عباس رجایی

Understanding the physical condition of the city and analyzing the pattern of physical development to achieve sustainable urban development is vital, because today the bulk of researchers assume that there is a significant relationship between the pattern of physical development of the city and sustainability. Accordingly, the primary goal of this study is to analyze the physical-spatial development pattern of Yasuj using spatial analysis methods such as local spatial autocorrelation (Moran), directional distribution, standard elliptic distribution and hot spots. The research methodology draws on both deductive and inductive methods. The former was employed to explore theoretical foundations and research literature, and the latter was adopted to gain insights into the pattern of physical development of Yasuj by tapping into statistics and information obtained from secondary data. The results of spatial analysis suggest that in population, residential and construction indices, density displays a pattern of cluster distribution and spatial autocorrelation. As such, the Z-Score was 54.58 for population density, 57.48 for residential density and 51.12 for construction density in 2015, exhibiting a significant surge compared to 1996 and 2006. The results of hot spots for 1996-2016 span in Yasuj city show dispersed and low-density physical expansion of the city, which has laid the ground for the spiral and unplanned growth of the city, especially in the northwest area. The highest hot spatial clusters of varying densities in Yasuj were observed in western blocks of the city with 99% significance and the highest cold spatial clusters were recorded in the northwestern blocks. Therefore, controlling and monitoring urban constructions and deterring the destruction of agricultural lands in the west and northwest areas of this city can serve as a key strategy in guiding the physical development of Yasuj.

Housing as a basic human need has characteristics that affect its performance as well as residents' satisfaction. The issue of housing quality is one of the most important and debated among the countries of the world, especially developing countries. The purpose of this study is to examine the background, actions taken, and the process taken by selected countries around the world on the topic of housing quality And It examines the plans, policies, dilemmas and strategies of different economic systems to create a proper residential system. Subsequently, indicators of housing quality in developing and developed countries were analyzed separately. The research shows that in developing countries - overseas metropolitan population growth, development of sustainable buildings, supportive policies, education of suitable housing construction, and supervision of the construction industry and development in developed countries; formulating appropriate laws and key policies, changing culture in conceptualizing housing, creating affordable affordable housing, improving urban reconstruction and renovation projects through Private investment is one of the most important strategies on earth Housing policies in different systems.

Housing is considered as one of the most basic needs of human life as the smallest element of the habitat, and the place of rest and comfort has been a long-standing fate of security and tranquility. Housing has become a very broad and complex concept today, and with the emergence of the concept of sustainable development, the importance of expanding the concept of sustainable housing and its growing aspects have become apparent. Sustainable housing design uses a wide range of active and passive design principles that improve the environmental and social aspects. Nowadays the cities of Iran are involved with the problem of the worn out and historical context of the city, which is incompatible with the new urban life and the characteristics of a modern city; the structural and functional anatomy of these tissues indicates the manifestation of problems such as conflict with the general structure of the city, population density and concentration, and Activities, economic decline, deterioration in physical quality, the reduction of local and residential values, the decline of social qualities, unfavorable environmental conditions, access difficulties and traffic congestion, and degradation of cultural and visual qualities. District 1 Region 9 of Tehran consists of 3 neighborhoods with the names of Professor Moin, Shahid Dastghib ​​and Dr. Hoshiar. Based on the census of 1390, the population is 73141 and 21719 households. The total area of ​​this area is 260.8 hectares, with an area of ​​73/1 hectares of that texture worn. In this research, by studying the theoretical foundations of sustainable urban housing and its dimensions and indicators, in District 1 of Tehran 9, we measured the sustainability of urban housing. The indicators studied in this study are economic sustainability, social sustainability and environmental indicators. The present research is based on the developmental-applied and descriptive-analytical methodology based on library studies and field studies. The results of the survey of economic indicators show that in District 1 per person, 16/29 square meters is the residential area. For every household with rented housing, 1/36 households have civil housing. In general, prices for housing in general are lower than average housing prices in Tehran. The results of social sustainability indicators show that the density of people in the room in district 1 Region 9 of Tehran is 3/11. The household size of the municipality's professor is more than other neighborhoods. The density of the number of residential units is 8876/53. Indicators of environmental sustainability show population density in District ​​1 is 280/44 per hectare. The ratio of the surface of green space to residential areas in District ​​1 is 0/09 square meters. The ratio of the area of ​​green space to the total area of ​​District 1 is 0/04 square meters. Per capita of parks and green spaces in District ​​1 is 1/6 square meters. 93/42% of household wastewater is disposed of with residential wells. All of these surveys show a very poor social and environmental sustainability condition, which is a good condition among economic indicators. Solving the problems of worn out tissues by promoting social capital; providing financial incentives and reducing loan installments for applicants; increasing green spaces to create vitality and expanding social interactions and improving the environmental situation are among the most important recommendations.

Rural development is one of the most important processes that is considered in different countries. Rural development needs to recognize the different important components. Social welfare is one of the important components using which enables us to reduce the problems of villages. By this issue we can reduce many problems in rural areas. This study tries to assess and determine the level of social welfare in rural areas of the Kheir area in the Estahban province. The research method that is used is based on descriptive - analysis and field methods (questionnaires and documents). The sample size is 313 persons that reside in twelve villages. The sample size was selected by the Cochran’s model. In order to analyze data, we also used both statistical methods (descriptive and inferential statistics) and TOPSIS and Morris methods. The results show that social welfare varies between villages in case study. This value is between 0.11 – 0.95. Social welfare in the rural areas is higher than the average (0.596). The results also show that there is a significant relationship between social welfare and two criteria: population and services. Also there is a statistically significant indirect relationship between distance from the center of township and social welfare.

For more than four decades، sociologists، politicians، economists and geographers have used a wide variety of statistical techniques to analyze and measure Quality of Life of individuals and communities. This was with the aim to obtain useful instruments for social، political and economic decision making. Quality of urban life has become an important field within urban studies. The increased level of attention to this topic is due to the increasing importance of Quality of Life studies in monitoring public policies and also due to the role they can play as effective tools in urban management and planning. In addition to development of Quality of Life indicators، geographers seek to identify and understand the geographical patterns of urban Quality of life indicators in relation to the processes that give rise to those patterns. Urban QoL is usually measured by either subjective indicators using surveys of residents’ perceptions، evaluations and satisfaction with urban living or by objective indicators using secondary data and relative weights for objective indicators of the urban environment. This paper relying on the objective approach in study of Quality of life and also using principal component analysis method is developing the Quality of life index in Tehran city. Use of census data، satellite images، quantitative GIS، GIS mapping and statistical analysis are powerful tools to investigate the variability of Quality of Life indicators among 117 municipality divisions of Tehran city. Four sets of data were used for the analysis of urban spatial structure in Tehran city. Census data (year 2006) were used for the analysis of socioeconomic condition. ETM+ satellite images (year 2009)، air pollution layer consisting of carbon monoxide (year 2009)، and urban services dispersion layers (year 2006) were used for the spatial analysis. To measure the vegetation cover، the Normalized Difference Vegetation Index (NDVI) and Landsat 7 ETM+ image dated on summer 2009 were used. The NDVI is a simple numerical indicator that can be used to analyze remote sensing measurements، typically but necessarily from a space platform، and assess whether the target being observed contains live green vegetation or not. Using the Landsat ETM+ 7 satellite image، we therefore calculated the normalized difference vegetation index. Thermal infrared band of ETM+ provides the source to extract surface temperatures. The procedure to extract land surface temperatures involves three steps: (i) converting the digital number of Landsat ETM+ band 6 into spectral radiance; (ii) converting the spectral radiance to at-satellite brightness temperature، which is also called blackbody temperature; and (iii) converting the blackbody temperature to land surface temperature. The average values for the air pollution and specially carbon monoxide were calculated and mapped، using zonal statistic function in GIS. The amounts of air pollution were calculated and analyzed for each area. Accessibilities to six types of urban services were measured for 117 zones of Tehran. These 6 types of urban facilities: educational centers (day care centers، elementary schools، schools for talented students، middle schools، high schools and universities); emergency services (fire stations، emergency centers، and police); health services (hospitals، health and treatment centers); recreation and sport centers (parks، sport clubs، sport grounds); cultural services (libraries، mosques، cinemas، and cultural centers) and subway stations، all analyzed using Arc GIS. Distance was used as criteria for accessibility. In this research، a 500 meter distance was considered as an optimum distance to urban services. These distances were standardized (0 to 1). The value given to a areas reduces with the increase in distance. When the distance reaches 5000 meters، the value given is zero. After calculating the mean value of distances to mentioned urban services، separately and for every zone، the degree of optimum distance of each zone to urban services were measured with weighted linier index. To give weights to these six indicators، Analytical Hierarchical Process was used on the basis of paired comparisons. Principal component analysis was used to extract factors related to socio-economic، environmental and accessibility variables. Factor analysis is a statistical technique used to determine the number of underlying dimensions contained in a set of observed variables. The underlying dimensions are referred to as factors. These factors explain most of the variability among a large number of observed variables. Exploratory spatial data analysis (ESDA) is a subset of exploratory data analysis (EDA) that focuses on the distinguishing characteristics of spatial data-specifically on spatial autocorrelation and spatial heterogeneity. More specifically، ESDA is a collection of techniques to describe and visualize spatial distributions، identify atypical locations or spatial outliers، discover patterns of spatial association، clusters or hot spots، and suggest spatial regimes or other forms of spatial heterogeneity. By using these methods we can identify spatial effects، which can be classified into two general types: spatial autocorrelation and spatial heterogeneity. Extracted components are «housing and skill»، «access to public services»، «environmental quality» and «unemployment». Exploratory Spatial Data Analysis have been used to identify and understand geographical patterns of QoL in Tehran city. The results of Exploratory Spatial Data Analysis indicate the presence of clustering (a positive spatial autocorrelation) and spatial heterogeneity in distributions of Quality of life Index across the districts of Tehran city. Results show that spatial autocorrelation and spatial heterogeneity are detected in the spatial distribution of urban Quality of Life components in Tehran city. Therefore، intra-urban inequalities exist with respect to urban Quality of Life components. The results of this explorative research of spatial data showed that there is a clustering (positive spatial autocorrelation) and unequal distribution of urban Quality of Life components in urban areas of Tehran. The results of the analysis approve the un-equality of socio-economic، environmental and accessibility variables among different areas of the Tehran city. The provided maps show the areas that need intervention and development of public infrastructure. The results of the analysis can guide policy makers and planners to reduce the city’s unequalities. Understanding of these variations can help to develop more realistic models، which are critical for Quality of Life planning.