Schmitt, Andreas and Uth, Philipp and Standfuß, Ines and Heider, Bastian and Siedentop, Stefan and Taubenböck, Hannes (2023) Quantitative assessment and comparison of urban patterns in Germany and the United States. Computers, Environment and Urban Systems, 100, pp. 1-18. Elsevier. doi: 10.1016/j.compenvurbsys.2022.101920. ISSN 0198-9715.
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Official URL: https://www.sciencedirect.com/science/article/abs/pii/S0198971522001648
Abstract
In this paper, we present methods to assess the homogeneity of the settlement landscape and to identify settlement clusters in terms of location and size. Due to various input data, methodologies, and spatial concepts, there are only a few international comparative research studies with quantitative, spatial approaches to date. Existing studies are mostly qualitative and empirically hardly replicable. Here, we introduce two novel methodological approaches to describe urban land patterns in a numerically stable, consistent and globally comparable manner. The first method evaluates the multi-scale homogeneity of the settlements and the respective density distributions in a purely non-parametric approach. The second method transfers the settlement patterns into a Gaussian Mixture Model via hierarchical multi-scale clustering in order to describe each cluster by the parameters of a 2D Gaussian distribution. In order to proof the robustness of both approaches, two different reference units are considered for the interpretation of the results: OECD functional urban areas and standardized subsets of 200 km × 200 km around the same central cities. We show that German urban areas are characterized by a higher heterogeneity within a smaller neighbourhood with an almost symmetric density distribution in comparison to urban areas in the U.S. Furthermore, German urban areas possess an increasing homogeneity with increasing size, i.e., the larger the urban agglomeration, the more uniform it appears. It is the contrary in the U.S. These findings are substantiated by the analysis of individual city centres. In Germany, many clusters of similar size define the urban region, whereas in the U.S. one large dominating cluster exceeds most neighbouring settlements significantly. The study is performed on the Global Urban Footprint Density, which assigns a density value to each urban pixel of about 30 m by 30 m. In this way, the approach is a blueprint to be extended to urban patterns of any spatial unit worldwide.
Item URL in elib: | https://elib.dlr.de/196447/ | ||||||||||||||||||||||||||||
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Document Type: | Article | ||||||||||||||||||||||||||||
Title: | Quantitative assessment and comparison of urban patterns in Germany and the United States | ||||||||||||||||||||||||||||
Authors: |
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Date: | March 2023 | ||||||||||||||||||||||||||||
Journal or Publication Title: | Computers, Environment and Urban Systems | ||||||||||||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||||||||||||
Open Access: | No | ||||||||||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||||||||||||||
In ISI Web of Science: | Yes | ||||||||||||||||||||||||||||
Volume: | 100 | ||||||||||||||||||||||||||||
DOI: | 10.1016/j.compenvurbsys.2022.101920 | ||||||||||||||||||||||||||||
Page Range: | pp. 1-18 | ||||||||||||||||||||||||||||
Publisher: | Elsevier | ||||||||||||||||||||||||||||
ISSN: | 0198-9715 | ||||||||||||||||||||||||||||
Status: | Published | ||||||||||||||||||||||||||||
Keywords: | Polycentricity, | ||||||||||||||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||||||
HGF - Program: | Space | ||||||||||||||||||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||||||||||
DLR - Research theme (Project): | R - Geoscientific remote sensing and GIS methods | ||||||||||||||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||||||||||||||
Institutes and Institutions: | German Remote Sensing Data Center | ||||||||||||||||||||||||||||
Deposited By: | Standfuß, Ines | ||||||||||||||||||||||||||||
Deposited On: | 18 Sep 2023 09:30 | ||||||||||||||||||||||||||||
Last Modified: | 19 Oct 2023 09:12 |
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