Record link: 
http://hdl.handle.net/20.500.12708/43865
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Title: 
Unfolding Urban Structures: Towards Route Prediction and Automated City Modeling
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Citation: 
Fogliaroni, P., McCutchan, M., Navratil, G., & Giannopoulos, I. (2018). Unfolding Urban Structures: Towards Route Prediction and Automated City Modeling. In S. Winter, A. Griffin, & M. Sester (Eds.), 10th International Conference on Geographic Information  Science (GIScience 2018) (pp. 26:1-26:6). LIPICS. https://doi.org/10.4230/LIPIcs.GIScience.2018.26
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Publisher DOI: 
10.4230/LIPIcs.GIScience.2018.26
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Fogliaroni, Paolo 
McCutchan, Marvin 
Navratil, Gerhard 
Giannopoulos, Ioannis 
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Organisational Unit: 
E120-02 - Forschungsbereich Geoinformation 
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Published in: 
10th International Conference on Geographic Information Science (GIScience 2018) 
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ISBN: 
978-3-95977-083-5
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Volume: 
114
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Date (published): 
2018
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Event name: 
10th International Conference on Geographic Information Science (GIScience 2018) 
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Event date: 
28-Aug-2018 - 31-Aug-2018
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Event place: 
Melbourne, Australia
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Number of Pages: 
6
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Publisher: 
LIPICS, 114
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Publisher: 
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, Dagstuhl
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Peer reviewed: 
Yes
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Keywords: 
intersection types; spatial structure; spatial modeling; graph theory
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Abstract: 
This paper extends previous work concerning intersection classification by including a new set of statistics that enable to describe the structure of a city at a higher level of detail. Namely, we suggest to analyze sequences of intersections of different types. We start with sequences of length two and present a probabilistic model to derive statistics for longer sequences. We validate the results by comparing them with real frequencies. Finally, we discuss how this work can contribute to the generation of virtual cities as well as to spatial configuration search.
de
 
This paper extends previous work concerning intersection classification by including a new set of statistics that enable to describe the structure of a city at a higher level of detail. Namely, we suggest to analyze sequences of intersections of different types. We start with sequences of length two and present a probabilistic model to derive statistics for longer sequences. We validate the results by comparing them with real frequencies. Finally, we discuss how this work can contribute to the generation of virtual cities as well as to spatial configuration search.
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Research Areas: 
außerhalb der gesamtuniversitären Forschungsschwerpunkte: 100%
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Science Branch: 
Geodäsie, Vermessungswesen
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Appears in Collections:
Conference Paper

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