Making Invisible City Visible: A Solution for Mapping Hidden Socioeconomic Patterns in Tehran

Abstract

Today, urban areas are among the most complex social landscapes. In order to detect and to resolve urban social problems, urban planners require a deep recognition of this complexity. Synthetic homogeneous neighborhoods offer one approach in moving towards reimagining some of the invisible socioeconomic aspects of urban life. In this paper, we use Openshaw's Automated Zone Design (AZD) methods that utilize an array of factors and algorithms to generate new homogenous socio-spatial units based on both statistical and heuristic procedures. The results are polygons (pseudo neighborhoods) which represent a specific underlying socioeconomic patterning across the city. Using Tehran as our case, the hidden socioeconomic patterns are different from the administrative city divisions and cartographic. The consistency of the new zone design was checked through global and local Moran's I; upon given assumption that for the resulted homogenous polygons (neighborhood), there is no spatial autocorrelation in the new zone design map. The results showed the random distribution for all but one socioeconomic indices in the new zone design map. The result converts heterogeneous urban divisions into new homogenous polygons (neighborhoods) by regrouping basic socioeconomic and spatial units.