GEOGRAPHICAL DATA
Year:2019 | Volume:27 | Issue:108 |Papers Count:15

Extended Abstract The troposphere is a layer of atmosphere that consists of dry gases and water vapor, which causes a time delay in the emission of electromagnetic waves resulting in an error in determining the precise position. In space geodesy, normally, the travelling time of the wave between an emission source in space (a satellite for GNSS or a quasar in VLBI) and a receiver located in a geodetic station on the surface of the Earth is measured. This time is then converted to distance by the speed of light in vacuum. There are two ways to manage the atmospheric delays in space geodetic data analysis; either, external measurements of the atmospheric delays are used to correct the measurements or, the atmospheric delays are estimated in a least square adjustment as the unknowns. To model this error using the first strategy, several methods have been proposed, among which, the most prominent ones are the three dimensional (3-D) ray tracing and the use of mapping functions. 3D ray tracing is considered to be a direct method for this estimation and the actual path of the wave which is curved, is estimated by using Eikonal equation and is compared with the theoretical straight path. It means we can find the amount of correction which should be considered. Contrary to this method, the use of mapping functions is considered as indirect method and by using proper functions, the amount of delay (hydrostatic and non-hydrostatic) in the vertical direction is plotted in the desired direction. The basic assumption in this method is to take the azimuth symmetry for the troposphere into considerations and therefore, the amount of delay will depend only on the elevation angle. In this paper, comparisons have been made between this method and the method of using mapping functions that are commonly used. Based on this research, it is determined which method to be used in different conditions to achieve the desired accuracy for space geodesy techniques such as GNSS and VLBI, and which method is the priority. In this comparison, VMF (Vienna Mapping Function) and GMF (Global Mapping Function) which are used widely in space geodetic techniques were used. Coefficients in these mapping functions are obtained based on Numerical Weather Models (NWMs) and specially ECMWF. VMF is called Isobaric Mapping Function (IMF) based on the older mapping function, and GMF function has been created with changes in VMF, so that it can be used offline in some software including VieVs software. To this end, data from two observation campaigns managed by IVS (International VLBI Service) namedCONT08 and CONT11 have been used in the years 2008 and 2011 for VLBI stations. These two campaigns involve 15 days continuous observations. The results of this study show that the station with the highest humidity (KOKEE) requires ray tracing at all intervals of accuracy and mapping functions cannot be used to produce reasonable accuracy. Also, in order to achieve the accuracy of less than 10 mm in the station's elevation, it is necessary to use ray tracing at almost all angles of elevation, or in order to achieve the accuracy of less than 20 mm, it should be used at the angles of elevation of approximately 0 to 35 degrees, and mapping functions can be used for the rest of the angles of elevation. Based on the diagrams and tables presented in this paper, the following results can also be extracted:-Use ray tracing method at the station with the highest humidity (KOKEE)-Use ray tracing to achieve an accuracy of better than 10 mm for the stations’ elevation at all angles of elevation -Use ray tracing to achieve an accuracy of better than 20 mm for station’ s elevation of approximately 0º to 35 º of the angles of elevation. Mapping functions can be used for the rest of the angles of elevation.-Use ray tracing to achieve an accuracy of better than 30 mm for the station’ s elevation of 0 to 26 degrees of the angles of elevation. Mapping functions can be used for the rest of elevation angles.-At angles of elevation which do not require ray tracing, mapping functions are used. It can be said that in 2008, finally, GMF mapping function achieved a better accuracy than the VMF, while in 2011, the performance of VMF mapping function was better than that of GMF.

Extended Abstract Introduction: Initially, researches were conducted on the positioning inside and outside of the building separately, and separate methods have been presented to determine the position inside and outside the building. But today, they are seeking methodswithout borderfor the positioning that can be used to conduct both indoor and outdoor location. Today, location-based services are one of the most widely used programs in mobile tools, but there are two obstacles that prevent these services from using their full potential. First, the location of individuals is not accessible at all points. The second obstacle is the lack of an integrated service to determine the position. The second obstacle has been addressed in this research. Users tend much to do the integrated positioning in internal and external environmentsusing their mobilephone devices. There are various methods for positioning in interior and exterior environments with respect to their characteristics. Therefore, in order to use the appropriate method for positioning in any environment, first there is a need to know the environment. Materials & Methods: In this research, the definiteexpert system was used for the detection of the environment. In the definite state, the existing space is divided into two internal and external parts. The internal space is the internal parts of the building and the rest of the spaces are known as the external space. First we specify the various factors in the detection of the environment, and then, to establish the knowledge base by definite method, different modes of the combination of factors were taken into consideration and finally, the results of each method were investigated. In order to detect the environment, four factors of light, numbers of satellites, accuracy and waves of wireless network were used. The expert system was used for decision-making. Regarding the number of satellites, it can be said that since receiving the waves of satellites in internal environments is difficult and the communication of the receiver with a number or all of the satellites is interrupted, therefore, it is expected that the number of satellites whose waves are receivable inside the building to be less than the satellites which are located on the horizon of that region. Another one of the factors of environment detection, the satellite signals are received by the receiver and the positioning is done. Due to the presence of the building and obstacles in these areas, the positioning is done with low accuracy, therefore, given that the accuracy of positioning in external environment is higher than that in internal environment, the detection of environment can be carried out with respect to the measurement of the positioning accuracy. One of the factors that indicate the accuracy of positioning is the DOP value. The accuracy of the two-dimensional positioning is determined by HDOP which indicates the accuracy of planimetric positioning. Given that the accuracy of positioning using GPS in the external environment is better than the internal positioning accuracy, therefore, the HDOP values in the internal environment will be higher than external environment. The power of received waves of wireless networks depends on the receiver’ s distance from the transmitter. The more the receiver is close to the transmitter, the greater will be the power of the received waves. Since the wave transmitters of the wireless networks are usually installed inside the building, therefore, the receiving power of these waves inside the building will be higher than the outside. Therefore, it is possible to perform the detection of the environment by measuring the receiving power of these waves. Researches show that the amount of light for indoor environment is generally much lower indoor than open or semi-openspaces, even in cloudy and rainy days. This is true even when the light sensor is rotated downwards. Its main reason is that the intensity of the sunlight is in the visible spectrum which is usually much higher than lamp light. Moreover, the light sensor has the ability to detect the light in the invisible spectrum like infrared and ultraviolet. When the sunlight and artificial light appear to be the same, the bright flux of the sunlight is much higher than the artificial light sourcesthroughout the day, therefore, the indoor environment of the building can be different from the outdoor in terms of the light intensity. This research was implemented in the mapping department of KhajehNasir University. The outer area of this university was considered as the outdoor environment and the corridor of the mapping department building’ s ground was studied as the internal environment. Results & Discussion: To create a classical expert system, the thresholds of each of the factors were determined by the measurements done. Then, for different modes, the necessary rules for detecting the environment were defined and the knowledge base was formed. Finally, after the formation of the database in different parts of the study area, the system was evaluated and its results were presented. We divided the study area into two internal and external environments. To evaluatethe results, we were deployed in each of the aforementioned places4 times, and we matched the environmentdetectionby the system with the reality and evaluated the amount of system accuracy. Conclusion: The results of this method show that the best result has been obtained when the light, accuracyandthe waves of wirelessnetwork were used. 92% of the detection of environment has been carried out correctly. The results also showed that in some exterior area, the detection of environmentwas associated with mistakesdue to the presenceof false ceilings and insufficient light. In the case of the accuracy and the number of satellites, in the external areas where there were high walls and satellite waves were not well received, the detection of environment was not done correctly.

Extended Abstract Introduction: Strategic and important industries are established in areas with possible access to water. Industrial development requires abundant water. Analysis of environmental resources and their pollution is the first consequence of industrial and human activities. Therefore today, due to the large volume of discharge and pollution in the environment, direct use of water is neither reasonable nor possible. Discharging industrial wastewater in land could severely contaminate the groundwater. In oil pollution monitoring researches, it is noteworthy that pollution detection and renovation operations require time and economic costs. Contamination of Soil and groundwater with pollutants such as hydrocarbons and chemical solvents has various environmental impacts. In Iran, the concentration of pollutants in some groundwater resources has been reported to be up to three times more than the standard value. This indicates the effect of a large amount of waste in the area which decrease soil quality in a way that soil layers are not able to compensate for it. Therefore, wastewater changes the drainage of underground water resources. In Iran and many other countries, causes such as leakage from contaminated petroleum storage tanks, leakage from transferring lines due to worn pipes, transportation of oil products, etc. in oil extraction mines, and refineries results in groundwater and surrounding areas facing oil leakage. Materials & Methods: The purpose of this research is to produce the water quality map of Shazand plain in Markazi province using Geographic Information System (GIS) technique and to investigate the effects of oil industries on the quality of underground waters. The first step is to identify areas affected by these oil industries and identified factors. Appropriate agricultural areas with water supply in the qualitative range were also identified. The location of existing wells in the plain, particularly wells located around the refinery and petrochemical complexes were investigated for the first time. Then, considering the direction of the water land in the plain and the paths of wells located at upstream mountains to downstream ordinary rivers, wells located in the refinery and petrochemical complexes were selected. Accordingly, 14 wells were sampled in the first stage and their coordinates were obtained using GPS. The samples were classified in the laboratory into four groups including physical parameters, chemical parameters, oil and water aromatic parameters and water volatile organic compounds parameters. In the next stage, the maps of water quality parameters zoning were prepared using the "Geostatistical Analyst" developer with the use of the interpolation method of "Inverse Distance Weighting (IDW)". Finally, spatial variations and the groundwater quality changes were investigated. Results & Discussion: Oil and aromatic parameters of water are presented along with the results of laboratory analysis in table 2. Results indicate that the numerical value of many parameters were less than 0. 1 mg/L. Just two parameters (Anthracene and Pyrene) in well no. 10 had a value of more than 0. 1 mg/L. Yet, the total value of oil pollutant was quite different. In wells no. 3, 8, 9, and especially well no. 10 the value was more than 0. 1 mg/L. The zoning map and spatial variation trend, along with statistical-descriptive indexes of total petroleum hydrocarbon of wells were also produced. The spatial variation of oil pollutants in Dashte-Shazand wells in south-north direction showed an increasing trend, which gradually changed into a decreasing trend. A decreasing trend was also observed in west-east direction. Comparing descriptive-statistical indexes with the standard level, we concluded that the total oil pollutant parameter near well no. 10, which is located in petrochemical complex faces contamination. Conclusion: The present study sought to measure some important indexes of oil contamination in groundwater and surface water near Dasht-e Shazand refinery and petrochemical complex. Therefore, data were collected from 14 wells in the study area. Then, oil and aromatic products were analyzed in laboratory. Using geostatistical technique, spatial variations of quality parameters concentration were investigated and compared with the desired and standard level. Results indicate that most of the wells near Dashte-Shazand refinery and petrochemical complex do not show any sign of contamination. Yet, the concentration of Anthracene and Pyrene parameters in well no. 10 is several times more than the standard level. This can increase the potential of contamination in Dashte-Shazand ground water resources. In wells no. 3, 8, 9, and especially in well no. 10, total petroleum hydrocarbon (TPH) was more than other wells. According to the TPH and PAH results, the contamination potential of well no. 10 was quite large. Due to the development of Shazand refinery, ground water resources of the area face an increasing danger of contamination. Moreover, the area has a high potential of population increase in residential areas. Thus, water contamination can also endanger the local environment. This shows the necessity of an appropriate management plan and regular monitoring of ground water, surface water, soil and air in the area.

Extended Abstract Introduction: Due to the large dimensions of earthquake damages and losses, more rapid procedures are required to identify damaged buildings. Field studies and old procedures are no longer efficient enough because of being time consuming, costly and requiring lots of workforce. This research seeks to identify the buildings damaged by earthquakes through analyzing the spectral response of urban houses to the reflective bands and effective factors, before and after the earthquake, for recognizing buildings damaged in the earthquake and compare the results of the reflective bands with each other, and then, determine the most efficient band among them. The earthquake stricken city of Bam was selected as the case study of this research. In order to identify the damaged urban houses, satellite imagery and remote sensing reflective bands were considered for detecting the changes, distinguishing the bands, and analyzing the spectral reflection profile. Materials and Methods: The high resolution Quick bird satellite, photographed the city of Bam just eight days after the earthquake on January 3, 2004. The satellite also had taken a clear image of Bam about three months before the earthquake on September 30, 2003, that, with regard to the objectives of the research and the capabilities of the images taken, these Quick Bird satellite images were selected to study and investigate in this field. The method of this research is to analyze the spectral reflection profile and the factors affecting it. Since the multi-spectral remote sensing is a set of reflective, emissive or backscattering energy from the study area in electromagnetic multi-spectral bands, the aim of this research is to describe why terrestrial phenomena show different responses to the electromagnetic spectrum, and to analyze their spectral curve as well. To this end, we established an analytical strategy to achieve a better interpretation of the blue (band 1: 450-520 nm), green (band 2: 520-600 nm), red (band 3: 630-690 nm), and infrared (band 4: 760-900 nm) reflective bands. And the earthquake stricken city of Bam was selected as the case study of this research in order to identify the damaged urban houses by analyzing the spectral reflection profile and factors affecting it. Results and Discussion: Urban housing is composed of various materials (concrete, asphalt, metal, plastic and soil) by man in various ways for building houses. When earthquake strikes, these houses might be destroyed. Therefore, satellite multi-temporal images before and after the earthquake were selected as data for analyzing the electromagnetic spectrum curve of the study area. In this research, the vulnerability of urban houses is different from one place to another. Therefore, educational samples of the case study from different parts of the city such as those which have been completely destroyed, partially destroyed or have remained intact, were selected. Then, the spectral response analysis of the urban houses was carried out in 4 blue (band 1: 450-520 nm) green (band 2: 520-600 nm) red (band 3: 630-690 nm) and Infrared (band 4: 760-900 nm) reflective bands before and after the earthquake in order to identify effective factors and the bands independent of these factors comparing with other bands. The results show that, before the earthquake occurs, some factors such as shadows cause a sharp decrease in the reflection in all bands, the atmospheric scattering at short wavelengths with increasing spectral reflection, the angle of sunshine, type of material, the surface smoothness or roughness of the surface, the time of the day, the height and texture had a great impact on the 3 blue, green and red reflective bands. Infrared band with a rectangular shape in spectral curve is a band independent of the aforementioned factors (with the exception of the shadow and surface smoothness of the materials). Conclusion: The results obtained from analyzing the spectral response of the urban houses in four reflective bands (Blue, Green, Red and Infrared) indicated that in general, the urban houses had high reflection and shadows had less reflection before the earthquake. After the earthquake, urban houses showed an irregular and significant reduction in spectral reflection, and the spectral reflection curve was irregular as well. However, the method of analyzing the spectral reflection profile is a point estimation method and does not result in a map, and this method is often used to check the accuracy of other methods.

Introduction: One of the most important challenges of this era is the rapid growth of urbanization. According to the United Nations report, around 66% of the world’ s population, equivalent to 6. 4 billion will live in urban areas by the year 2050, while this number was only about 746 million people, equivalent to 30% of the world’ s population in 1950. This increasing trend is followed by the issues such as providing citizens with proper housing, providing energy, health services, education, employment, transportation etc., which should be resolved by appropriate policies and solutions. In this regard, modeling urban growth might play a key role in guiding urban strategies. Planners have traditionally used various models to formulate urban growth. However, these models lack sufficient dynamism and mobility and do not take the social behaviors of individuals and their interactions into account. The shortcomings of the previous methods have led to an increase in the use of modern modeling methods like cellular automata and agent-based model, particularly when presenting a perspective of the future urban growth is expected. Although the use of agents is a common tool in the modeling of the earth systems, few studies have been carried out in this regard in Iran, and various existing foreign studies are not in full agreement with the existing situation yet, due to the complex nature of the land use change problem. Therefore, researchers are still trying to provide new models by focusing on available findings and different aspects of the problem. In this research, a multifunctional system has been developed for the simulation of the urban growth by integrating the irregular cellular automata and the agent. Materials and Method: The study area in this research is NajiAbad in the city of Kashan that is one of the city’ s new districts. The texture of this district has taken shape in a designed and regular manner. The average area of its parcels is 250 square meters whose formation is mainly towards the northwest-southeast direction. Land use map of the year 2006 (1385), slope map, soil type, access map, floodway and river map were used in this research. The data of the year 1385 are used for the simulation of urban growth in 1392 and the results are compared with real data of 1392 and thus the results resulted from the model are evaluated. We have presented forecast of urban growth for the year 1400 subsequently. In the presented model, cadastral polygons act as irregular automata which have their own status and properties. In this model, the changes are updated in each replication, and each time step is considered to be one year. The first step in the evaluation model is the overall proportion of the land parcels which is one of the effective parameters in the decision-making process of the agents. The calculation of the spatial proportion of the parcels for development is carried out by irregular cellular automata and based on four criteria of neighborhood, physical proportion, accessibility and constraints. Twelve effective factors were classified in proportion with these criteria and were normalized before the combination. The overall proportion of each land parcel has been calculated based on weighted linear combination function. In the next steps, the activity of the agents starts in the model. Many actors play roles in the development of the urban environment. In this research, the agents are classified into 3 general classes of urban planning agent, developing agents and family agents. The family agents were classified into 3 classes of families with high, medium and low income according to the income level of the families. The urban planning agent estimates land demands and issues the segmentation permits for a number of lands. The developing agent calculates the profitability of the parcels, and segments those having separation permits and high profitability. The family agents search the environment and choose suitable land for habitation based on their preferences. This process is followed up until all family agents are settled and the demands are achieved. Results and Evaluation: In this research, the output of the model and urban growth map in the study area for the year 2013 (1392) is calculated based on the input data of 2006 (1385). In this research, each time step is considered to be one year. In order to evaluate the model results, real data of 1392 has been used. In this research, the error matrix was used to calculate the accuracy of the results and comparison criterion is Kappa index. The Kappa index is a value between 0 (nonconformance of the calculated and observed maps) and 1 (full match of calculated and observed maps). Although there is no global standard, the Kappa index greater than 0. 80 is often considered as a criterion of the proper conformation of calculated and observed maps. The Kappa index in this research was calculated to be 71% based on the error matrix. In this calculation the area of the previous developed regions has been eliminated. Although the elimination of the area related to these regions relatively reduces the overall accuracy of the model, it leads to a more accurate evaluation of the results. The accuracies of the user and producer in the developed lands feature a higher overall accuracy of the model, which can be a reason for desirable design of the model and its adaptation to the reality. Conclusion: In this research, cellular automata were used to simulate the variations in the status of each land parcel in comparison with different spatial factors. Although the conventional cellular environment in cellular automata methods facilitates the possibility of urban growth modeling, it was attempted in this research to conduct modeling on the scale of irregular polygons of lands and in the form of base parcel. Although the use of cellular automata on this scale makes calculations more complicated and difficult, the results of modeling can be evaluated more realistically. In this research, the agents were classified into 3 general classes of urban planning agent, developing agent and family agents. The family agents were classified into 3 classes of families with high, medium and low income according to the income level of the families. The evaluation of the results with real data showed that the accuracy of the model was 71%. This study has been conducted in a vector structure and local scale that can be extended to other areas. This modeling can be done on a regional scale in future works.

Introduction: The natural behaviors of the human life environment where the settlements are constructed without recognizing and studying these behaviors are called hazards. The distinctive features of natural hazards are the changes in the hazard severity in different locations, as in the urban environments, human activities along with greater vulnerability in the environment, aggravate the hazard and the extent of its occurrence. The city and its infrastructure development in providing security and various needs of human are of the most substantial areas for the development of social life. In general, identifying areas prone to hazards is a key tool for decision makers to reduce the damages caused by natural hazards. On the other hand, abstract study of the nature’ s behaviors in the form of flood, earthquake, land slide and subsidence has always made managerial decision-makings difficult, so that avoiding the aggravating factors of a hazard has caused to get close to another hazard. Objectives: The main objective of this study is to evaluate areas affected by these four natural hazards in all 22 Districts of Tehran City. In other words, this research with the aim of comprehensive and integrated zoning of hazards such as flood, earthquake, landslide and subsidence has proceeded to identify, evaluate and adjust the findings in the form of a comprehensive map of the susceptibility of these behaviors under the title of four environmental hazards within the 22 districts of Tehran city. Discussion: Multiple-risk analysis, including a range of data, provides a more realistic model of the natural environment management. In this regard, studies have been conducted on the various approaches to analyze spatial data, how to create a combination of environmental hazards and how to determine their risk and vulnerability levels. To generate a probabilistic model, the basic assumption is that the risk level is determined by risk factors and possible hazards in the future, and with an emphasis on the past events. In this study, the creating and effective factors in environmental crises are related and calculated with each other with respect to several risks. Research Methodology: One of the usual algebraic methods is the Analytic Hierarchy Process (AHP), which, as a weighted evaluation method, evaluates different scenarios and selects the best option by combining the qualitative and quantitative factors. The Analytic Hierarchy process as one of the multi-criteria decision-making methods provides the ground for performing applied spatial analyses by examining the effects of different factors in contradiction with each other. The research method is quantitative-analytical, and all the factors affecting the occurrence of each hazard have been identified and digitized in ArcGIS environment and modeled using Frequency Ratio (FR) model. Then, each of the four susceptibility maps was combined in fuzzy method and the final susceptibility map was classified into 5 classes of very high, high, moderate, low and very low susceptibility, and was extracted and presented as a map and a table. Results: This research resulted in the production of the susceptibility zone map for more probable hazards including flood, earthquake, landslide, and subsidence of Tehran City in the separation of 22 Districts. This map includes several factors such as slope degree, slope direction, slope shape, elevation layers, distance from the river, distance from the road, distance from the fault, geology, land use, and the rain The result show that the effective factors in flood are the distance from the river, and the slope; the most effective factors in the destruction are the wasting of groundwater and eliminating the geotechnical properties of the soil; the most effective factors in the occurrence of earthquake are the distance from the major and minor faults which determine the length of major and minor faults. Based on the results of this research and their analyses in Tehran’ s districts, areas with very high, high, moderate, low and very low susceptibility were observed. Then, considering this study, their percentages were calculated in each class and reported in the form of a table. Among the 22 districts of Tehran city, districts 1, 3, 18, 5, and 4 are more susceptible than the rest of districts and districts 9, 10, 11, 12, and 17 are less susceptible in terms of the four aforementioned hazards. Therefore, it is recommended that the process of reinforcement and standardization of existing facilities and infrastructure to be implemented by prioritizing hazardous zones. Concerning the construction and development of new infrastructure and facilities, the occurrence and exacerbation of these natural hazards within the hazardous areas may be prevented by imposing restriction or not issuing construction permits.

Introduction: In today’ s complex and growing world, population growth, changes in the patterns of consumption and quality of life in rural areas have led to many environmental problems. One of the most important problems derived from this issue is the production of rural wastes and their inappropriate management. In the past to the present, waste management has been carried out in an improper and insanitary way, such as removing wastes from residential areas, dumping them on the roadside and burning them. Waste disposal in the aforementioned methods is not only the solution to the problem in the right way, but also the transformation of one type of contamination to another one. This method of waste disposal which is conducted without observing the technical principles, environmental standards and conditions of the region, will create the possibility of environmental, economic and social harms to the region and threaten the rural environment. The solution to this problem is to locate appropriate landfills for rural wastes. This research has selected the southern Soma village in the city of Urmia as the area of interest or study area of this research, considering the above mentioned topics. Material and Methods: In this research, which is an applied research in terms of the objective, and a descriptive-analytical one in terms of nature, Multi Criteria Evaluation method (MCE) and Geographic Information System (GIS) have been used to identify suitable waste disposal sites. Multi Criteria Evaluation (MCE) is a method used to combine data in terms of their importance in a particular decision-making process. Conceptually, MCE methods including weighting, scoring or quantitative and qualitative ranking of criteria are for demonstrating their importance with regard to one or a set of goals (Ian 2010: 239). Considering the objective of this study and the analysis tools, the implementation stages of the research are as the following: -Identifying the required parameters -Preparing and producing the parameters -providing the geodatabase and managing the data -Standardizing the sub-parameters -Weighting the parameters -Overlaying the layers Results and Discussion Identifying the Determinants: Based on the determinants and according to the Boolean logic, the areas of the South Soma village are either suitable (1) or unsuitable (0) for burying waste materials. The result of this action showed that nearly 70 percent of the village’ s area is not suitable for waste burial. In fact, based on the environmental standards of the Environmental Conservation Organization (ECO) of Iran and the related resources, no waste burial should be done in 70% of the village’ s area and these areas have been identified as the restricted areas for landfill. The first phase of locating landfill site: Based on the statistical information of the landfill locating map, 88. 92% of the total area of the village is not suitable for waste disposal. Due to severe and hard conditions of the region, the major part of the suitable lands have also many limitations and might be exploited for waste burial only with high economic costs. Therefore, waste disposal in the lands of this zone is practically unjustifiable economically or the topographic situation of the region makes it very difficult to exploit these lands. Accordingly, if we add the limited suitability zone lands to unsuitable and determinant zone, 94% of the village’ s area is not suitable for waste burial, and only about 6% of the total area of the village can be used for burying waste materials. The second phase of locating landfill site: The use of the slope control layer: Accordingly the slope parameter was overlaid on the landfill suitable zone. The slope factor managed to place about 2% of the total 6% of the suitable zone in the medium and low suitability zone, therefore, about 4% of the total area of the village with suitable slope and less than 15% will be suitable for landfill. Conclusion: In the present research, the suitable landfill sites were identified using Multi-Criteria Evaluation and Geographic Information System. To do this, the suitable lands were proposed for landfill by producing the maps of constraints, geomorphology, climate, water resources, socio-economy, environment and geology-hazards. The results of the first phase showed that about 88. 92% of the total area of the village was not suitable for landfill and the determinants and severe geographical conditions are the main obstacles for waste disposal in these areas. Based on the first phase of site location, only 6% of the total area of the village was identified to be suitable lands for landfill. In the second phase, the sites proposed in the first phase were screened again by applying slope control layer. The results of this overlay showed that by applying slope, 2% out of the total 6% suitable area in the previous phase were placed in moderate and low suitable zones. Accordingly, in general, 4% of the total area of the village with a slope of less than 15% were proposed for landfill.

Introduction: A Digital Elevation Model or DEM is a physical representation of terrain and topography that is modeled by a digital 3D model. DEMs have various applications in many fields. Today, with respect to improvements in technology and importance of generating DEM from every region in our country, the importance of satellite remote sensing is more sensible. One of the main topics in satellite remote sensing is radar remote sensing. In recent years, a number of satellites have been launched to capture SAR information from the surface of the Earth. The last project is Sentinel, and Sentinel-1generates SAR data. It generates images with medium spatial resolution from the Earth every 12 days. DEMs are generated through multiple methods, one of which is SAR interferometry. Material and Methods: The area under study in this research for conducting experiments and generating the DEM is Iran and the city of Tehran. Tehran is located in the north of the country and south of the Alborz Mountains, 112 kilometers south of the Caspian Sea. Its elevation ranges from 2000 meters in the highest points of the north to1200 meters in the center and 1050 meters in the south. In this paper, the Sentinel-1 stereo images are used to generate DEM. Tehran is located on part of these images. These images are shown in Figure (1). In order to evaluate the digital model generated by these images, a reference digital model which has been prepared from the city of Tehran with an accuracy of 1 meter is used. This elevation data was collected using terrestrial surveying and aerial photogrammetry. In this paper, radar interferometry was used to generate digital elevation model from the Sentinel-1 images. In SAR interferometry, the phase of images taken from various imaging positions or various imaging times is compared pixel by pixel. The new image is produced by differentiating between these values which is called interferogram. Interferogram is a Fringe interference pattern. Fringes are lines with the equal phase differences similar to contours in topographic maps. The phase difference obtained from SAR interferometry is affected by several components. Some of the most important components are orbital paths, topographic, displacement and atmospheric components. By eliminating the major part of the orbital component (and calculating the effect of other components or assuming their insignificance effects comparing with orbital and topographic components), since the topographic radar observes the Earth from two different points, the stereoscopic effect is revealed. This topographic component leads to fringes which encompasses the topography like contours. These patterns are called topographic fringes. Results and Discussion: In order to conduct the experiments considered in this paper, two mountainous and flat areas in Tehran are picked out and separated from the main image. The mountainous area is selected from the north and the flat one from the south of Tehran. The aforementioned technique is implemented and executed on these images. The generated DEM in these two areas is shown in Figure (2). After generating the Earth DEM using the Sentinel-1 images, and comparing it with the reference DEM having an elevation accuracy of 1 meter, the accuracy of the generated DEM was determined. As expected, the results in the flat area were more desirable compared to the mountainous area. The accuracy of the generated DEM was evaluated by creating a network with the dimensions of 138761 points from the flat area and a network with the dimensions of 78196 points from the mountainous area, from both generated and reference DEMs and comparing the corresponding elevations of the network points. Digital numbers of images represent the magnitude of error occurring in the generation of DEM. After testing the 3 error (blunder detection) and eliminating large errors occurred in DEM, a standard deviation error of 1. 26 meters for the flat area (South of Tehran), and 10. 32 meters for the mountainous area (North of Tehran) were obtained. Conclusion: Considering the development of technology and the launch of new satellite imagery projects from the Earth and the importance of the existence of a digital elevation model from the country, it is possible to recognize the importance of studying these images more and more. One of the latest satellite remote sensing projects is the Sentinel project. The Sentinel-1 radar images with medium spatial resolution capabilities provide the possibility of generating a Digital Elevation Model (DEM) from the country. This research is the first study on the accuracy of Digital Elevation Model resulted from the Sentinel-1 radar images in Iran. An elevation accuracy of 10. 32 meters in the mountainous area, and 1. 26 meters in the flat area were obtained. The results show that these satellite images have the capability of generating a relatively optimal DEM, particularly in non-mountainous area.

Introduction: Remote sensing science is one of the most powerful tools for the mineral explorations and mineral resource estimation. With regard to this science, any type of rocks with structural characteristics and mineral constituents has a special spectral signature, thus, using remote sensing techniques, different types of rocks in a particular area can be recognizable based on their reflective characteristics. Remote sensing techniques are considered as one of the standard methods in geological studies due to the identification of spatial patterns of rocks as well as their speed and economic price. Pervious geological studies indicate that the study area mostly contains basalt, limestone and marble, which has resulted in physical and chemical degradation of basalt stones under the influence of some geological events. Some parts containing basalt have lost their qualities due to these degradations. Therefore, the classification and separation of high-quality basalt zones from low-quality zones is the main objective of this paper. Materials and method: The main objective of this study is to identify high-quality basalt zones in the Dir-o-Morreh mine located 50 kilometers from Tehran city near the lake of Hoz-e-Soltan. Basalt is a dark-colored and fine-grained igneous rock composed mainly of plagioclase and pyroxene minerals. Typically, this type of rock is formed externally or in the presence of air, such as the flow of lava, and these rocks can also take form intrusively like igneous dikes or narrow pillars. The basalt in the Dir-o-morreh mine is of igneous dike basalt type. In this study, the ASTER satellite multi-spectral images were used. These images allow us to have a good spatial and spectral resolution with regard to the objectives. However, reflectance conversion and atmospheric corrections were carried out on these images before using them, in order to enhance the accuracy of the project. Aerosols contained in the atmosphere are liquid or solid particles suspended in the air, which are very important in the evaluation of satellite imagery for remote sensing. After applying pre-processing, Basalt Exploration Index (BEI) was introduced and used to identify the basalt. The BEI index has been extracted using various sources, including the basalt spectral signature provided by the department of applied mathematics and statistics of Johns Hopkins University, ASTER satellite behavior (defined by the space team of NASA and Japan) and the Earth’ s data which were collected to validate the results. This index has been able to identify different basalt zones, including major extraction zones and other potentially possible zones. Moreover, this index is able to completely separate the basalt zones from the surrounding areas (mainly limestone, marble and clay rocks). At the next step, convolution and morphology filters have been applied to separate high-quality Basalt zones from the low-quality. The amount of the brightness of an output pixel from the Convolution filters is a function of weighted average of the brightness of its surrounding pixels. Using convolution with the selected kernel in satellite imagery returns a new filtered spatial image. High-pass Standard convolution filter was used in this study, which eliminates low frequencies of an image by retaining the high frequencies. The morphological nuclei used in this study are only the structural elements of this project and should not be confused with convolution kernels. In order to control the obtained results, the classified zones were double-checked on the field. Results: The results obtained from the field studies and the identified zones are appropriately consistent with each other using the proposed index. Supervised classification was applied to improve the level of assurance and accuracy. Supervised classification is based on the idea that the user can select sample pixels in an image representing certain classes and then use image processing software using these educational samples as the referral for the classification of all other pixels in the image. This classification algorithm can be very effective and accurate and classifies satellite images in pixel-based or object-oriented form. Supervised classification can result in the preparation of two maps in two different classifications, which is has been done by using the Maximum Likelihood Algorithm. MaxVer or Maximum Likelihood is a statistical classification method that takes the weight of average value of the distance between the classes into consideration, using statistical parameters. To achieve sufficient accuracy, this algorithm requires a number of educational samples or pixels (more than 30). The primary classification includes 5 types of rocks or classes: high-quality basalt, low-quality basalt, limestone, marble stone, and clay which are designated on the map. In order to increase accuracy of the proposed method, the second map was prepared with 3 different classes (low-quality basalt, High-quality basalt, and surrounding rocks) in the second stage. Conclusion: These maps help us in preparing a new BEI which is more accurate and more capable. It was also able to prove its capability in the latest ground operations and determining the most zones with high-quality basalt.

Introduction: Land use is one of the most important indicators of economic and social development in urban areas, and has resulted in extensive changes in available structures and procedures of these areas. Therefore, human activities are known as one of the main principles and components of change in land use. Generally, land use changes are inevitable product of interactions between human activities and environmental elements. Remote sensing technology with capabilities such as providing update and reliable information about natural and urban areas, digital processing of satellite imageries, providing the possibility of temporal and spatial comparing of different phenomena, diversity of products, and etc. is considered to be a powerful tool in improving the efficiency of urban management. Consequently, remote sensing data are used to determine type, quantity and location of land use changes. Moreover, remote sensing technology is used extensively in land use maps all over the world. Many models have been applied to predict land use changes, which due to the complex, dynamic, and non-linear nature of the issue gained little attention. However, CA-Markov model, which is a combination of Markov chain and cellular automata, is commonly considered to be an appropriate and good method for spatial-temporal modelling of land use changes. In the present study, land use changes were investigated for a 15-year period in Shiraz using object-based image analysis. Then, a land use map was produced using cellular automata-Markov (CA-Markov) model to predict land use changes in the study area in 2020. Material & Methods: The present study includes two main phases. In the first phase, land use map of Shiraz was produced using Fuzzy object based analysis of satellite imageries. In the second phase, modeling and predicting of land use changes in 2020 were performed. Landsat imageries of the study area in 2005, 2010 & 2015 were used in this research. After preprocessing and preparing the imageries, segmentation procedure was performed as the first stage of object based classification using multiresolution segmentation algorithm. The nearest neighbor algorithm was used for object based classification of satellite imageries. Classification conditions were defined in accordance with each class properties, and classification was performed based on fuzzy operators of the classification operation. In CA-Markov model, the possibility of changing from one class of land use to another was calculated using transfer matrix table. Then, land use map of future years will be predictable in accordance with the transfer probability matrix, and desired time interval. Result & Discussion: In this study, scale parameter of 10, shape index of 0. 4, and compactness index of 0. 2 were extracted as the optimum conditions for segmentation. Apart from spectral data, information regarding the location, context, texture, normalized difference vegetation index, enhanced vegetation index, and digital elevation model were also used to improve the efficiency of classification phase. The results of model validation shows an overall accuracy of 89% and kappa coefficient of 0. 87. Therefore, the results of CA-Markov model shows a very good potential for predicting land use changes in Shiraz. Thus with the adjustment and calibration of model parameters and based on land use maps of 2010 and 2015, Shiraz land use in 2020 was predicted. Conclusion: Due to the complexity of modeling dynamic changes in urban land use, utilizing efficient and update methods of data analysis is crucial. Therefore, satellite imageries and object based image analysis techniques were used to prepare land use map of Shiraz based on the data collected over a 15 year period. By considering the defined land use classes (residential area, barren lands, street network and urban green space), optimum image segmentation parameters were found. Then, classification conditions were defined for each class using the nearest neighbor algorithm and fuzzy operators. In this way, image classification was performed. By analyzing land use changes during the 20-year period, we understand that residential area has increased from 38 square kilometers in 2005 to 142 square kilometer in 2020. Additionally, green space area faced a reduction of 4 km in the first 5 years of the period, while in the next 15 years green space area shows an increasing trend.

Introduction: Vegetation plays an important role in the cycle of energy, carbon, hydrology and bio-geochemistry. The climate and vegetation have a mutual effect on each other. For example, the surface vegetation affects atmospheric patterns by affecting the surface albedo (which determines the amount of radiation available for global warming, low atmosphere and evaporation as well). Therfore, the long-term study of the effect of the remot linking patterns on the varibility of vegetation is essential. So far, no study has been done on the effect of remote linking patterns on the varibility of vegetions. Therefore, the main objective of this study is to detect the vegetation changes in the month of May in Iran in relation to the remote linking patterns of the North Atlantic Oscillation. In this regard, remote linking patterns, such as El Nino have a significant effect on the surface climate with their periodic oscillations (Glantz, 1991). Many studies have been carried out in relation to the remote linking patterns and climatic elements on regional scale, but the role of remote linking patterns in the vegetation changes is a new topic which has been brought up lately (Wang et al., 2004). The normalized difference vegetation index (NDVI) obtained from the remote sensing satellite data is widely used to examine the vegetation features. Vicent Serrano et al. (2004) identified the positive and negative trends between NDVI and NAO in the Northern and Southern parts of Iberian Peninsula, respectively, by investigating the relation of NDVI, the North Atlantic Oscillation index (NAO) and the precipitation. Gouveia et al (2008) extracted the NAO correlation in the winter with vegetation activity in the spring and summer seasons by the combination of NDVI and luminosity temperature. Cook et al. (2004), Stockli and Vidale (2004), Sarkar and Kafatos (2004), Mennis, (2001), Erasmiet et al., (2009) also showed that there was a relationship between the remote linking patterns and vegetation in different parts of the world. Lu et al. (2012), showed that the vegetation impressibility in china in El Nino phase is greater than that of La Nino phase. Materials & Methods: In order to investigate the relationship between the North Atlantic Oscillation and vegetation changes in the month of May in Iran, the normalized vegetation index products of MODIS sensor (MOD13A3) were used during the statistical period of 2001-2014. By applying the NDVI 0. 2 threshold on the average long-term map of the vegetation index for the month of May in Iran, the area with larger and equal vegetation of the desired threshold was separated. Then, due to the severity and weakness of the NDVI values, the aforementioned area was divided into 3 areas based on the values of NDVI in order to assess the sensitivity of each area with regard to the remote linking patterns of the North Atlantic Oscillation which, helps identify the relationship between each vegetation category (namely, thinned, medium and dense vegetation) and the North Atlantic Oscillation index. Results & Discussion: Due to the existence of vegetation-free deserts in Iran, an area susceptible to vegetation was first separated based on the threshold of at least 0. 2 of the NDVI values. This region has about 38. 2% of the country’ s total area. Due to the high spatial variations in the NDVI values, the area was divided into 3 classes of thinned, medium and dense vegetation based on 0. 2 to 0. 5, 0. 5 to 0. 7 and higher than 0. 7 ranges. It was assumed that the area with thinned and dense vegetation had the highest and lowest sensitivity respectively, with regard to the changes of the remote linking patterns. The positive and negative phases of the North Atlantic Oscillation (NAO) have significant effects on the climate of Iran. For example, the amount of vegetation, precipitation and humidity advection in many parts of the West, Northwest, and Northeast of Iran in the February 2010 (as a negative phase), were much higher than that in the February 2014 (as a positive phase). A 14-year time series was prepared from the NDVI values of the May for 18363 points in Iran and, each point was calculated with the variations in the values of the NAO index of January to May in a Pearson correlation coefficient matrix (assuming that the NAO changes in January influence the vegetation of May in Iran). The results showed that the positive and negative correlation values in terms of spatiality can be observed in all regions without a regular spatial pattern however, the maps showed that negative correlation values have covered a wider range of Iran in January and February. This indicates that, in the positive phase of the pattern, the higher values of sea level pressure in the Azore region, coinciding with the poor moisture transfer and precipitation systems, have caused less vegetation in a few months later (May) in Iran. Conclusion: Given the highest coefficient of determination obtained in February(0. 77) in East Azerbaijan province, the vegetation values of May can be estimated for the index points located in the Northwest and western provinces using the state of NAO in the months of winter.

Introduction: The rapidity of urbanization, especially in developing countries, has led to the fact that half of the world’ s population is currently settled in urban areas. Most of these areas with high population density are vulnerable to crises (Shelter Center, 2010: xiv). The fact is that the increase in the concentration of physical capital, infrastructure and economic activities in the cities has led to the increase in adverse effects of natural disasters (Tangri et al., 2008: 30; Lall and Deichmann, 2012). Meanwhile, it has long been argued that the earthquake, as one of the most catastrophic and devastating types of natural hazards, especially in developing countries (Dong & Shan, 2013: 85)has caused lots of damages to the properties and assets in urban areas and around them, through the destruction of urban buildings and infrastructure, (Min et al, 2010). Like other developing countries, Iran has experienced a high level of urbanization that has completely changed the physical structure of urban areas (Soltani et al., 2011: 6644), so that by 2015, the urban population of the country has been 74. 3 percent, which is estimated to reach 91. 5 in 2050 (Statistical Yearbook for Asia and the Pacific, 2015). Increasing urbanization in the cities of the country along with unplanned development is one of the factors that boost the possibility of increasing casualties and damagesdue to the occurrence of natural disasters in the cities of the country (Pourmusavi, 1391: 40) and leads to the loss of resources and achievements whose reestablishment will take many years (Patterson et al, 2010: 128). Materials & Methods: The present research is of applied type with descriptive-analytical method. Thestatistical population is the buildings of district 9 of Tehran municipality. Tocomplete the library informationin order to understand the status quo, the studies and deductions of the Information Technology and Communication Organization of Tehran Municipality updated in 2015 were used. The indices used in the research have been weighted based on the experts’ opinions using the Analytic Network Process (ANP), and the obtained results have been applied on the layers under study in the GIS environment and the map of each layer has been prepared in the Geographic Information System. Finally, the general vulnerability map of the region was extracted through the integration of the layers under study (overlay). The opinions of the experts are determinant in evaluating thevulnerability of the city, butin this research, in order to reach a precise evaluation, along with the preparation of the map based on the experts’ opinions, the vulnerability scenario has been developed at different intensities, thereby to standardize the data, and to analyze the layers and criteria, the fuzzy model andthe linear threshold function have been used, respectively. The results have been categorized into 5 vulnerability groups of very low, low, medium, high and very high, and the percentage of each group has been calculated. Tools used in the research are SUPER DECISION and GIS. Results & Discussion: The present research was carried out aiming at vulnerability evaluation of urban buildings in district 9 of Tehran municipality to various intensities of earthquake, thus, in this research, the vulnerability rate of urban buildings to various earthquake intensities was measured using ten indices (type of material, type of view, building density, age of the building, number of floors, ground area of buildings, compatibility of neighboring uses, distance from fault, geological formations and the width of passages)along with the required sub criteria. To design the earthquake scenarios at different intensities, the first step was to accomplish stratification for each of the main criteria and sub criteria using the weights obtained from the ANP in the Arc GIS environment, then, the general vulnerability map of the region was prepared by overlaying the layers. Finally, the earthquake scenarios at different intensities were designed by fuzzification of the map. Conclusion: In order to determine the seismicity potential of the study area which is part of the primary and very important stepsin the process of the determination of vulnerability levels of various regions to earthquake, the preparation of the major faults’ map of the region, the preparation of the earthquakes epicenter map, the determination of the intensity and magnitude of earthquakes, the estimation of the features of earthquakes that are likely to occur by the significant faults of the study area were placed on the agenda. For this purpose, in order to evaluate the vulnerability of earthquake hazard, 10 indices were investigated as the effective factors on the vulnerability of urban buildings which have been selected based on the indices of previous studies. These indices (type of material, type of view, building density, age of the building, number of floors, ground area of buildings, compatibility of neighboring uses, distance from fault, geological formations and the width of passages) were analyzed using the ANP calculation method whichhad beenscored by the experts, and the weight of criteriawas applied to the effective layers of the vulnerability, and finally, the general vulnerability map was extracted by integrating the layers in the GIS environment. In order to evaluate the vulnerability rate of urban buildings, the data obtained from the ANP model was fuzzified, and the earthquake scenarios were ultimately designed based on the seismicity potential of Tehran faults and were applied on the general vulnerability map of the study area. The results of the research indicate that in an earthquake with a modified intensity of 6 mercalli, the vulnerability rate of urban buildings in the vulnerability ranges of very low, low, medium, high and very high are 26%, 56%, 17%, 1% and 0%, respectively and the damaged buildings in the districts 1 and 2 are in the vulnerability ranges of very low (28% & 24%), low (53% & 59%), medium (18% & 16%), high (1% & 1%) and very high (0%). In an earthquake with a modified intensity of 7mercalli, the vulnerability rate of urban buildings in the vulnerability ranges of very low, low, medium, high and very high are 21%, 10%, 52%, 16% and 1%, respectively, and the damaged buildings in the districts 1 and 2 are in the vulnerability ranges of very low (23% & 18%), low (11% & 9%), medium (48% & 56%), high (17% & 16%) and very high (1% & 1%). In an earthquake with modified intensity of 8mercalli, the vulnerability rate of urban buildings in the vulnerability ranges of very low, low, medium, high and very high are 7%, 4%, 10%, 61% and 18%, respectively.

Introduction: The construction of power transmission lines (PTLs) is one of the most important activities of the power industry of any nation in the development of power transmission network. Many technical, economic, environmental and social factors are involved in the issue of power transmission lines routing. These factors sometimes have co-directional and increasing effect and, in some cases, the effect is not co-directional and is even in opposite direction. Therefore, it is very important to determine the appropriate route for the power transmission lines which is in proportion with the needs and objectives of the project and to take the role of effective factors into consideration. Materials & Methods: In this research, factors and criteria effective in power transmission lines routing were investigated in the form of three economic, access and maintenance objectives of the power transmission lines and adverse environmental effects. Given that, the problem is multi-objective, the criteria of more than one objective function must be optimized simultaneously. This data set includes Digital Elevation Model layers, land slope, villages, land use, roads, power transmission lines routes, geology, landslide, soil type, soil erosion, rivers and protected areas. In order to weight the factors and their combination, considering the features of each factor, the Fuzzy Analytic Hierarchy Process (FAHP) methods and the Weighted Linear Combination (WLC) have been used. FAHP is a very useful method for multiple-criteria decision-making in the fuzzy environment, which has provided substantial applications in recent years. Also, WLC is an analytical method which is used in the time of multi-criteria or more than one criterion decision-making. Any feature taken into consideration is called a criterion. Each criterion is weighted based on its significance. As previously mentioned, the issue of the power transmission lines routing is a multi-objective issue. Since there is no single solution to optimize each objective simultaneously, there is a set of Pareto optimal solutions. This solution is called non-dominated or Pareto optimal that the values of none of the objective functions can be improved without reducing the values of one or several other objectives. Considering the presented explanation, in order to determine the appropriate route with regard to the multi-objective problem, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was used as an evolutionary multi-criteria decision-making method. The aforementioned model was used for the routing of 63 KV transmission lines between the two power stations of Shahid Salmani and Kiyasar in the city of Sari. The Arc GIS 10. 3, Matlab and Google Earth were used in this research. Moreover, GIS was used for displaying, managing, analyzing and storing large and various datasets. Discussion and Results: In order to solve the power transmission lines routing problem, different parts of this algorithm have been developed and expanded. In this research, an innovative operator was used for intersecting, mutating and non-dominated sorting. To determine the appropriate route based on the multi-objective, the algorithm must be run repeatedly and by using different parameters. In the present model, the objective functions are evaluated in every iteration in order to obtain the best result. In order to test and evaluate the efficiency of the algorithm, two samples of commonly used experiments in this field, i. e., repeatability test and parameter adjusting test, were used. The success rate of the repeatability and parameter adjusting tests for the presented model were 89% and 88%, respectively, which indicates the success of this model in both tests. The comparison of the best route generated from the proposed model with the existing power transmission line shows the improvement of the values of the objective functions, the reduction of 27 tension towers and 31 suspension towers and the reduction of about 6 km of the route length relative to the existing route of the power transmission line. Conclusion: The Final Results of the Research Indicated that GIS capabilities can be properly integrated with the NSGA-II algorithm which, has appropriate capabilities such as, less computational complexity, high speed implementation of the algorithm and elitism process to solve the problem of routing the power transmission lines, and are exploited by applying appropriate changes in this algorithm, and by employing the FAHP method for any type of route and routing problem Particularly in the field of distribution, super-distribution and high voltage power lines. In future researches, in case of having more comprehensive information layers such as wind, temperature, precise geological information, agrology and technical and specialized calculations like tension and compression in the towers, combining the proposed method with dynamic programming algorithms in the tower locating sector and the possibility of taking various equipment in different environmental conditions into consideration can improve the process and quality of routing. Also, in the future works, it is possible to solve the problems of locating-routing of towers and passing the route of the transmission line by taking technical, environmental, social and economic factors into consideration, using modern methods or other methods for optimizing multi-objective evolutionary algorithms.

Introduction: Statistics show that more than half of the world's population (54% in 2014) live in urban areas, although there are many differences between countries in terms of urbanization levels. For the first time in history, the urban population exceeded the rural population of the world in 2007. One of the most important problems of urban and environmental development is the shortage or lack of natural-regional parks in the center of the cities and in suburbs. Natural and regional parks have social, economic and ecological impacts in terms of the coherent structure which, is considered as a significant criterion for the betterment of the quality of living space and development of the community, with lots of benefits such as obtaining a suitable environment to develop the social coherence, maintain comfort and treat psychological and mental illnesses. Identifying the suitable locations for the natural-regional parks is one of the cases that should be taken into consideration regarding any type of development, including comprehensive plans, civil plans or regional plans. The purpose of this paper is to achieve the spatial organization of Mazandaran province in order to construct and allocate natural and regional parks in the regions of this province using the new scientific methods of spatial analysis in the GIS environment and applying multi-criteria decision-making techniques. Research Method: The process of this study is descriptive and analytical. Accordingly, the necessary data and criteria, including maps and information layers and satellite imagery were analyzed using ARC GIS 10 and ENVI 5. 1 software. In order to weigh, in addition to taking the experts point to the criteria into account, the Marinoni extension in Arc GIS software was used with regard to the hierarchical decision-making process. The main criteria used in this study are natural vegetation, transportation network, welfare and service centers, cultural-educational centers, commercial-residential areas, population centers, industrial areas. As it was mentioned, the information layers were provided for each of the influential factors, and a weight was assigned to each of the layers, and then, appropriate weights were assigned to each of the information layers based on their significance using hierarchical analyzing model to provide the spatial modeling, and the information layers were integrated, and the optimal regions were identified using the provided model. Results and Discussion: Identifying and selecting the factors influencing the location, are among the significant stages of the study. The more compatible are the identified factors with the land reality, the more satisfactory will be the outcomes of the location. Accordingly, in this study, weights have been assigned to each one of the weights based on the opinions of the experts, using the hierarchical model, and the criterion of the transportation network with relative normalized weight (0. 311) has had the most importance among the main criteria. Natural vegetation (with a normalized score of 0. 277), population centers (with a normalized score of 0. 271), and travelling facilities and services (with a normalized score of 0. 120) have been placed in the subsequent ranks, respectively. Accordingly, in this research, with regard to the opinions of the experts, four main criteria of industrial, population centers, commercial-residential, cultural-educational, welfare and services, transportation network and natural vegetation, each one of which includes sub-criteria as well, were taken into consideration. A combination of the AHP process and Fuzzy set was used for analyzing the spatial data, in order to evaluate the selected factors and the Geographic Information System (GIS) as well. As it is seen, areas with a very good desirability in Kalastan have accounted for 6. 6%, and areas with the lowest potential for the construction of natural-regional parks in Kalastan constitute 5. 5%. Similarly, areas with medium potential and regions with relatively appropriate potential in Kalastan of Mazandaran show an average of 12. 4% and 10. 1%, respectively. Estimates show that about 129817 hectares of the area of the province are susceptible to creating regional parks, i. e. the area No. 1, which will be a significant amount for the decision-makers and planners in the urban and regional areas in pursuit of achieving sustainable development and protecting the natural environment of this province. In the next regions, the priority of the selection will be with the experts and decision-makers of this field. Conclusion: The purpose of this research was to identify the areas susceptible to the creation of regional parks in the province of Mazandaran, in order to provide the sustainable financial resources for the management of the province while, protecting the natural resources of the province.

Introduction: The development of tourism throughout the world, and its ever-increasing economic importance has paved the way for the development of rural tourism and its impact on the rural development. Initially, this concept took shape by the development of urbanization, the rapid growth of transportation system, rising families’ incomes, and more attention paid to the way of spending leisure time in the country in the big cities and villages around them. First, Iran enjoys a great variety of cultural, historical and natural attractions, and is ranked high among the countries of the world in terms of capabilities. Furthermore villagers account for 30% of the total population of the country, and the revenues from the agricultural sector are not sufficient for creating the job opportunities and the income needed for the villagers. Therefore, working on is essential to provide the ground for social and economic development in rural areas. In order to explain the role of tourism in rural development, a comprehensive study has been carried out on the Moridan area and the factors contributing to this development have been evaluated. Finally, considering the capabilities, facilities and limitations in the region, an appropriate method was proposed. Methodology: The research method is descriptive-analytic and the information was collected through library studies. The information and statistics related to the government departments were obtained from them and the field studies were carried out through questionnaires and interviews. People needed for selecting the target population of the research were chosen for interview, using the Cochran’ s formula (with 95% of sample volume n=38) and from among 318 habitants of 11 villages and 20 families in order to increase its capability of generalizability using the descriptive and inferential statistics obtained from the research. Therefore, the collected data were entered into the periodic table and the standard deviation was determined using descriptive statistics, for all cases. Discussion: The village of Moridan is located near the county of Langroud. The study on the social, economic and natural structure of the region shows that agriculture, gardening and stock raising are among the most fundamental economic activities in the region, which is not able to meet the needs of local people on its own. Concerning the geography of the region and taking different aspects into account, tourism is considered to be the safest and most effective economic activity for the villages of the region. The following process was pursued in performing this research regarding the economic impacts of tourism in the region and to realize its objectives: 318 people were asked to fill out the questionnaires. 148 of those people had an average age of 45-65, which is considered the largest group, accounting for 46. 7% of the total number of interviewees. Interviewees over the age of 65 account for the least number among the different groups. 33% of the interviewees were government’ s employees, and 58% were self-employed. The education level of most of the interviewees was under high school diploma and about 35% of them had university degrees. Two significant economic variables were considered in performing the research, namely, the creation of job opportunities and the amount of income. In the studies done on the created job opportunities, directly or indirectly, as the result of tourism industry growth, the number of the region’ s tourists and the number of the jobs created were directly proportional to each other and, regarding the impact of tourism development on the number of the jobs in the region, the opinions of the majority of the interviewees were positive (x=4. 8) (very high). This issue was quite obvious, especially due to the number of villas and towns in the region (x=4. 7) and, has also had a significant impact relating the role of development. 4. 49% of respondents had positive opinions on the creation of new jobs and its impact on preventing the migration of young people to large cities, which is a remarkable percentage. Results: Regarding the increase in the average family income, the interviewees confirmed its positive impact (x=4. 42). Considering the increase in the average family income due to investing in construction, as well as the provision and distribution of construction materials in the region, and finally, tourism development, families have emphasized on the positive and key role of tourism in mass construction and consequently, the job opportunities. These opportunities include engineers, construction workers, masons, construction material workers, architects, etc. Considering the increase in family income, the provision of some rural items and handicrafts for tourists, tourists have emphasized the sale of rural products, handicrafts and dairy products to tourists, which represent the increase in the families’ income (x=4. 41). Regarding the positive role of tourism, most respondents have also emphasized on the increase of the families’ income (x=4. 55). The results also indicate that the growth of the capital owned by families is through the sale of their lands (x 4. 55). Overall, the findings of the research show that, tourism has a positive economic impact on the rural regions of interest and are also the basis for the proper growth of agriculture and stock raising in the region, and this is in close relation with the rapid growth of the activities related to tourism in the villages. Tourism has proven to be an appropriate means of growth and can help improve the quality of life, create job opportunities and increase the income of families. Planning for performing tourism activities through enacting rules and regulations can help promote the region’ s economy. The realization of the aforementioned objectives is subject to the provision of proposals in the form of short and long-term plans.