Urban growth pattern in Europe and the United States

Authors: Sunhui Sim*, University of North Alabama, Stefan Fina, Research Institute for Regional and Urban Development gGmbH, Karsten Rusche, Research Institute for Regional and Urban Development gGmbH, Caroline Baumgart, Research Institute for Regional and Urban Development gGmbH
Topics: Urban Geography, Remote Sensing, Geographic Information Science and Systems
Keywords: urban growth, urban sprawl, indicators, GHS
Session Type: Paper
Day: 4/7/2019
Start / End Time: 3:55 PM / 5:35 PM
Room: Marshall East, Marriott, Mezzanine Level
Presentation File: No File Uploaded

This contribution presents a comparative analysis of urban growth patterns in Europe and US. We use satellite image based products for the years 2000 and 2010 to provide realistic trend indicators for urban growth and structure patterns in selected city regions with more than 500.000 inhabitants. The novelty of our research is that we compute the indicators for several rings around the central city. The rings are composed of drive-time distances, thus acknowledging the need to model functional relationships between city centres and their commuter catchments. This approach will allow us to analyse the pattern and structure indicators for different variations of city size, suburban structure, polycentricity and the urban-rural continuum. The aim is to better differentiate between urban growth indicators in relation to their distance to the city center. This is necessary to monitor inner-city structures separately, which are frequently historically grown and preserved and carefully modernized by city planners with a specific set of policies (heritage, tourism, infill development). Newer city structures at the outskirts, however, are often exposed to a different set of urbanization drivers and related policies like transit-oriented development, residential and industrial zoning provisions, and free market forces of urban sprawl. The ring structure will allow us to clearly identify this distinction through clustering methods for urban density and built-up density gradients from the core to the periphery.

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