جستجوی مقالات مرتبط با کلیدواژه « spatial clustering » در نشریات گروه « علوم انسانی »

Over the past decade, various and heterogeneous types of households have emerged in Iran, resulting from economic, social, and demographic changes. One of the most significant demographic changes in the country is the increase in the frequency of female-headed households. Comparing the establishment of female-headed families in developed and developing countries indicates that social, economic, and demographic factors have different effects on these types of households. Therefore, through a Critical study of all existing research, which has focused on central averages and disregards micro-level changes, it is possible to establish a clear foundation for policies affecting female-headed families. Focusing on female-headed families, as a distinct group, this study examined their similarities and differences in social, economic, and demographic aspects at the county level, and studied their distribution within the theoretical frameworks of second demographic transition and inequalities concerning drive and pressure mechanisms. Based on the current theoretical and experimental literature, this study classifies the existing components in terms of their role in the formation of female-headed families as "driver" and "pressure." Voluntary drivers of the feminization of household headship were analyzed using the second demographic transition theory and the forced pressures of feminization of household headship were investigated in the context of inequality theory.This paper examines the role of driver and pressure mechanisms on the distribution of female-headed households in 429 Iranian counties in 2016 using data from the Statistical Center of Iran and spatial autocorrelation (Moran’s I and Getis index), K-mean clustering and ordinary least squares regression methods. The results of spatial autocorrelation revealed that southeast counties have the highest concentration of female-headed households, while the lowest concentration is observed in northwest counties extending in a line to the center. According to the spatial clustering model and the hierarchical exploratory analysis method on the variables of the percentage of female-headed households, economic, demographic, and social status, the counties are divided into five clusters with the smallest difference from the central average in each cluster and the greatest difference with the next cluster in the best case: cluster 1 includes only three counties and is considered an outlier;  cluster 2 contains the north-west, south, and north-east counties and affected by economic drivers; cluster 3 contains central and northern counties and affected by social and demographic drivers; cluster 4 contains western and southwestern counties and affected by demographic and economic pressures; and cluster 5 contains southeastern and eastern counties and affected by social and economic pressures.Furthermore, the results of ordinary least squares regression revealed that the covariates explain 75% of fluctuations in the frequency of female-headed families. The three economic components of the percentage of jobless families, employment rate of urban women, and economic participation rate had a positive and significant impact (at an error level of less than 0.001) on the development of female-headed households. The socio-demographic components of the percentage of widowed women, early marriage, percentage of divorced women, and the literacy rate of women had a positive and significant effect, and the two components of the percentage of the ever-married population and the percentage of the urban population had a negative and significant effect (at an error level of 0.001) on the formation of female-headed households in counties of Iran.Generally, Social, economic, and demographic changes have a relatively strong impact on the formation of female-headed households via two driving and pressuring mechanisms. As a result, empowering women in the context of the second demographic transition can increase these households in districts (central and north counties) influenced by the driving mechanism.  Continued social, economic, and demographic pressures can increase these households in districted (southeast counties) affected by the pressuring mechanisms. Thus, policymaking based on the role of these mechanisms may help the state to empower and support these families.

Gender is recognized as an important factor in protecting the environment. Nevertheless, gender mainstreaming is still considered a secondary option and waste of funds. This study evaluates the impact of the gender gap on the environmental performance of selected countries in the world using the World Economic Forum data and the clustering k-mean and ordinary least squares regression methods in the framework of demographic metabolism theory during 2014-2020. The results of spatial clustering showed that countries of South and Central Africa and South Asia are in cluster 1 with the lowest values of economic participation and opportunity, health and survival, educational attainment, and political empowerment. Therefore, they must first consider the dimensions of educational attainment and health and survival. Cluster 2 with moderate values ​​in South America, East Asia, Middle East, and Eastern Europe in order to achieve membership in Cluster 3 as well as Cluster 3 itself in Western Europe, North America, and Australia need to further protect the environment and hence, must emphasize the economic participation-opportunity and political empowerment of women. In addition, the results of multivariate ordinary least squares regression showed that the dimensions of the gender gap explain 41% of the fluctuations in environmental performance. Thus, it can be said that the instability of environmental performance in Asian, African and South American countries is due to the gender gap. In addition, the two dimensions of women's educational attainment and political empowerment are the most important components influencing environmental performance.

The main purpose of this study was modeling the suitability of recreational services in order to identify the high-priority areas for the development of recreational activities. To identify the spatial patterns of recreational services, the landscape attractiveness index, visit rate estimation, and access distribution were combined using a set of sub-indices. Moreover, the weight of each index was calculated using CRITIC weighting method and the importance of each index in the formation of recreational services spatial suitability was determined. The results showed that the presentation of highly recreational services is mainly done in the areas with forest ecosystems, protected areas, and aquatic ecosystems such as rivers and wetlands that have diverse landscapes. On the contrary, urban and human-built areas have the least potential for the provision of recreational services. Getis-Ord Gi* statistic was used to model the recreational suitability, identify recreational suitability clusters, and zoning. With its very low suitability, Zone 1 covers 19.9 percent of the area under study. This zone is mainly filled with agricultural lands (54.7%), grasslands (36.1%), and urban lands (6.8%). In contrast, with its very high recreational suitability, Zone 5 covers 16.5 percent of the area under study. The main uses of the lands in this zone are forest lands (55.5%) and aquatic layers including rivers and wetlands (17.2%).  Zone 3, which has an average suitability rate, covers more than half of the area under study. The approach presented in this study helps identify the development priorities in the light of the recreational potentials of the ecosystems existing in an area. Thus, it can be used to improve the spatial planning of recreation and tourism in order to preserve ecosystem services and sustainable use of them.

One of the social and economic security problems and issues that threatens citizens and is somehow related to the State order and security is the crime of theft. Motorcycle theft is the common theft in the recent decades in which thieves commit them with different motives and various uses. To mitigate and counter perpetration of crimes, it is very important to be aware of the crime trends in consecutive years and locations. Therefore; the present research has been prepared with the intention of spatial-locational modeling of the crime of motorcycle theft. This research is of applied typre in terms of objective and of descriptive-analytical type in terms of method. In this research, the statistical sample includes 14 townships in the vicinity of Metropolitan Tehran, East and West Police Commands. This research uses data analysis on the crime of motorcycle thefts within 1398. The spatial analyses used average center and ellipsoid of the criteria deviation, spatial self-correlation and smoothing and interpolation were utilized. The results of the research showed that firstly, the spatial and geographical analyses of the crimes of motorcycle theft, a high number of which, occur in Tehran, indicated this crime well in ellipsoid of the criteria deviation and average center analyses well enough and it proved that the centeredness of the crimes of motorcycle theft is located in the expanse of Tehran West Suburb and its movement direction is east to west. Secondly, crime clustering in three clusters (category) in the area showed that density and mass of the crimes of motorcycle theft are located in lower East Tehran Police Command, high West Tehran Police Command and the Metropolitan Tehran Police Command is located at a very high level.