Geography

Geography

An Analysis of the Explanatory Components of Urban Poverty in Esfarayen

Document Type : Research Article

Authors
1 Professor, Department of Geography and Urban Planning, Yazd University, Yazd, Iran.
2 PhD student in Geography and Urban Planning, Yazd University, Yazd, Iran.
Abstract
Introduction
Today, poverty is Considered to be one of the most important issues in society, and its elimination from it is a main goal of economic development in each society. The Esfarayen cites is one of the big cities of North Khorasan, Iran, that was constructed in the not-so-distant past from the joining of 19 small villages. In recent years, this city's faced rapid urban population growth.  By the way,  the inability to provide appropriate facilities and services to citizens leds to the formation of slums in these cities.  Some of the problems that indicate unfavorable conditions in Esfarayen city include, unemployment, false employment, violence, and insecurity which have caused many problems in social, economic, physical, and environmental dimensions. So, in this study, the spatial multidimensional poverty index has been studied for Esfarayen City with the goal of planning for a reduction in class gaps and spatial justice.
 
Methodology
The present study is considered descriptive-analytical research in terms of purpose and research methodology. The used data for this studied are included the library resources data and the comprehensive data of the Statistics Center of Iran in 2020. Also, for the data analysis, the ArcMap software has been used. In the first step, the urban poverty research indicators were identified in terms of the economic, physical, and social dimensions. These indicators are detailed in Table 1. After identifying, the indicators were computed  in EXCEL software and drawn in GIS software.  In the second step, the hot spot analysis method was used in ArcGIS software to analyze poverty based on these dimensions. In the third step, the multidimensional urban poverty index was calculated based on the sum of the economic, physical, and social dimensions. The hots spot methods were used for the investigation of multidimensions urban poverty.  Finally in the last step, by converting the data plot of poverty to the raster, the multidimensions urban poverty were divided into three categories of poor, average, and affluent.
 
Results and Discussion
In an investigation of the results of the current study, the hot spot analysis results showed that the hot spots of this city are located along Shahid Keshavarz Boulevard in the east of Esfarayen, which includes neighborhoods 16, 17, 18, 19, 20. Also, most of the cold spots are located in the west and south part of Esfarayen, especially in the  8 and 15 neighborhoods. The results of Moran's analysis showed that the multidimensional urban poverty index in Esfarayen City has a cluster distribution. This cluster distribution indicates the spatial autocorrelation between the indexes.  A study of the major complication for the multidimensional urban poverty index shows that this indicator was located in the border neighborhood including the 18 and 19 neighborhoods, and has an elliptical distribution in the northeast and southwest directions. Finally, the urban poverty zoning results showed that the largest zone in Esfarayen City is the poor zone. this area includes 395 blocks, 26813 population, 7862 households, and 227/390 Hectares areas. Also, a prosperous area with 128 blocks, 1880 population, 560 households, and 167/362 hectares area is the smallest zone of the city.
 
Conclusion
Generally, the multidimensional poverty analysis results for Esfarayen city show that from the total population of this city, 51% are in average status, 45% are in poor status, and 4% are in prosperous status. The significant difference between the populations of poor and affluent areas and also the significant difference between the distribution of urban poverty index clusters indicates in the existence of a class gap in Esfarayen. This issue requires planning to overcome the existing conditions
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