spatial distribution

Today, educational spaces are one of the most important uses in cities and are of considerable importance compared to other uses of urban services. Allocation of space to this use is one of the important issues that are considered in urban planning. The metropolis of Tabriz is among the cities in which the spatial distribution of urban services, including educational services, has not been done properly and adequately. In order to solve the problems caused by this issue and also increase the efficiency of these spaces, it seems necessary to pay attention to proper organization and distribution. Accordingly, the present study uses spatial statistics models, hot spot analysis and spatial autocorrelation in Arc / GIS software to investigate the spatial distribution of educational applications in the city of Tabriz. The required data has also been collected by the library method and by referring to the relevant sources and organizations. The results show that there is inequality in the general educational situation in the blocks of Tabriz; Zones 1 and 2 of Zone 2 and Zone 5 of Zone 4, and Zone 1 of Zone 8, Zone 1 of Zone 3 and Zone 3 of Zone 10 have the most weight and Zones 4 and 6 of Zone 5, Zone 2 of Zone 9 and finally Area 1 of Area 6 has the lowest weight of educational uses. In such a way that these areas are at a lower level in terms of stability. Also, according to Moran index, the spatial distribution of educational uses in Tabriz metropolis is clustered. Based on this index, the existing inequality in the distribution of the intended user is quite obvious.Adequate access to public service facilities can be considered as an important indicator for improving the quality of life, which is one of the foundations of justice policies. This helps to meet the basic needs of urban residents, as it has a profound effect on the participation of urban residents in specific physical activities. As a result, poor spatial access to urban facilities can worsen the quality of life for residents of affected neighborhoods. Therefore, to achieve a sustainable distribution system of urban facilities, ensure adequate and easy access of urban residents to these facilities, and improve the quality of life of affected residents, its study is important for urban planners in recent decades, Tabriz metropolis due to development The growing physical and demographic population is witnessing the imbalance of the distribution system of public land uses, including educational land, and the balance of spatial distribution of land uses and education centers in this metropolis have been disturbed, causing spatial inequality in access to facilities. Therefore, the purpose of this study is to analyze the spatial distribution of education services using spatial statistics in the GIS environment in the metropolitan areas of Tabriz and to identify the inequalities in the availability of educational services in the metropolitan areas of the city, because attention to equitable distribution These services will increase social welfare, the spatial balance of the population, maintain the safety of citizens and reduce social tensions. In line with the above objectives, the present study seeks to answer this question: Spatial pattern of service distribution and educational uses What is it like in the blocks of Tabriz metropolis?

     Due to the nature of the subject and objectives of the research, the type of applied research and research method is based on the descriptive-analytical method. The required information has been obtained by the documentary method and based on the latest comprehensive plan of Tabriz metropolis (2011). The statistical population of the study includes ten areas of Tabriz metropolis. To study and identify the distribution of educational uses and weights of this use in different areas of Tabriz and also its distribution pattern from spatial statistics models, spot analysis Hot Spot Analysis and Spatial Autocorrelation (Morans I) are used in GIS software.

      Hot spots analysis has been used in different areas of Tabriz in order to investigate the spatial distribution of educational uses. This statistical analysis calculates Gettys-Ardji statistics for all features present in the data. Also, according to the calculated Z score, it can be shown in which blocks the data are clustered with high or low values. As explained in the research method, the larger the Z-score, the higher the values ​​are highly clustered and form a hot spot. In the case of statistically negative and significant Z, the smaller the Z-score, the more intense the clustering of low values ​​and the indication of cold spots. The results of this analysis in two types of numerical and graphic outputs show that the features are randomly, scattered or clustered in space. If the value of the Moran index is close to a positive number (+1), the data have a spatial autocorrelation and their distribution pattern is clustered, and if the Moran value is close to a negative number (1-), the data view is broken and their distribution pattern is scattered. In the case of this tool, the null hypothesis is that there is no spatial clustering between attribute values ​​associated with geographic features. Moran index calculated for 1390 is equal to 0.127204. This value is less than one and on the other hand the value of P-value is equal to zero, it can be concluded that the desired indicators have spatial autocorrelation and because the value of Moran is positive and close to one, so the spatial distribution of educational uses in Tabriz to the form is clustered and concentrated, and this factor shows that spatial justice has not been observed in the distribution of the intended uses. 

        Therefore, in this study, using spatial statistics models, hot spot analysis and spatial autocorrelation in Arc GIS software, the spatial distribution of educational applications in the city of Tabriz has been studied. The results show that there is inequality in the blocks of Tabriz in terms of the general educational situation. Thus, the blocks with high weight for educational use and high concentration of hot spots are in the desired condition, which includes areas 1 and 2 of area 2 and area 5 of area 4, area 1 of area 8, area 1 of area 3 and area 3 are from area 10. Also, blocks with low training weight and low concentration of hot spots, which include areas 4 and 6 of area 5, area 2 of area 9, and finally area 1 of area 6, which are at a low level in terms of urban sustainability. There are more. Also, the application of general G coefficient showed that the spatial pattern of concentration of educational centers in Tabriz is a random pattern towards high concentration (hot spot). In fact, the areas of Tabriz with a large number of educational centers, are concentrated close to each other and have formed hot clusters. According to Moran's index, the spatial distribution of educational uses in the city of Tabriz is clustered and centralized, and this factor showed that spatial justice was not observed in the distribution of educational uses.

The spatial distribution of the transmittancy of different types of urban centers at different scales is one of the main and strategic concerns of experts, managers and spatial political logisticians. Meanwhile, the production of urban safe space based on the spatial organization of the centers involved in urban security, under the effect of spatial factor of activism, and the analysis of the spatial distribution of sensitive centers also requires the identification of factors affecting the spatial distribution of sensitive metropolitan centers in Tehran with emphasis on passive defense. The present study attempted to identify these factors using qualitative and quantitative methods. This study is a descriptive-analytical type that uses a meta-synthesis method for identifying the first factors affecting the spatial distribution of sensitive metropolitan centers of Tehran with emphasis on passive defense and also employs quantitative methods to investigate and explore factors and verify the designed model. The statistical population of this study consisted of 140 elites, specialists and experts in the field of defense, political geography and urban planning. Statistical techniques were factor analysis, exploratory and confirmatory and SPSS and Lisrel programs were used in data processing. The results showed that 54 items were classified into eight main dimensions (1. economic factors, 2. socio- demographic factors, 3. privacy factors, 4. access to services and infrastructures, 5. nature-environment considerations, 6. factors related to military geography, 7. physical factors and 8. Political-administrative factors) with a coefficient of variance of 17, 14, 12, 9, 6, 7, 5 and 5 percent, respectively, explain 86/22 percent of the total variance. Confirmatory factor analysis also showed that all pathways were significant with 95% probability and the effect of exogenous latent variables on endogenous latent variables (octagonal dimensions) was significant. The chi-square statistic also showed the fitting of the designed model.

The main objective of development is to eradicate poverty in each society as well as make a plan for its eradication. Realization of this major issue requires understanding the status quo and choosing poverty probability index. In this connection, the present study aims to measure the spatial distribution of poverty in different provinces of our country in order to provide more realistic planning for the eradication of poverty. A descriptive-analytical research method (with the practical aim) has been used. Since the poverty is a multidimensional phenomenon, 18 economic, social, cultural and physical indicators have been used to analyze the poverty in this paper. Analytic Network Process (ANP) has been used to express the relative importance of each index as well as PROMETHEE method and GAIA Data Processing have been used to analyze the data. Results of the research show that Zanjan, Yazd, East Azarbaijan, Mazandaran and South Khorasan Provinces are the richest but Kerman, Khuzestan, Kermanshah, Lorestan, Sistan and Baluchestan, Kohkiluyeh and Boyer Ahmad Provinces are known as the poorest provinces of the country. The spatial distribution of poverty in Iran’s territorial zone implies that most of the poor provinces are located in both southeastern and western regions of our country.

With an increase in the life expectancy index, the aging population in Iran and the world has grown and taken into consideration as an effective factor on socio- economic system of societies. The present research provides an overview the status of aging in the Iranian population as well as it tries to analyze this indicator from both geographic and spatial distribution perspectives. According to the studies, the most important indicators to assess the status of aging in a biological environment are such as old age indicator, old age ratio, aging ratio, youth ratio, the burden of support, parental support ratio (emotional support), potential support ratio (spiritual support). The research is carried out through secondary analysis data of Iranian Statistical Center as well as using the Matlab and Execl-Macros programming. The results showed that Iranian population has been going through youthfulness increasingly and entering elderly and aging periods. For example in our central regions such as Tehran, Isfahan and Arak, we face to more serious challenges than marginal areas including Sistan and Baluchestan Province. The upward trend in aging index of Iranian population indicates that the aging crisis in the Iranian population is being far away from expected. Thus, the ascending/increasing trend should be taken into consideration as the biggest challenge facing the development planning system as well as its impacts on all aspects of this process.

New theories describe the Creative Class as the driving force behind creativity that consequently results in economic growth. This study aims to explore this concept in Iranian provinces based on the theoretical literature relating to the Creative Class and analyze the special patterns governing where they choose to live using spatial analysis methods. To this end, spatial autocorrelation indicators in a Geographic Information System (GIS Software) was used. The findings of the article suggest that there is an uneven distribution of the Creative Class in Iran. Tehran, due to its role as the country's capital and in light of the state's centralized political system as well as a quasi-capitalist and rentier economy, has become a place that attracts and accumulates members of the Iranian Creative Class.