Spatial Identification and Analysis of Urban Poverty Spaces Using Space Statistics in GIS Environment Case Study: Ardebil City

Poverty spectrums were generated non detachable urban regions and because of poverty phenomenon negative consequences and It’s development, mentioned cases were paid attention by policy makers and planners. The main subject in prevention poverty phenomenon development is accurate recognition of poverty spectrums and spatial consolidation in cities. Poverty position and It’s development in Iran cities, this case has different patterns. Based on poverty spatial dispersion investigation importance in urban societies and by regarding mentioned phenomenon studying; proper decision making And planning provide to poverty problems reducing in urban sectors for managers and administrators. Current research was implemented with the aim of poverty spatial dispersion analysis, poverty blocks recognition and also poverty clustering in Ardebil city urban blocks by using 31 social, Economic and physical indices. According to theses features; spatial statistical models, hot spots analysis, spatial auto-correlation were used in Arc/GIS software. Based on research results, Ardebil urban blocks are located in different classes by regarding investigated indices. According to spatial auto-correlation model (Moranas), poverty dispersion in Ardebil city follow by clustering model and mentioned kind of dispersion cause to creating spatial dichotomy in Ardebil city.