University of Isfahan Spatial Planning 2228-7485 10 1 2020 03 20 Spatial Analysis of the Impact of Social Capital on Changes in Sustainable Development in Rural Areas (Case Study: Bojnourd County) Spatial Analysis of the Impact of Social Capital on Changes in Sustainable Development in Rural Areas (Case Study: Bojnourd County) 1 28 23981 10.22108/sppl.2019.118588.1410 FA Ali Ghorbani Ph.D. Candidate, Geography and Rural Planning, Faculty of Literature and Humanities, Ferdowsi University of Mashhad, Mashhad, Iran Aliakbar Anabestani Professor, Geography Department, Faculty of Literature and Humanities, Ferdowsi University of Mashhad, Mashhad, Iran Hamid Shayan Professor, Geography Department, Faculty of Literature and Humanities, Ferdowsi University of Mashhad, Mashhad, Iran Journal Article 2019 08 05 Statement of the Problem: In the last two decades, the concept of social capital has been emphasized through its relationship to fundamental social components including awareness, participation, trust, cohesion and social networking for sustainable development of communities, particularly rural communities. Therefore, social capital is essential for achieving sustainable rural development. Purpose: The purpose of this study was to evaluate the impact of social capital in sustainable development of rural settlements and its spatial analysis in Bojnourd County. Methodology: The research method in this study is descriptive-analytical and its purpose is fundamental. Documentary and field methods have been used to collect the data. The sample population is 22 villages with over 20 households in Bojnourd County. From a total of 4849 households in rural areas of the sample, using Cochran formula, the sample size of 298 households were selected by random sampling. To test the conceptual model of research and to investigate the impact of social capital on sustainable development of rural settlements, partial least squares technique and Smart PLS software and Geographically Weighted Regression model were used. Result: The coefficients of T among the main variables of the study were above 2.58, meaning a significant and indirect relationship; thus, social capital has a positive and significant effect on sustainable development of rural settlements. According to total coefficients, social network with coefficient of 0.575 has the highest and social cohesion with coefficient of 0.046 has the least effect on sustainable development of rural settlements. The results of spatial analysis using GWR model showed that social capital impact factor on sustainable rural development in Izman-e-Paieen and Miyanzou villages was highest and in total 36.6% of villages and 41% of rural population of Bojnourd County had an impact factor between 0.871 up to 0.885. Innovation: This study was the first attempt to discuss the spatial analysis of the impact of social capital on sustainable development through Geographically Weighted Regression. Statement of the Problem: In the last two decades, the concept of social capital has been emphasized through its relationship to fundamental social components including awareness, participation, trust, cohesion and social networking for sustainable development of communities, particularly rural communities. Therefore, social capital is essential for achieving sustainable rural development. Purpose: The purpose of this study was to evaluate the impact of social capital in sustainable development of rural settlements and its spatial analysis in Bojnourd County. Methodology: The research method in this study is descriptive-analytical and its purpose is fundamental. Documentary and field methods have been used to collect the data. The sample population is 22 villages with over 20 households in Bojnourd County. From a total of 4849 households in rural areas of the sample, using Cochran formula, the sample size of 298 households were selected by random sampling. To test the conceptual model of research and to investigate the impact of social capital on sustainable development of rural settlements, partial least squares technique and Smart PLS software and Geographically Weighted Regression model were used. Result: The coefficients of T among the main variables of the study were above 2.58, meaning a significant and indirect relationship; thus, social capital has a positive and significant effect on sustainable development of rural settlements. According to total coefficients, social network with coefficient of 0.575 has the highest and social cohesion with coefficient of 0.046 has the least effect on sustainable development of rural settlements. The results of spatial analysis using GWR model showed that social capital impact factor on sustainable rural development in Izman-e-Paieen and Miyanzou villages was highest and in total 36.6% of villages and 41% of rural population of Bojnourd County had an impact factor between 0.871 up to 0.885. Innovation: This study was the first attempt to discuss the spatial analysis of the impact of social capital on sustainable development through Geographically Weighted Regression.

https://sppl.ui.ac.ir/article_23981_3b9762bb96e445a72cc0fd4cabeeb85e.pdf

University of Isfahan Spatial Planning 2228-7485 10 1 2020 03 20 Determining the Seasonality of Monthly Rainfall using the Markham Method in the Ardabil Province Rain Gauge Stations Determining the Seasonality of Monthly Rainfall using the Markham Method in the Ardabil Province Rain Gauge Stations 29 42 24118 10.22108/sppl.2019.111033.1215 FA Fatemeh Daddeh MA Student, Faculty of Agriculture and Natural Resources, University of Mohaghegh, Ardabili, Iran Raoof Mostafazadeh Assistant Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh, Ardabili, Iran Abazar Esmali, Ouri Associate Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh, Ardabili, Iran Ardavan Ghorbani Associate Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh, Ardabili, Iran Journal Article 2018 06 03 The spatial and temporal fluctuations of the climatic element of precipitation and severe changes will lead to changes in atmospheric patterns. Therefore, the study of precipitation trends in different time and space scales is considered as a topic of interest in climatology. The purpose of this study was to calculate the seasonal precipitation index, using the Markham method in 28 rain gauge stations of Ardabil province during the 30-year recorded period. In this regard, daily rainfall data were analyzed and the Markham method was used to calculate the mean time of occurrence and the seasonality index (SI) of the components S, C and p R (average annual rainfall vector). In the next step, the Seasonality Index (SI) obtained from the p R ratio to the total annual rainfall for all rain gauge stations over the study area. According to the results, the lowest amount of seasonality is related to Sanin and Shamshirkhani stations with a value of 0.18. While the highest seasonality value is calculated for the Sarein Station with a value of 0.39. Based on the seasonal pattern of monthly rainfall values, the mean occurrence time of rainfall of 20 rain gauge stations falls into winter season, and the 6 rain gauge stations experience the highest rainfall during spring season and the 2 remaining stations had a rainy autumn season. Distinguishing seasonality pattern of monthly and seasonal rainfall can be used for the prediction of water balance changes, cultivation timing, and flood/drought events in finer time scales. The spatial and temporal fluctuations of the climatic element of precipitation and severe changes will lead to changes in atmospheric patterns. Therefore, the study of precipitation trends in different time and space scales is considered as a topic of interest in climatology. The purpose of this study was to calculate the seasonal precipitation index, using the Markham method in 28 rain gauge stations of Ardabil province during the 30-year recorded period. In this regard, daily rainfall data were analyzed and the Markham method was used to calculate the mean time of occurrence and the seasonality index (SI) of the components S, C and p R (average annual rainfall vector). In the next step, the Seasonality Index (SI) obtained from the p R ratio to the total annual rainfall for all rain gauge stations over the study area. According to the results, the lowest amount of seasonality is related to Sanin and Shamshirkhani stations with a value of 0.18. While the highest seasonality value is calculated for the Sarein Station with a value of 0.39. Based on the seasonal pattern of monthly rainfall values, the mean occurrence time of rainfall of 20 rain gauge stations falls into winter season, and the 6 rain gauge stations experience the highest rainfall during spring season and the 2 remaining stations had a rainy autumn season. Distinguishing seasonality pattern of monthly and seasonal rainfall can be used for the prediction of water balance changes, cultivation timing, and flood/drought events in finer time scales.

https://sppl.ui.ac.ir/article_24118_4bbdc636f6795949c5958424442e70a4.pdf

University of Isfahan Spatial Planning 2228-7485 10 1 2020 03 20 Assessing the Degree of Urban Creativity based on Iranian-Islamic Indices in the Metropolis of Isfahan using the Multi-indicator Decision-making Model of VIKOR Assessing the Degree of Urban Creativity based on Iranian-Islamic Indices in the Metropolis of Isfahan using the Multi-indicator Decision-making Model of VIKOR 43 66 24117 10.22108/sppl.2019.115053.1346 FA Reza Mokhtari Associate Professor of Geography and Urban Planning, Payame Noor University, Tehran, Iran Ahmad Moazzeni Assistant Professor of Sociology, Payame Noor University, Tehran, Iran Behnam Jalilian MA, Geography and Urban Planning, Payame Noor University of Isfahan, Iran Journal Article 2019 01 14 In recent years, extensive efforts have been made to identify creativity factors in cities, so that today's creativity in cities has become the subject of competition. This research was carried out with the aim of explaining, identifying and assessing the indices and components of the Iranian-Islamic creative city in Isfahan. The research method was applied in terms of purpose and was descriptive-analytical in terms of nature. Data collection methods were documentation with using survey method and a questionnaire tool. The obtained data were analyzed using SPSS 23 software. Fifteen regions of Isfahan were clustered using the VIKOR ranking model and ARC GIS software. To assess internal and content validity (CVR and CVI), 11 main and 97 sub-indicators were evaluated by 35 faculty members, managers and urban experts. Subsequently, 13 sub-indicators were excluded due to lack of maximum score. The statistical population of the study was 120 experts from the field of social and urban cultural affairs of the 15 zones of Isfahan. After analyzing the data, it was found that there was a significant difference between the northern and southern regions of Isfahan city in terms of urban creativity. Also, the results showed that area 3 with score 0.9998, area one with score 0.5377, area 6 with a score of 0.2429, and area 5 with a score of 0.1839 earned the highest rank in urban creativity. Based on the results, the urban creativity outcomes of the fifteen regions of Isfahan are consistent with the Iranian-Islamic Indicators of the creative city. In recent years, extensive efforts have been made to identify creativity factors in cities, so that today's creativity in cities has become the subject of competition. This research was carried out with the aim of explaining, identifying and assessing the indices and components of the Iranian-Islamic creative city in Isfahan. The research method was applied in terms of purpose and was descriptive-analytical in terms of nature. Data collection methods were documentation with using survey method and a questionnaire tool. The obtained data were analyzed using SPSS 23 software. Fifteen regions of Isfahan were clustered using the VIKOR ranking model and ARC GIS software. To assess internal and content validity (CVR and CVI), 11 main and 97 sub-indicators were evaluated by 35 faculty members, managers and urban experts. Subsequently, 13 sub-indicators were excluded due to lack of maximum score. The statistical population of the study was 120 experts from the field of social and urban cultural affairs of the 15 zones of Isfahan. After analyzing the data, it was found that there was a significant difference between the northern and southern regions of Isfahan city in terms of urban creativity. Also, the results showed that area 3 with score 0.9998, area one with score 0.5377, area 6 with a score of 0.2429, and area 5 with a score of 0.1839 earned the highest rank in urban creativity. Based on the results, the urban creativity outcomes of the fifteen regions of Isfahan are consistent with the Iranian-Islamic Indicators of the creative city.

https://sppl.ui.ac.ir/article_24117_59414902efd721004a74e79873f610b0.pdf

University of Isfahan Spatial Planning 2228-7485 10 1 2020 03 20 Predicting the Physical Development of Qaen City using Satellite Images Predicting the Physical Development of Qaen City using Satellite Images 67 84 24345 10.22108/sppl.2019.114824.1336 FA Ahmad Asadi Assistant Professor of Geography and Urban Planning, Faculty of Humanities, Bozorgmehr University of Qaenat, Qaen, Iran Ebrahim Akbari Master of Remote Sensing and GIS, Faculty of Geography and Environmental Sciences, Bozorgmehr University of Ghaenat, Qaen, Iran Najma Shafiey Ph.D. Candidate of Geomorphology, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran 0000-0003-0681-2491 Journal Article 2019 01 01 The growth of cities and their impacts on the environment have disastrous consequences. But, with having the knowledge of the areas, investigation, employment, and proper use of new technologies, sustainable development can be achieved. On the other hand, geography and its most important indicators, especially geomorphology as a specialized science, can play an important role in the growth and development of urban centers. The present study examines the development status of the city and the risks that affect its development. In the present study, using the remote sensing and geographic information system of land use changes in the city of Qaen, in order to estimate the increase in the urban area and the reduction of agricultural and horticultural lands in the period from 2000 and 2017, and also its effect on the geomorphological hazards (such as fault, waterway and lithology) has been studied in the region. The area of use was characterized by maximum similarity algorithm, supervised method and Markov chain model at 1404 horizons. The results of this study show that during the years 2000, 2010 and 2017, the area of use of the boundaries built in the city of Qaen has increased and this increase has brought the city closer to the clay formations, faults and main waterways. So that constructed lands (114.84%), gardens and agricultural lands (99.1%), uncultivated lands (99.71%) and rangeland (99.94%) will change. The combination of different data to obtain more accurate and coherent outcomes as well as a vision for identification of favorable areas for urban growth and development in the coming years will be considered as the innovation of this research. The growth of cities and their impacts on the environment have disastrous consequences. But, with having the knowledge of the areas, investigation, employment, and proper use of new technologies, sustainable development can be achieved. On the other hand, geography and its most important indicators, especially geomorphology as a specialized science, can play an important role in the growth and development of urban centers. The present study examines the development status of the city and the risks that affect its development. In the present study, using the remote sensing and geographic information system of land use changes in the city of Qaen, in order to estimate the increase in the urban area and the reduction of agricultural and horticultural lands in the period from 2000 and 2017, and also its effect on the geomorphological hazards (such as fault, waterway and lithology) has been studied in the region. The area of use was characterized by maximum similarity algorithm, supervised method and Markov chain model at 1404 horizons. The results of this study show that during the years 2000, 2010 and 2017, the area of use of the boundaries built in the city of Qaen has increased and this increase has brought the city closer to the clay formations, faults and main waterways. So that constructed lands (114.84%), gardens and agricultural lands (99.1%), uncultivated lands (99.71%) and rangeland (99.94%) will change. The combination of different data to obtain more accurate and coherent outcomes as well as a vision for identification of favorable areas for urban growth and development in the coming years will be considered as the innovation of this research.

https://sppl.ui.ac.ir/article_24345_a9431668cdaa17431ae9cbb92e9ea633.pdf

University of Isfahan Spatial Planning 2228-7485 10 1 2020 03 20 Detecting Impervious Urban Surfaces using the Textural Properties of Radar Imagery Detecting Impervious Urban Surfaces using the Textural Properties of Radar Imagery 85 104 24046 10.22108/sppl.2019.117592.1392 FA Marzieh Sohrabi Mofrad Graduate Master of Remote Sensing and Geographic Information System, Faculty of Humanities, University of Hormozgan, Bandar Abbas, Iran Masoud Bakhtyari Kia Assistant Professor of Geography, Faculty of Humanities, University of Hormozgan, Bandar Abbas, Iran Journal Article 2019 06 11 Urban population growth and the continuous physical development of cities change the natural coverage of the earth and transform it into artificial cover and impervious surfaces. The dramatic increase of these surfaces yields negative consequences in many areas such as increasing surface runoff and flood risk, decreasing groundwater recharge, or intensifying the urban heat island effect. For these reasons, accurate estimation and monitoring of the trend of changes in these ranges is necessary. In this regard, remote sensing data are a cost-effective solution for the preparation and monitoring of impervious surfaces. The purpose of this study was to identify impervious urban surfaces using radar images. In the present study, the textural properties of the Gray Level Co-occurrence Matrix (GLCM) were evaluated using maximum likelihood classification methods, artificial neural network, and support vector machine on Sentinel-1 radar image to determine impervious surfaces of Bandar Abbas city. The overall accuracy of 97.00%, 98.14%, 98.40% and Kappa coefficient of 0.95, 0.97, and 0.97, respectively, for maximum likelihood classification, artificial neural network, and support vector machine, indicated the appropriateness of the utilized methods for detecting impervious urban surfaces. For extracting urban surface information, spectral feature classification algorithms are mostly used. This causes a large amount of useful spatial information such as texture to be ignored in the classification images. Given that SAR images are sensitive to the geometrical properties of urban surfaces, impervious urban surfaces can be accurately detected by using textural properties of radar imagery, which has not been addressed so far. Urban population growth and the continuous physical development of cities change the natural coverage of the earth and transform it into artificial cover and impervious surfaces. The dramatic increase of these surfaces yields negative consequences in many areas such as increasing surface runoff and flood risk, decreasing groundwater recharge, or intensifying the urban heat island effect. For these reasons, accurate estimation and monitoring of the trend of changes in these ranges is necessary. In this regard, remote sensing data are a cost-effective solution for the preparation and monitoring of impervious surfaces. The purpose of this study was to identify impervious urban surfaces using radar images. In the present study, the textural properties of the Gray Level Co-occurrence Matrix (GLCM) were evaluated using maximum likelihood classification methods, artificial neural network, and support vector machine on Sentinel-1 radar image to determine impervious surfaces of Bandar Abbas city. The overall accuracy of 97.00%, 98.14%, 98.40% and Kappa coefficient of 0.95, 0.97, and 0.97, respectively, for maximum likelihood classification, artificial neural network, and support vector machine, indicated the appropriateness of the utilized methods for detecting impervious urban surfaces. For extracting urban surface information, spectral feature classification algorithms are mostly used. This causes a large amount of useful spatial information such as texture to be ignored in the classification images. Given that SAR images are sensitive to the geometrical properties of urban surfaces, impervious urban surfaces can be accurately detected by using textural properties of radar imagery, which has not been addressed so far.

https://sppl.ui.ac.ir/article_24046_4404302e125ca3ce626e607a32f97de0.pdf

University of Isfahan Spatial Planning 2228-7485 10 1 2020 03 20 Saudi Arabia's Balancing Policy with Iran in Yemen Saudi Arabia's Balancing Policy with Iran in Yemen 105 122 24294 10.22108/sppl.2019.119020.1420 FA Morteza Hemmati PhD Student in Department of Humanities and Law, Isfahan (Khorasgan) Branch of Islamic Azad University, Isfahan, Iran Shahrooz Ebrahimi Associate Professor of International Relations, University of Isfahan, Isfahan, Iran Mahnaz Goodarzi Assistant Professor in Department of Humanities and Law, Isfahan (Khorasgan) Branch of Islamic Azad University, Isfahan, Iran Journal Article 2019 09 16 Problem Definition: What are the reasons for Saudi Arabia's conservative foreign policy shift to an aggressive approach after the Arab spring in Yemen? Purpose: Investigating and analyzing the causes of the Saudi military invasion of Yemen from two geopolitical and ideological aspects and its impact on Saudi Arabia's balancing policy with Iran. Methodology: The study was conducted using the descriptive-analytic method. Data collection method was library one using scientific and research papers and online sites. The theoretical framework of this paper was derived from the theory of balance of power, which emphasizes the (relative) equality of power between the two rival blocs, providing a useful theoretical framework for examining the shift in the conservative approach of Saudi foreign policy to the aggressive approach following the Arab spring developments in Yemen. Result: The findings of this article suggest that Ansarullah's full control over Yemen could change the balance of power for Iran's benefit by endangering Saudi security (provoking Shiites in the south and east as well as threatening oil transit through the strategic Bab al-Mandab Strait) and expand its sphere of influence in the Middle East. Saudi Arabia has changed its conservative foreign policy approach to an aggressive foreign policy towards Yemen after changes in Islamic awakening for expanding its influence and maximizing its security on the one hand and to curb the expansion of Iranian influence in the region with the aim of weakening the axis of resistance and balancing strategy on the other. Problem Definition: What are the reasons for Saudi Arabia's conservative foreign policy shift to an aggressive approach after the Arab spring in Yemen? Purpose: Investigating and analyzing the causes of the Saudi military invasion of Yemen from two geopolitical and ideological aspects and its impact on Saudi Arabia's balancing policy with Iran. Methodology: The study was conducted using the descriptive-analytic method. Data collection method was library one using scientific and research papers and online sites. The theoretical framework of this paper was derived from the theory of balance of power, which emphasizes the (relative) equality of power between the two rival blocs, providing a useful theoretical framework for examining the shift in the conservative approach of Saudi foreign policy to the aggressive approach following the Arab spring developments in Yemen. Result: The findings of this article suggest that Ansarullah's full control over Yemen could change the balance of power for Iran's benefit by endangering Saudi security (provoking Shiites in the south and east as well as threatening oil transit through the strategic Bab al-Mandab Strait) and expand its sphere of influence in the Middle East. Saudi Arabia has changed its conservative foreign policy approach to an aggressive foreign policy towards Yemen after changes in Islamic awakening for expanding its influence and maximizing its security on the one hand and to curb the expansion of Iranian influence in the region with the aim of weakening the axis of resistance and balancing strategy on the other.

https://sppl.ui.ac.ir/article_24294_0812d6bc3142716f917bbb0a88d9f38f.pdf