Land use planning is one of the essential aspects of sustainable urban development, aiming to balance land use in urban areas. This study seeks to identify the factors influencing the realizability of service land uses in Zanjan city through a futures studies approach. Data collection employed a combination of library and field methods. In the field phase, the Delphi method was used, engaging 35 experts in urban planning, urban management, and housing, who assessed key factors across two rounds of questionnaires. A total of 36 factors were identified across five dimensions: legal, economic, socio-cultural, physical-spatial, and managerial. The data were analyzed using MICMAC software. The results indicated that "urban land use laws and regulations" and "service location and spatial distribution" scored the highest direct influence values (85 and 82, respectively), playing the most significant roles in realizing service land uses. Key barriers identified include weak institutional coordination, inappropriate physical development policies, and lack of effective citizen participation. Cross-impact matrix analysis revealed a 55.32% fill rate, indicating a system of interdependent and mutually influential factors that contribute to the instability of service land use realizability. The study proposed solutions to improve the current situation, including: Revising urban laws and regulations, Strengthening institutional coordination among relevant bodies, Utilizing modern technologies such as GIS for proper service location planning, and Enhancing citizen participation culture in urban planning. The findings not only identified key influential factors but also emphasized the importance of considering multidimensional and sustainable aspects in service land use planning. This research provides a foundation for sustainable development and spatial justice in Zanjan city.
Today, the accelerating trend of urbanization, the lack of guidance and urban management, national and regional inequalities, and differences in the socio-economic base of individuals have led to the growth and expansion of informal housing. Due to this situation, informal housing has been expanding in Tehran's metropolitan area. The present study seeks to find key factors affecting informal housing in the study area and also to determine the relationships between criteria through structural-interpretive modeling (ISM). Are; Which is applied in terms of the nature of the application and in terms of the combined method (quantitative and qualitative) and in terms of the inductive research approach In this method, a questionnaire tool was used and in order to analyze the relationships and present their structural model, the interpretive structural modeling method was used, The results of MICMAC analysis and the classification of key factors in the four matrix clusters It shows that the factors of economic growth, redistributive policies, decentralization and transfer of authority, regional equilibrium policies, revision of development and sanctions laws and regulations and its effects are in the fourth cluster,which are in fact variables of research. In fact, key variables are research, and the only factor in housing policies is the cluster of link variables, which will guide other factors, and change will affect the entire system.
Landslides are among the most common and destructive natural hazards that change the shape of the earth's surface, and reviewing the damages caused by landslides, the need to investigate the factors influencing the occurrence of this phenomenon and predict its occurrence. proves that Khalkhal City, due to its special geological, climatic, and geomorphological characteristics and human activities, has been affected by the risk of landslides for a long time. Therefore, considering the importance of the issue; The purpose of this research is to produce a landslide risk map in this city. In this regard, first, the distribution map of landslides and influencing variables, including; DEM, slope, aspect, land use, lithology, distance from fault, distance from river, distance from road, and rainfall were provided. Next, after the fuzzy membership and determining the weight values of each factor using the CRITIC method, the landslide susceptibility map was prepared using the MARCOS multi-criteria decision-making method. The results of the study showed, respectively; that The factors of slope, land use, and lithology with weight coefficients of 0.148, 0.139, and 0.132 have the greatest influence on the occurrence of landslides in the region. According to the results of the research, respectively; 707.14 and 512.87 square kilometers of the area of the city are in high-risk and very high-risk categories, and these areas are areas that need management work and the implementation of protection projects. Also, considering the use of the ROC curve method the area under the curve (0.89), and the correlation of 0.83% between the final map obtained from the research and the distribution of sliding surfaces, the accuracy of the MARCOS method in identifying and zoning prone areas The risk of landslides in Khalkhal city is great.
Vulnerability is the inevitable result of risks and crises that threaten societies to varying degrees. One of the main threats is earthquakes. The recent approach to disaster management programs is to increase the resilience of communities that have different dimensions. One of them is the physical dimension of urban resilience, which is linked to the components of land use planning. In this research, with the aim of analyzing land use criteria affecting the resilience of Tabriz city and using fuzzy AHP method, research has been done. Based on the results of the study of theoretical foundations, 13 effective criteria have been identified and the basis of action. The required data were extracted and used from maps and spatial information of urban plans, especially the detailed plan of Tabriz, Then Using ARC Map10.3.1 software, each criterion is analyzed and each criterion is presented in the form of a fuzzy map. Sum, Product and gamma fuzzy operators have been used to achieve the final resilience map. Due to the high accuracy of the gamma operator, its results are considered as the final output. The results show that in the city of Tabriz, 2% have very low resilience, 40.8%, low resilience,15.3% moderate resilience, 23.5% high resilience and 7.2% very high resilience - based on the Used criteria-. Areas with low resilience are generally located in the north of Tabriz city and correspond to the informal settlement texture and the worn-out texture of the city, which corresponds to the fault line of Tabriz and Micronutrient and permeability are other features of these areas. Due to the high population density in these areas, it is necessary to immediately adopt the necessary programs to improve the quality of physical resilience criteria in the city.
Correct analysis of the housing market situation and correct knowledge of the factors affecting housing, especially in terms of its price and the extent of the impact of each of them, can help planners and officials in the correct analysis and forecast of the future situation and appropriate Provide appropriate solutions. The aim of this study was to identify the drivers of housing price in Khorramabad. Theoretical data were prepared by documentary method and experimental data by survey method based on Delphi method. The statistical population of the study is 30 experts and specialists in the field of housing in Khorramabad city were selected by purposive sampling. Delphi methods, cross-sectional analysis and MicMac software were used to analyze the data. For this purpose, first 23 factors were identified by Delphi method and using descriptive questionnaires by experts. In the next step, the matrix of cross-effects was designed to measure the impact of factors on each other and provided to experts. Finally, out of a total of 23 initial factors affecting housing prices in Khorramabad, 12 factors were identified as key factors of the system. Size: Household income, land price, building density, number of units and floors, access to urban facilities and services, population density, geographical location of lands, uninhabited future uses, number of rooms, security status, size of property plots, demand status.
for the spatial analysis of precipitation in the Middle East, have been used gridded precipitation data from the World Precipitation Climatology Center (GPCC) with a monthly temporal resolution and a spatial resolution of 0.5×0.5 arc degrees. Therefore, a matrix of 80 x 160 dimensions was obtained for the Middle East region (160 longitudinal cells and 80 transverse cells). The reason for choosing network data is their proper spatial and temporal separation and their up-to-date compared to station data. The period under investigation is from 1970 to 2020 AD. Finally, the long-term maps of the Middle East precipitation were drawn on an annual and monthly basis. The results indicate that precipitation in the Middle East tends to concentrate and cluster in the spatial and temporal dimension. In other words, due to the special geographical location of the Middle East region, such as uneven topography, distance and proximity to moisture-feeding sources (Caspian Sea, Black Sea, Mediterranean Sea, Atlantic Ocean, and Indian Ocean) and the direction of unevenness, Precipitation in high altitude areas, It is concentrated in the neighborhood of seas and oceans and also in the windy slopes of the mountain range of the region. The uneven distribution of geographical conditions has caused uneven distribution of Precipitation in the Middle East. So that; The center and gravity of the Middle Eastern Precipitation is concentrated in the eastern end of the Black Sea, southern Turkey in the neighborhood of Syria and Iraq, the Ararat-Zagors belt in the west of Iran, the southern shore of the Caspian Sea, the Pamir highlands and the Bay of Bengal in India, and the Hindu Kush highlands in Pakistan. Is. However, the many parts of the Middle East, due to their proximity to large deserts (African Sahara, Lut Desert, Dasht-Kavir, Arabia's Rab-al-Khali and Afghan deserts), have less than 100 mm of Precipitation. The results showed that the maximum Precipitation of this region has been transferred to the winter season, and the summer season is still the driest period in the Middle East, and only the coasts of the Indian Ocean and the Bay of Bengal have monsoon rains
The development of nature-based tourism is dependent on the introduction and attention to the attraction of natural tourism attractions. In fact, identifying the factors affecting the increase in the attractiveness of ecotourism and geotourias places is among the most important issues in the development of tourism and naturalization of an area. According to this, the purpose of the present paper is also to investigate the factors affecting the attractiveness of tourist and geotorrhean locations in the study area. The present research is applied in terms of purpose and in terms of its method, descriptive-analytic. The data collection tool and information questionnaire and interview are. The statistical population of the research is experts and specialists in Tourism in Khorramabad in Lorestan province. In this research, 50 experts and natural tourism specialists were selected as samples. The research results indicate that four factors of ecotourist and geotourist tourism products, natural assets, and development of tourism infrastructure and create opportunities of nature-centered tourism boom are the most important factors in increasing the attractiveness of tourist places and geotorrhea. Also, the results showed that the strengthening of regional tourism infrastructure, private sector investment in tourism and the recognition of natural tourism capacities and tourism attractions, and planning for its development, are the most important strategies for development of natural tourism in Khorramabad.
“Synergogy is a method whose principles are based on group participation and comprehensive structural synergy in the learning process. In the meantime, the content of location-based courses (such as geography) is intertwined with spatial data, and its stabilization requires memorization and mental imagery. Experience has shown that learning these subjects in traditional ways has not been effective and has not been able to stabilize the learning content. This research is written with the nature of the applied method and with the aim of investigating the synergistic rhythm of the place-based curriculum of geography. The statistical population was 60 students of the final year of geography at Farhangian University, who collected data using the library and field method (Choo and Bowley evaluation model) and entered it into SPSS software, and analyzed the data with the rhythm analysis model and the structural equation model of path analysis.The results Examining the components of group dynamics, doing work, feedback and the variables of place, time and classroom space arrangement shows that the synergistic rhythm of place-based courses has a linear, continuous, regular and gradual growth, which is important in regular linear practical courses and in sinusoidal theory courses. Is. At the same time, in the structural equation, the effect of time-spatial variables and space arrangement on the synergism of the place is continuous and they are in continuous relationship with the positive direction. It is more desirable to conduct the synergy method of place-based geography lessons with the priority of workshop classes, technology site and smart classes. Holding synergistic classes in the morning (9 to 11) is considered the most suitable time.The direct and indirect effect of the sum of all variables on synergy has relative favorability.
There are various indicators to monitor and management of agricultural water resources in arid and semi-arid countries including Iran, some of which can be extracted directly in situ, and some can be retrieved using remote sensing technology and satellite images. Aim of this study is to propose the most appropriate and efficient indicators of agricultural water resource management for achieving maximum production and maximum water efficiency using remote sensing technology, therefore, Crop Water Stress Index (CWSI) and Surface Energy Balance Algorithm (SEBAL) were used to estimate Evapotranspiration (ET). In the first step, ET rate was calculated using SEBAL algorithm for six Landsat 8 satellite images related to the wheat growth period. Then, zoning of this index was done in the range of zero to one, in four categories of very low, low, medium and high, which respectively indicate the lowest to the highest amount of ET. In next step, CWSI was calculated based on Idso equation, and its results show different changes both in cold season and in warm months. Comparison of ET and CWSI shows a significant relationship between these two indices in warm months, while in cold months, no significant relationship can be seen. These findings along with the established relationship between ET and CWSI can inform water management strategies in arid environments for sustainable crop production.
The country of Iran, with its geopolitical foundations, which is influenced by its geography, has always been the focus of the countries of the world, especially the world powers, throughout history. The use of this capacity and conditions for the economic prosperity of the country depended on the ability of the statesmen and the type and structure of the government systems in formulating foreign policy, and how effective they were in changing the social environment and the way of economic livelihood of the people. In a fundamental and theoretical way, this thesis has analyzed the formulation and presentation of the national strategy of the Islamic Republic of Iran based on its geopolitical characteristics. The results of this research show that the spirit that governs it according to the structure it entails (statehood), is economic regardless of geographical and geopolitical infrastructure, and this field of foreign policy has not only failed to achieve success, but is also passive. And it has become introspective and stopped from being effective and dynamic. While looking at Iran's geopolitical and geographical foundations, we find that its geopolitical position does not have a global effect and is not below the regional level.
Every year, wildfires burn large areas in the Hyrcanian forests, of northern Iran. This study aims to know the fire regime and assess fire risk in protected areas in Guilan province (256,488 hectar). Fire ignitions and frequency/frequency of burned areas from 1992 to 2022 were identified. Then fire behavior modeling was done to simulate burn probability and fire intensity (i.e. conditional flame length) using the FlamMap modeling system based on fire weather information, topography maps, local fuel models, and historical fire data. By combining maps of simulated burn probability and conditional flame length, a fire hazard map was prepared in the protected areas. According to the obtained results, 8% of the number of historical fires in the period occurred in the protected areas, although most of these fires have very small sizes and limited burned areas (including 0.1% of the burned areas in the province). Frequent fires (fire frequency more than 1) cover 60% of the protected areas, and 11% of these areas are highly likely to ignite. The changes in the burn probability and fire intensity reflect the diversity of fire activity in the protected areas, especially in the south-central parts, which catch the highest values of burn probability (more than 1) and conditional flame length (more than 3 meters). Finally, the fire hazard mapping showed that 77.7% and 4.8% of the protected areas are classified as very low and low fire hazards, respectively. On the other hand, 12.4% and 5.2% of these areas were placed in high and very high hazard classes, respectively. The quantitative results of this research provide scientific criteria for identifying high-priority areas in protected areas where management efforts can help reverse the increasing fire risk of protected forests.
Today, the cities of the country are faced with a kind of duality and inequality. As urban inequality has become one of their spatial characteristics. Therefore, the purpose of the present study is to Zoning of spatial inequality neighborhoods of Isfahan metropolis based on economic indicators for better planning for organizing, empowering and enhancing their quality of life. This study is an applied one and its method is descriptive-analytical. The research data were obtained from Statistical Blocks of Iran Statistical Center (2016). The statistical method used to analyze the data, compile the indices and extract the final urban poverty indices with AHP, Topsis and Hotspot. The findings show that the coefficients of influence on the components of the main occupational, occupational, housing and vehicle components respectively are: 0.266, 0.317, 0.223 and 0.184. According to the final index of poverty status in terms of economic indicators, 23 neighborhoods (11.98%) have good quality, 37 neighborhoods (19.27%) have relatively good quality, 52 neighborhoods (27.08%) are in moderate condition, 64 Neighborhoods (33.33%) are in poor condition and finally 16 neighborhoods equivalent to 8.33% of all metropolitan areas of Isfahan are in poor condition. In total, about 42% of all metropolitan areas of Isfahan are in poor condition. The results of the Hotspot model show that neighborhoods with higher than average values in the south and partly in the center of the city and neighborhoods with lower than average values are located in the east and partly west of Isfahan. In fact, the city can be divided into northern and southern parts.
Resiliency is one of the approaches to reducing the vulnerability of communities and strengthening peoplechr('39')s ability to deal with the dangers of natural disasters, especially earthquakes, and has economic, social, institutional, physical, and environmental dimensions. This research is applied in terms of purpose and descriptive-analytical in terms of nature and research method. The researcher-made questionnaire with 102 items was a tool for collecting research data. The sample size was 386 simple based on Cochranchr('39')s formulas and the sampling method was random. Exploratory factor analysis and path analysis were used in the SPSS25 software platform for data analysis and factor modeling. The results indicate that Parsabad city has the lowest scores in terms of social and physical resilience and is in a moderate to good condition; environmental resilience is in a moderate condition, institutional and economic resilience are in a bad situation. Also question factorization, 13 factors for social dimensions, (behavior during the crisis, crisis awareness, crisis preparedness, knowledge, cooperation, trust, assistance, reliance, interaction, accuracy, attitude, first aid, and necessary measures); 3 factors (Damages, Compensation and ability to return) for economic dimensions; 5 factors (performance of public institutions, the performance of semi-public institutions, institutional communication, institutional measures, and institutional context) for institutional resilience; 4 factors (open space, building resistance, public access and Relief access) for physical resilience and 3 factors (environmental, nutritional and soil factors) for environmental resilience. Finally, the modeling of resilience indicators for Parsabad city was presented.
Considering that more than one third of energy consumption is related to residential areas, proper planning and design of neighborhoods according to the climatic conditions of each region can be an effective step towards reducing energy consumption. It aims to optimize energy consumption in the residential blocks of Rushdieh neighborhood in Tabriz. Investigating and understanding the energy consumption situation in Rushdieh neighborhood of Tabriz, its capabilities and bottlenecks in planning is very important, if they are not paid attention to and there are no efficient strategic plans, it will lead to an increase in social, economic and environmental instability. According to its nature, the research method is descriptive-analytical and practical in terms of purpose. It is related to the intended goals of the research, the statistical population of the research is the professors, experts and elites of urban planning, which has been used to examine the indicators and strategies. The method of selecting people was targeted and snowball. Finally, the results showed that the formulation of policies, practical measures to improve the design of main roads and local accesses in the direction of neighborhood air conditioning should be emphasized as the most important strategy. In order to reduce energy consumption, the development of neighborhood design policies and residential blocks with the goals of using wind energy to reduce energy consumption have been placed in the second and third ranks of this prioritization, respectively.
This study investigates the impact of natural and anthropogenic factors on the physicochemical composition of groundwater in the Qazvin aquifer. Based on the optimized Gibbs diagram, the concentration of samples at the end of the freshwater interaction path with silicate units results from geochemical evolution due to the dissolution of these geological units and an increase in the Na/(Na+Ca) ratio. The ion exchange mechanism was assessed using bivariate diagrams of Ca+Mg vs. SO4+HCO3 and Schoeller's chloro-alkaline indices CAI-1 and CAI-2. The results indicate that in 68% of the samples, direct ion exchange, and in 32%, reverse ion exchange control the groundwater chemistry. The changes in Ca vs. SO4 indicate that gypsum dissolution alone is not the source of these ions. These changes could be due to ion mobility and transport during pedogenic processes (sulfur biogeochemical cycle) and anthropogenic factors. The study also examined the role of factors such as agricultural input, atmospheric input, soil nitrogen, sewage input, manure input, chemical fertilizers, and the denitrification process in groundwater pollution using NO3/Na vs. Cl/Na and the NO3/Cl vs. Cl diagrams. The results reveal that agricultural and sewage inputs significantly impact the NO3 and Cl content. Furthermore, in some locations, especially in the southeast of the aquifer, the denitrification process causes a decrease in NO3 concentration. These findings can contribute to effective water resource management in this strategic aquifer by understanding the controlling mechanisms of physicochemical composition and identifying potential groundwater pollution sources.
Air pollution has significant impacts on human health, environmental quality, and the sustainable development of cities. This study aimed to evaluate PM10 using meteorological data from the city of Ahvaz through statistical methods and artificial neural networks. Daily meteorological data and air quality control station data for 4485 days (from 2011 to 2023) were obtained from the National Meteorological Organization and the Khuzestan Department of Environment. Initially, the data were processed and refined, and their normality was assessed using the Kolmogorov-Smirnov test. Given the non-normality of the data, Spearman's and Kendall's Tau-b methods were employed to examine their correlations. The time series and statistical information of the data were obtained using Python programming language. Furthermore, to predict future PM10 levels, the Multilayer Perceptron (MLP) neural network method was utilized. The results of these analyses indicated a significant correlation between meteorological variables and PM10. The Spearman and Kendall Tau-b correlations showed that PM10 had a positive and significant correlation with wind speed (0.094 and 0.061) and temperature (0.284 and 0.187) at a 99% confidence level. Conversely, PM10 exhibited a negative and significant correlation with visibility (-0.408 and -0.300), wind direction (-0.048 and -0.034), precipitation (-0.159 and -0.125), and relative humidity (-0.259 and -0.173) at the 99% confidence level. For future PM10 predictions, the MLP neural network was used. The model was of the Sequential type with an input layer consisting of 6 neurons, three hidden layers of Dense type with 16, 32, and 64 neurons, and an output layer with a linear activation function. The mean squared error (MSE) for the training set was 0.0034, and for the validation data, it was 0.0012. For the test set, the obtained validation accuracy was mse_mlp=0.0048 and val_loss=0.0012. The results indicate a significant direct or inverse correlation between meteorological data and PM10. Additionally, the outcomes of the MLP neural network demonstrated that the network provided satisfactory performance and acceptable predictions for PM10 data in Ahvaz.
Air pollution and adverse effects of pollution caused by the combustion of fossil fuels in urban settlements are among the important environmental issues of metropolises that need to pay attention to ways to reduce air pollution in cities. Global experience has shown that urban form indicators are one of the most important factors affecting air pollution and energy consumption in the city. Therefore, paying attention to the form of the city plays an important role in the long-term perspective of cities for better air quality. The present study is applied in terms of purpose and descriptive-analytical in terms of method. In order to collect the required data and information, library and documentary methods have been used. To analyze the data and answer the research questions, the Moran statistical technique was used in the GIS software environment. The results of this study showed that the air pollution situation in Tabriz in terms of air pollutants, ie sulfur dioxide, nitrogen dioxide, carbon monoxide in the second half of the year is more than the first half of the year, so that among the air monitoring stations The field had the highest number of air pollution. Also, the results of the study of the effect of urban form and land use pattern on air pollution showed that urban form and land use are effective on air pollution.
sudden stratospheric warming has an obvious effect on the Earth's surface climate. In this research, the changes in precipitation during the occurrence of this phenomenon have been investigated. For this purpose, after revealing the warmings that occurred during the studied period (1986-2020), 18 warmings were identified. The 5th decile and 9th decile of precipitation were calculated for the precipitation data of 117 stations. And the size of the difference from the normal rainfall was checked in two ways. First, the precipitation at the time of warming was compared with the long-term average, and then the trend of changes in precipitation at three times before thewarming, at the same time as the warming, and after the warming was finished. Finally, these results were obtained. Warmings according to the month in which they occur; They have a different effect on the amount of precipitation. In the sudden stratospheric warming that occurred in December, January and February, the northwest experiences the most rainfall changes and is above normal, and the probability of rainfall above the 9th decile increases up to 65%. Western and southwestern regions also have higher than average rainfall and the probability of heavy rainfall is high. Precipitation on the shores of the Caspian Sea shows an inverse relationship with sudden stratospheric warming, so in all the investigations of this research, the lack of precipitation at the time of warming in these areas is significant. Southern regions have less than normal rainfall in all sudden stratospheric warming events. The center of Iran has higher than average rainfall in the sudden stratospheric warming months of March. Eastern Iran also has heavy rains compared to normal during the sudden stratospheric warming months of March.
Climate change and global warming are very important issues of the present century. Climate change process, especially temperature and precipitation changes, the most important issue is environmental science. Climate change means a change in the long-term average. Iran is located in the subtropical high pressure zone in arid and semi-arid regions and the Hyrcanian forest is a green area between the Caspian Sea and the Alborz mountain range. At the 43rd UNESCO Summit, the Hyrcanian forests were registered as the second natural heritage of Iran. Beech is one of the most important tree species and the most industrial species of Hyrcanian forests It accounts for about 18 percent of the northern forest volume (from Astara to Gorgan with a life span of about 250 years). The study area is located in the Shanderman basin in western Guilan province. In this research using tree dendroclimatology, Use of vegetative width of beech tree rings, Weather station statistics located in the study area, And Mann-Kendall nonparametric statistical method, To Investigate Climate Change Trend on Growth Time Series and Pearson Statistical Method, in order to evaluate the correlation of diameter growth of beech tree rings with climate variables in the region, an attempt was made. Results of time series of beech tree growth rings over 202 years. Using the nonparametric method Mann- Kendall showed, Changes in growth rings of beech trees have a downward and negative trend, at level 5 %, it was significant. Temperature Minimum, Average, Maximum, and Evaporation during the growing season, there was an upward trend and Annual precipitation there was a downward trend. Using the Pearson method Fit correlation of growth ring diameter with temperature, For the average monthly in February and the average minimum temperature in July, August and September and Negative correlation, for average maximum temperature in February, July, August and September at 95% level, it was significant and precipitation in June, the correlation was 95% positive and significant.
Abstract Due to the increasing importance of tourism, determining the location of Bojnourd is an inevitable necessity. The city of Bojnourd has been affected by this phenomenon by having special capabilities and opportunities for tourism in different economic, social, environmental and physical dimensions. The present research is of applied type and is a descriptive-analytical research method. SPSS, AMOS and Expert choice software were used to analyze the data. The statistical population of the study is the citizens of Bojnourd. The sample size was calculated to be 384 people using the Cochran's formula and was randomly distributed in Bojnourd. Research findings show; With 95% confidence, tourism development has affected the urban development of Bojnourd. Also, among the variables explaining urban development, the growth of cultural services with a factor load of 0.67 had the highest correlation with the hidden variable of urban development. The index of development of infrastructure and construction facilities and services with a factor load of 0.66 is in the second place and the variable of improving the livelihood of residents with a factor load of 0.56 is in the next place. Finally, the index of increase in public services has a factor of 0.52 and has the lowest correlation with its hidden variable. The results of the structural model also show this Tourism has played an important role in the urban development of Bojnourd.
