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Measuring Urban Sprawl Based on Massive Street Nodes and the Novel Concept of Natural Cities
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
University of Gävle.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper, we develop a novel approach to measuring urban sprawl based on street nodes and naturallydefined urban boundaries, both extracted from massive volunteered geographic informationOpenStreetMap databases through some data-intensive computing processes. The street nodes are definedas street intersections and ends, while the naturally defined urban boundaries constitute what we callnatural cities. We find that the street nodes are significantly correlated with population of cities. Based onthis finding, we set street nodes as a proxy of population to measure urban sprawl. We further find thatstreet nodes bear a significant linear relationship with city areal extents. In the plot with the x axisrepresenting city areal extents, and the y axis street nodes, sprawling cities are located below the regressionline. We verified the approach using urban areas and population from the US census, and then applied theapproach to three European countries: France, Germany, and the United Kingdom for the categorization ofnatural cities into three classes: sprawling, compact, and normal. This categorization sets a uniformstandard for cross comparing sprawling levels across an entire country.

Keyword [en]
Street networks, openstreetmap, volunteered geographic information, GIS
National Category
Geosciences, Multidisciplinary
URN: urn:nbn:se:kth:diva-101658OAI: diva2:548439

QC 20121005

Available from: 2012-10-05 Created: 2012-08-30 Last updated: 2012-11-13Bibliographically approved
In thesis
1. Geospatial Knowledge Discovery using Volunteered Geographic Information: a Complex System Perspective
Open this publication in new window or tab >>Geospatial Knowledge Discovery using Volunteered Geographic Information: a Complex System Perspective
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The continuous progression of urbanization has resulted in an increasing number of people living in cities or towns. In parallel, advancements in technologies, such as the Internet, telecommunications, and transportation, have allowed for better connectivity among people. This has engendered drastic changes in urban systems during the recent decades. From a social geographic perspective, the changes in urban systems are primarily characterized by intensive contacts among people and their interactions with the surrounding urban environment, which further leads to subsequent challenging problems such as traffic jams, environmental pollution, urban sprawl, etc. These problems have been reported to be heterogeneous and non-deterministic. Hence, to cope with them, massive amounts of geographic data are required to create new knowledge on urban systems.

Due to the thriving of Volunteer Geographic Information (VGI) in recent years, this thesis presents knowledge on urban systems based on extensive VGI datasets from three sources: highway dataset from the OpenStreetMap (OSM) project, photo location dataset from the Flickr website, and GPS tracking datasets from volunteers, taxicabs, and air flights. The knowledge primarily relates to two issues of urban systems: the urban space and the corresponding human dynamics. In accordance, on one hand, urban space acts as a carrier for associated geographic activities and knowledge of it benefits our understanding of current social and economic problems in urban systems. On the other hand, human dynamics reflect human behavior in urban space, which leads to complex mobility or activity patterns. Its investigation allows a derivation of the underlying driving force that is very instructive to urban planning, traffic management, and infectious disease control. Therefore, to fully understand the two issues, this thesis conducts a thorough investigation from multiple aspects.

The first issue is investigated from four aspects. First, at the city level, the controversial topic of city size regularity is investigated in terms of natural cities, and the conclusion is that Zipf’s law holds stably for all US cities. Second, at the sub-city level, the size distribution of spatial units within different cities in terms of the clusters formed by street nodes, photo locations, and taxi static points are explored, and the result shows a remarkable scaling property of these spatial units. Third, enlightened by the scaling property of the urban space at the city or sub-city level, this thesis devises a novel tool that can demarcate the cities into three categories: compact cities, normal cities, and sprawling cities. The tool is then applied to cities in both the US and three European countries. In the last, another representation of urban space is taken into account, namely the transportation network. The findings report that the US airport network displays the properties of scale-free, small-world, and disassortative mixing and that the individual natural airports show heterogeneous patterns that are probably subject to geographic constraints and socioeconomic factors.

The second issue is examined from four perspectives. First, at the city level, the movement flow contributed by agents using two types of behavior is investigated through an agent-based simulation, and the result conjectures that the human mobility behavior is mainly shaped by the underlying street network. Second, at the country level, this thesis reports that the human travel length by air can be approximated well by an exponential distribution, and subsequent simulations indicate that human mobility behavior is largely constrained by the underlying airport network. Third, at the regional level, the length that humans travel by car is demonstrated to agree well with a power law with exponential cutoff distribution, and subsequent simulation further reproduces this levy flight characteristic. Based on the simulation, human mobility behavior is again revealed to be primarily shaped by the underlying hierarchical spatial structure. Finally, taxicab static points are adopted to explore human activity patterns, which can be characterized as the regularities in space and time, the heterogeneity and predictability in space.

From a complex system perspective, this thesis presents the knowledge discovered in urban systems using massive volumes of geographic data. Together with new knowledge from empirical findings, the development of methods, and the design of theoretic models, this thesis also shares the research community with geographic data generated from extensive VGI datasets and the corresponding source codes. Moreover, this study is aligned with a paradigm shift in that it analyzes large-size datasets using high processing power as opposed to analyzing small-size datasets with low processing power.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xii, 96 p.
knowledge discovery, urban systems, complex system, VGI, OSM, GPS tracking dataset, scaling, heavy-tailed distribution detection, urban sprawl, Zipf’s law, human activity/mobility patterns, agent-based modeling, complex network.
National Category
Geosciences, Multidisciplinary
urn:nbn:se:kth:diva-104783 (URN)978-91-7501-531-6 (ISBN)
Public defence
2012-12-03, Q2, Osquldas väg 10 NB, KTH, Stockholm, 13:30 (English)

QC 20121113

Available from: 2012-11-13 Created: 2012-11-12 Last updated: 2012-11-13Bibliographically approved

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