Zoning and spatial analysis of poverty in urban areas (Case Study: Sabzevar City-Iran)

Abstract

The present descriptive-analytical study employs a survey research method, documentary technique, and applied-developmental research design to zone the 18 neighborhoods of Sabzevar City in terms of urban poverty indicators. Data collection was done through a questionnaire distributed among a sample with the size of 384 participants selected from for citizens of 18 neighborhoods of Sabzevar City. A total of 17 urban poverty indicators were surveyed in the form of three sociocultural, economic, and access to urban services indicators. For data analysis, the analytic network process (ANP), Grey Relational Analysis (GRA), and spatial statistics tests were used. The results of the integration of the three economic, sociocultural, and access to urban services indicators depict that the highest urban poverty is in neighborhoods 17 and 18, 6, 14, 15, 13, 12, 11, and 9 respectively. All these neighborhoods are among the marginal neighborhoods of the city. The lowest urban poverty levels are in neighborhoods 1, 2, 3, 4, 5 and partly in neighborhoods 13, 14 and 16, which are part of the city's central neighborhoods, mostly including government employees, the salaried, and those with high-paying jobs. Comparing different types of urban textures via the Integrated Zoning Map of Poverty in Sabzevar City shows that urban poverty zones correspond to the areas of unofficial settlements and extension villages, and the economic poverty in the southern regions of the city is higher than other urban areas. According to the principles of Grey Relational Analysis (GRA), neighborhoods 1 and 2, which includes Southern Kashifi St., Northern Asrar St., and Imam Khomeini Blvd., is considered to be at a higher level than other areas in terms of poor urban poverty. The results of spatial statistics tests (spatial autocorrelation test and G-test) indicate the correlation and clustering of the data model or urban poverty indicators of the study area. Keywords: Urban poverty, Spatial structure analysis, ANP model, Grey relational analysis (GRA), Spatial statistics, Sabzevar city