LIPIcs.GIScience.2023.36.pdf
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Characterizing Urban Expansion Processes Using Dynamic Spatial Models – a European Application (Short Paper)
Authors
Alex Hagen-Zanker 
,
Jingyan Yu ,
Naratip Santitissadeekorn ,
Susan Hughes
-
Part of:
Volume:
12th International Conference on Geographic Information Science (GIScience 2023)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Conference on Geographic Information Science (GIScience) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2023-09-07
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Document Identifiers
Author Details
- School of Sustainability, Civil and Environmental Engineering, University of Surrey, UK
- Institute of Geography and Sustainability (IGD), Faculty of Geosciences and Environment, University of Lausanne, Switzerland
Cite As Get BibTex
Alex Hagen-Zanker, Jingyan Yu, Naratip Santitissadeekorn, and Susan Hughes. Characterizing Urban Expansion Processes Using Dynamic Spatial Models – a European Application (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 36:1-36:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.36
Abstract
Characterisation of the urban expansion processes using time series of binary urban/non-urban land cover data is complex due to the need to account for the initial configuration and the rate of urban expansion over the analysed period. Failure to account for these factors makes the interpretation of landscape metrics for compactness, fragmentation, or clumpiness problematic and the comparison between geographical areas and time periods contentious. This paper presents an approach for characterisation using spatio-dynamic modelling which is data-centred using a process based model, Bayesian optimization, cluster identification, and maximum likelihood classification. An application of the approach across 652 functional urban areas in Europe (1975-2014) demonstrates the consistency of the approach and its ability to identify spatial and temporal trends in urban expansion processes.
Subject Classification
ACM Subject Classification
- Applied computing → Environmental sciences
Keywords
- Urban expansion
- morphology
- spatio-temporal dynamics
- simulation
- compactness
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References
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