The Vertical Space Problem

Abstract

Populations in contemporary cities are being measured, analyzed, or represented in less than optimal ways. Conventional methods of measuring density of populations in cities rely on calculating the number of people living within a bounded surface space. This approach fails to account for the multiple floor residential patterns of the contemporary urban landscape and exposes the vertical space problem in population analytics. To create an accurate representation of people in contemporary urban spaces, a move beyond the conventional conception of density is needed. This research aims to find a more appropriate solution to mapping humans in cities by employing a dasymetric method to represent the distribution of people in a city of vertical residential structures. The methodology creates an index to classify the amount of floor space for each person across the extent of the city, a metric called the personal space measure. The personal space measure is juxtaposed with the conventional population density measurements to provide a unique perspective on how population is concentrated across the urban space. The personal space metric demonstrates how improved metrics can be employed to better understand the social and structural landscape of cities. Chicago, with a large population and a high vertical extent, makes an ideal case study to develop a methodology to capture the phenomena of urban living in the 21st century and to explain alternative approaches to accurately and intelligently analyze the contemporary urban space.