-based and object-based algorithms concluded that object-based classification with total accuracy of 95.10 % has higher efficiency in exploration of the province land use compared to pixel-based classification with total accuracy of 88.37%.

At present, the question of identification, control, and prevention of human, economic, and social losses resulting from natural events such as earth tremors, floods, and earthquakes have attracted special interest in scientific-research communities and in responsible authorities of most countries around the world. In recent decades, considering the upward trend in losses and damages caused by natural events (especially landslides), prediction of damages and losses and introduction of solutions and methods for controlling and avoiding them have been addressed in earnest. This research evaluated the region around the Benaravan fault using logistic regression (logit regression or logit model) to determine regions that face slope instability hazard. Field surveys were made, previous research was reviewed, and the prevailing conditions in the region was studied first and, using the Idrisi software, it was found that the nine factors of altitude class, slope, dip direction, lithology, distance from the fault, distance from the waterway, distance from the road, land use, and vegetation influenced occurrence of slope instability. After performing slope instability hazard zonation, percentages of slope instability in each class were calculated. Results indicated that areas with high hazard zonation in the study region constituted the smallest part of it. In this research, which used logistic regression, the elevation factor with the highest coefficient was the best variable for predicting the occurrence probability of slope instability in the region. The highest incidence of slope instability occurred at high altitudes with slopes of 23-32 degrees because of gravity force.

The purpose of this study was to extract and explore land use changes from satellite images with object-oriented and knowledge-based models, as well as predict these changes using the Markov chain model by the 2030 in the Zailbirchai basin. Considering that the separation of some LULC from each other, such as irrigated wheat, Rain-fed Agriculture, Irrigated agriculture, and orchard in images with a spatial resolution, such as Landsat images and known pixel-based methods, is rigorous. Therefore, in the present study, a method based on the knowledge based was used for the extraction of the LULC with the OLI image of 2015 and its validation was done with kappa coefficient (0.86). Then the result of method was used in the TM image of 1987 (kappa coefficient equal to 0.83). Finally, after the analysis of the changes occurred, temporal changes was predicted for 2030. The classification of images shows the growth of residential, orchard and irrigated agriculture land uses, respectively, 15, 42 and 50 km2 over the course of 28 years. This growth reflects the high consumption of water in the region. Cross Tab, on the other hand, shows the conversion of low-consumption applications such as irrigated wheat to arable crops. Also, in the next 15 years, based on pattern of 28-year-old using Markov chain analysis model, this growth will be up to 8, 27 and 8 km2, respectively.

Saymarreh landslide is one of the known largest landslides in the world that is located in the southwest of Iran. The purpose of this study was to compare the characteristics and geomorphological influences of this landslide with the largest landslides of the world. Saymarreh landslide is one of those large landslides that have undergone significant geomorphological, historical, and cultural changes during the Holocene era. The evolutionary trend of this landslide is highly complicated; in fact, it is one of the most important characteristics of large landslides. This landslide formed several dam lakes, and their formation were frequently repeated. However, it is not clear that whether the formation and evolution of the lakes were due to the river erosion sequences or the repetition of Saymarreh landslide. A large number of researchers believe that Saymarreh landslide is the largest landslide in the world, but some researchers do not believe so and introduce other landslides as the largest ones. Thus, by performing detailed investigations into the region, the geomorphic features of this landslide and its evolution was probed. To achieve this goal, ETM2002 satellite images, IRS of PAN and LISS III satellite images of 2004 and 2006, topographic maps, geological maps of SRTM DEM, and ArcGIS software were employed. The research method was empirical and it was based on the analysis of the field data. In this regard, the process of the landslide formation, its causes and morphometric characteristics in three classes of slide area, mass movement and displacement parameters along with deposited materials in Saymarreh Dam lakes were studied. The results relevant to the morphometry of the landslide indicated that various factors were involved in the occurrence of Saymarreh landslide. Among these factors, undercutting of the Asmari limestone layers made by Saymarreh and Kashkan Rivers, particularly in front of the landslide, was the most important cause of the landslide occurrence. The landslide had formed a large lake behind the slide mass and had formed sequential terraces due to repeated slides. The results of the morphometry of the lake, particularly through the estimation of its water (45.642 Gm3) and sediment volume (23.422 Gm3), and comparison of the time taken for filling of the water volume (19.8 years) with the time required for deposition of the whole sediment volume (1888 years) showed that the sediments have not been deposited only during one stabile period of the lake and the lake has been renewed at least at several stages. As a result, the reoccurrence of Saymarreh landslide at several times led to the obstruction of the Saymarreh River. Stratigraphy studies on the lake sediments and the age of its terraces clearly implied the renewal of the lake at least at 4 stages. The sequences of the lake terraces and other evidences confirmed the different scales of the reoccurrence of the large Saymarreh landslide. Discussion and conclusion: This landslide obstructed the Saymarreh and Kashkan rivers and led to the formation a large lake in that region. The lake depleted after destructing the landslide mass, and there was a change in the direction of the Kashkan River.
The main triggering factor for this landslide was undercutting of Saymarreh and Kashkan rivers. Other factors included the direction and the angle of the slope, steep structural slopes, and gravity. The results obtained from the morphometry of Saymarreh Lake and stratigraphy of the lake sediments demonstrateed that Saymarreh landslide had been reactive several times and led to formation of the lake at several stages.

The prediction of the occurrence of floods and the reduction of damages caused by it is strongly influenced by the modeling of physical phenomena and the spatial-temporal distribution of precipitation. The purpose of the research was to optimize the rainfall gauging network in Kurdistan province using Kriging estimation variance and taking into account the topography of the area. In this study, to optimize the rain gauging network in Kurdistan province, rainfall data of the rain gauging, synoptic, and climatology stations were used. In order to reduce the costs, stations close to each other that are located in the same height range and also have the same error variance, were removed from the existing network. In order to reduce the maintenance cost of the stations, after clustering of the area, 8 stations whose removal had little impact on the accuracy of the data, were identified in the province. Then. In order to strengthen the network, the optimization of new stations was put on the agenda and 28 points were set as the proposed stations.

After reviewing the existing stations’ data, 145 stations were selected for the analysis and optimization of the existing network. After selecting the normal data and spatializing them, due to the large extent of the area and the variability of the average annual precipitation, Kurdistan province is divided into smaller regions with less variations in the average rainfall. The regional division or clustering of stations is carried out using the functions available in the ArcGIS 10.2.2 software and based on the main catchment basins. In the next step, the spatial distribution of rainfall and the variance of the errors in all clusters are calculated separately. Given the importance of highlands in receiving rainfall and supplying water, the distribution of rain gauges on elevation layers has been studied. At this stage, redundant stations were eliminated, and stations which are located in close proximity of each other, and are located in the same elevation range and also have the same error variance, can be eliminated too. At the final stage, adding new stations and strengthening the network took place. At this stage, the priority is to build the station for areas where the variance of the errors is high. After adding each station, the error variance of the whole system is calculated again. Adding a new station to the network will continue as long as the network error reaches its minimum.

1-Normality test of data
After spatializing the rainfall data, their normal distribution was investigated using the Kolmogorov – Smirnov test. The results show that the distribution of data at 95% level does not have a significant difference with a normal distribution.
2- Division of the region and clustering of stations
In this study, using the region’s digital elevation map, and based on the analyses made in the software ArcGIS 10.2.2, clustering of stations and division of the region was carried out. The entire area of interest is divided into 8 clusters.
3- Calculating the Kriging error of the existing network
The amounts of the rainfall data error can be obtained by calculating the Kriging error of the existing network. As mentioned in the previous sections, the calculation of the error in the Kriging method is a function of semi-variogram (spatial structure) of the variable and this feature increases the estimation accuracy of the variable error.
4- Distribution of the stations on elevation layers and determination of the redundant stations By studying the distribution of the stations on altitudes, stations which had no impact on the accuracy of data extraction were removed. The candidate stations for removal were located in a same range of elevation, and showed similar error values. In order to be sure of the decision taken, by eliminating each station, the overall error of the network in each cluster is calculated, and an increase in the error values represents the wrong station is being removed.
5- Adding the proposed stations and calculating the variance of the new network error
Adding new stations to the network is done based on the Kriging variance. The priority of the station construction is for areas that display a high error. In the Kriging error variance method, adding a new station to the network is done based on Eó2 (error variance), in a way that points with equal error variance or greater than the value of data variance is considered as the first priority for the construction of the station. The points whose error variances are between the variance of data and ½ of the variance of data, is the second priority and finally, the third priority belongs to the points whose variances are between ½ and ¼ of the variance. In this research, based on Kriging variance, 28 stations have been proposed to strengthen the rain gauging network in Kurdistan Province.

Given that precipitation is considered as the main entrance to the planning of sustainable water resources development, in this study, the optimization of rain gauging station network in Kurdistan province was investigated using the Kriging error variance. In previous studies, generally, entropy has been considered as the main model for network modification, therefore, due to the limitations of these methods in not using the semi-variogram features, in this research, the geo-statistic method based on kriging error variance was used due to its high accuracy. The amount accuracy increase in this method depends to a large extent on the semi-variogram features (spatial structure) of the precipitation, which can be used to calculate the error variance rate for the new station before the construction and inventory of the station. In order to strengthen the network, the optimization of new stations was put on the agenda and 28 points were set as the location of the proposed stations. For practical comparison of the results, the error variance values were calculated before and after the addition of the proposed stations, the average error variance of the annual precipitation in the province decreased by 11%, with the largest decrease belonging to the central part of the province with 24.03%.

Benarvan Fault with the length of more than 20km is one the most important faults existing in Azarbaijan region which is located on the southern flank of Bozghoush Mount of Azarbaijan with the general orientation of southwest- northeast. In this research seismicity and seismic risk were determined by deterministic and probabilistic methods and the obtained results were analyzed. To do so, first, existing seismic sources and faults of the region and surrounding regions were identified and investigated in a radius of about 100 km and their characteristics such as length, orientation and distance from the center of Benarvan Village were determined. Then the maximum credible earthquake resulting from the activities of these faults was calculated by using deterministic and probabilistic methods. The Gutenberg-Richter Method was applied for calculating the return period of earthquake magnitude, as well. In fact, in this section the magnitude return period was calculated for the 100 km extent of the region by using the statistical methods. The results of the calculation of return periods for various magnitudes showed that the return period for an M7 earthquake was about 107 years.