Spatio-Temporal Building Population Estimation for Highly Urbanized Areas Using GIS

Abstract

Detailed population information is crucial for the micro-scale modeling and analysis of human behavior in urban areas. Since it is not available on the basis of individual persons, it has become necessary to derive data from aggregated census data. A variety of approaches have been published in the past, yet they are not entirely suitable for use in the micro-scale context of highly urbanized areas, due mainly to their broad spatial scale and missing temporal scale. Here we introduce an enhanced approach for the spatio-temporal estimation of building populations in highly urbanized areas. It builds upon other estimation methodologies, but extends them by introducing multiple usage categories and the temporal dimension. This allows for a more realistic representation of human activities in highly urbanized areas and the fact that populations change over time as a result of these activities. The model makes use of a variety of micro-scale data sets to operationalize the activities and their spatio-temporal representations. The outcome of the model provides estimated population figures for all buildings at each time step and thereby reveals spatio-temporal behavior patterns. It can be used in a variety of applications concerning the implications of human behavior in urban areas.