فصلنامه برنامه ریزی منطقه ای
پیاپی 52 (زمستان 1402)

Free zones are gateways to world markets by taking advantage of the potentials and opportunities of the domestic economy in international trade. If the goal of the country's development is to develop the areas outside the big cities so that it includes all the rural areas in addition to the cities, one of the most important efforts is to pay attention to the small towns and somehow determine and evaluate their role in the development of the region. is In this research, the role of Aras Free Trade Zone in the development of medium and small cities has been evaluated. The main purpose of the research is to investigate the role of the Aras Free Zone on the development of medium and small cities around. The collection of information was done in two ways: library and field. The statistical population studied are the residents of small and medium towns around the region. The reason for choosing this community is the impact of Aras Free Zone on the lives of these residents. 150 of these people were randomly selected; Also, Cochran's formula was used to estimate the sample size. Cronbach's alpha method was used to measure the reliability of the research. Factor analysis and Spearman's test were used for the analysis. According to the results obtained from the questionnaires and the analytical test, Aras Free Zone is an effective factor in the development of small and medium cities and has caused the economic and social development of these cities. Suggestions for further development of small and medium cities have been presented.

The peripheral region of the subcontinent holds significant geopolitical importance in the foreign policy of the Islamic Republic. Due to the dynamics of the international system and regional developments, the absence of a coherent foreign policy roadmap has resulted in missed opportunities for Iran in this region. This study aims to analyze the strengths and weaknesses of Iran's foreign policy strategy, propose solutions to enhance national power, and suggest strategies for the subcontinent region. Employing a descriptive-analytical approach, data collection involved library research and documentary analysis. The findings reveal that Iran's foreign policy strategy in the subcontinent operates at two levels. Firstly, it encompasses the entire subcontinent, where Iran seeks to enhance its relations across political, economic, social, cultural, and security domains. Simultaneously, Iran endeavors to develop a comprehensive strategy for its foreign policy within the subcontinent. Secondly, Iran tailors its strategy based on the geopolitical interests and concerns of individual subcontinental countries. By adopting a geopolitical approach rooted in Islamic thought, Iran can formulate a coherent foreign policy strategy aligned with its regional and global roles. This approach ensures Iran's active engagement in regional affairs while maintaining its principles and interests.

Tourism competitiveness holds significant importance in economic development. Enhancing competitiveness can lead to increased market share and economic growth in the tourism sector. Numerous studies have analyzed the determinants of tourism destination competitiveness. This research examines how tourism competitiveness in Iranian cities contributes to the country's economic development.The purpose of this research, on the one hand, is the link between the two concepts of competitiveness and the indicators used for measurement, and on the other hand, studies related to tourism competitiveness models and economic growth resulting from the presence of tourists. In terms of the nature of the research, the research method of the upcoming study is qualitative research, and in terms of the goal, it is developmental or applied in terms of methodology, it is analysis and copying tools, And the statistical population is used by experts and professors related to tourism competition and urban planning, and in the end, the analysis of information has been done by means of confirmatory factor analysis. The results obtained from these studies define a model in which the provision of heritage tourism resources with the provision of productive resources and the links between them are the elements that determine the capacity of an economy for production as a result of economic growth. The presented models have emphasized a set of related variables that indicate how they must be measured and evaluated. Even so, an increase in tourism activity contributes positively to economic growth, although how it does so, how much, as well as generalizing this contribution to the development of all countries or periods, are questions that remain.

Income inequality has been one of the debating issues among economists and policy makers from the last few decades. So that, reducing inequality has been one of the main concerns of social reformers and policy makers and it is considered as one of the main problems in many developed and developing countries. Furthermore, housing has a vital role in household’s consumption and asset portfolio and it is important because of playing various roles in the individual’s lives, the economy and society. Therefore, considering the importance of income inequality as one of the concerns of economic policy makers and the importance of housing prices in the economy, this research seeks to study the effect of housing prices on income inequality in urban and rural areas of Iran by using Johansen-Juselius method over the period of first quarter of 2009 to forth quarter of 2019. The results of the study indicate that, housing prices has a significant positive impact on income inequality in urban and rural areas of Iran. So that, the results of the study based on the Gini coefficient index as an indicator of measuring income inequality, indicate that in the urban areas in the long run, one percent increase in the housing prices increases the Gini coefficient by 0.61 percent and in the rural areas in the long run, one percent increase in the housing prices increases the Gini coefficient by 1.37 percent. Also, the results of the study based on the ratio of the cost of ten percent of the richest to the cost of ten percent of the poorest population as an indicator of measuring income inequality, indicate that in the urban areas in the long run, one percent increase in the housing prices increases the ratio of the cost of ten percent of the richest to the cost of ten percent of the poorest population by 6.10 percent and in the rural areas in the long run, one percent increase in the housing prices increases the ratio of the cost of ten percent of the richest to the cost of ten percent of the poorest population by 3.99 percent.

Land surface temperature (LST) is one of the important criteria in applications, and its accurate time and place monitoring is considered essential for environmental studies and management as well as planning. Considering the limitations that exist in meteorological stations to determine this necessary parameter, with the help of different algorithms and sensors containing thermal infrared bands, this parameter can be determined on a wide scale. The accuracy of different algorithms for determining the LST using remote sensing images varies in different regions, using different sensors, and so far, no specific algorithm with high accuracy has been considered for all regions. In this article, the aim is to determine the temperature of the LST by using Single channel, Split window, Planck, Mono Window and RTE algorithms, as well as using the fusion method of LST determination algorithms in a weighted and simple way. In the weighted method, the weight of each method is determined with the help of TOPSIS and SAW multi-criteria decision-making algorithms. At the same time as the Landsat 8 satellite passes through the study area, the LST is taken for 25 points. To evaluate the performance of the proposed method of fusion of the LST determination algorithms, the root mean square error (RMSE) statistical criterion is used to make a comparison between the ground measurements and the values calculated by the algorithms. The results show that the algorithm fusion method, where the coefficient of each algorithm is calculated using the TOPSIS multi-criteria decision-making method, has the highest accuracy (RMSE=0.552oK). By using this combined algorithm, more weight is given to more accurate methods. Among the five algorithms separately, the single-channel algorithm has the best accuracy (RMSE=0.5623oK) and the single-window algorithm has the lowest accuracy (RMSE=1.0046ok).