Verlag der Österreichischen Akademie der Wissenschaften

Abstract:
Automated zoning procedures offer efficient, systematic and objective methodologies for identifying the neighborhood effects on socio-economic statistics. However, the automatic spatial aggregation of census data over manually defined geographic units based on landscape heterogeneity characteristics are barely studied. In this study we utilize high-resolution remote sensing data and census data and apply a multi-level zoning system in order to analyze how a deprivation index differs in the corresponding urbanization environment within the Shannon’s diversity Index. Our study area is the capital city of Ecuador, Quito. The results of the autocorrelation analysis show that, within the Shannon’s Diversity-based multi-level zoning system, areas with a low degree of deprivation in the city center of Quito tend to be larger as the size of the neighborhood increases, and the poverty areas, which are mainly located in the north-east and south-west of Quito, differ significantly between different zoning levels. Our conclusion is that the neighborhood effect influences not only the composition of the spatial pattern and social data, but also their correlation and autocorrelation. Therefore, when analyzing the environment effect of urbanization and its influence on the society development, different levels of zoning systems should be taken into consideration.