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Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata

Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata
Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata
The urban morphology is a complex system characterised by self-organisation where interactions of multiple agents produce emerging patterns on the urban form. Additional complexities in port cities arise from the port-urban relationship which could either benefit or cause tensions for each other. Most urban cellular automata (CA) models simulate land-use evolution through transition rules with consideration of multiple factors representing the local interactions. Calibration of such models could be seen as a process to measure the effect of each factor. Due to the complexity of the calibration process of urban land use and transport interaction (LUTI) models based on CA, manual methods are often preferred. This, however, limits the insights on urban interactions to a few explored settlements and in turn prevents applications for planning in other port-urban contexts. This paper, therefore, seeks to address three main points. First, the paper demonstrates an improved methods for the calibration of LUTI models based on CA. Second, using the aforementioned method, the paper contributes to a better understanding of the dynamics between port and urban system by quantifying generalizable interactions between urban agents from a wide range of port-urban settlements. Finally, this paper illustrates how the use of these interactions in a simulation model can allow long-term impact predictions of planning interventions.

These were done by formulating an urban CA-LUTI model in a structure akin to a neural network model to enable automatic calibration using an application of the gradient-descent algorithm. The model was then used to quantify the dynamics between geographic, land-use, and transport factors in 46 port-based and 10 non-port settlements across Great Britain, thus enabling cross-sectional analysis. Some interactions were found to be generalizable across all settlements, such as the effect of proximity to port on manufacturing activities. Meanwhile, other interactions were observed to vary between settlements. In order to examine the nature of these variations, cluster analysis of the study areas was conducted on the basis of the calibrated interactions. This produced two main groups, one of which was populated by non-port settlements and relatively larger port settlements and the second consisted of smaller port settlements. In the first group, the attractions of ports to other urban land-use activities were either small or negative, while these effects were more positive in settlements in the second group. Overall, the findings of the research are consistent with existing evidence in the port-cities literature but go further in quantifying the interaction between urban agents within port-urban systems of various sizes and types. These quantified interactions will enable planners to better predict the longer-term consequences of their interventions.
Nugraha, Tafta
df33fa16-daeb-4d68-bd65-c26cda240a5b
Nugraha, Tafta
df33fa16-daeb-4d68-bd65-c26cda240a5b

Nugraha, Tafta (2020) Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata. 52nd Annual Conference of the Universities' Transport Study Group, ,. 06 Jul 2020. 12 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

The urban morphology is a complex system characterised by self-organisation where interactions of multiple agents produce emerging patterns on the urban form. Additional complexities in port cities arise from the port-urban relationship which could either benefit or cause tensions for each other. Most urban cellular automata (CA) models simulate land-use evolution through transition rules with consideration of multiple factors representing the local interactions. Calibration of such models could be seen as a process to measure the effect of each factor. Due to the complexity of the calibration process of urban land use and transport interaction (LUTI) models based on CA, manual methods are often preferred. This, however, limits the insights on urban interactions to a few explored settlements and in turn prevents applications for planning in other port-urban contexts. This paper, therefore, seeks to address three main points. First, the paper demonstrates an improved methods for the calibration of LUTI models based on CA. Second, using the aforementioned method, the paper contributes to a better understanding of the dynamics between port and urban system by quantifying generalizable interactions between urban agents from a wide range of port-urban settlements. Finally, this paper illustrates how the use of these interactions in a simulation model can allow long-term impact predictions of planning interventions.

These were done by formulating an urban CA-LUTI model in a structure akin to a neural network model to enable automatic calibration using an application of the gradient-descent algorithm. The model was then used to quantify the dynamics between geographic, land-use, and transport factors in 46 port-based and 10 non-port settlements across Great Britain, thus enabling cross-sectional analysis. Some interactions were found to be generalizable across all settlements, such as the effect of proximity to port on manufacturing activities. Meanwhile, other interactions were observed to vary between settlements. In order to examine the nature of these variations, cluster analysis of the study areas was conducted on the basis of the calibrated interactions. This produced two main groups, one of which was populated by non-port settlements and relatively larger port settlements and the second consisted of smaller port settlements. In the first group, the attractions of ports to other urban land-use activities were either small or negative, while these effects were more positive in settlements in the second group. Overall, the findings of the research are consistent with existing evidence in the port-cities literature but go further in quantifying the interaction between urban agents within port-urban systems of various sizes and types. These quantified interactions will enable planners to better predict the longer-term consequences of their interventions.

Text
Urban Dynamics in Port Cities - AT Nugraha (UTSG 2020) - Accepted Manuscript
Restricted to Repository staff only until 7 July 2022.
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More information

Published date: 6 June 2020
Venue - Dates: 52nd Annual Conference of the Universities' Transport Study Group, ,, 2020-07-06 - 2020-07-06

Identifiers

Local EPrints ID: 442384
URI: http://eprints.soton.ac.uk/id/eprint/442384
PURE UUID: d50ca32e-c9ab-48cd-81f8-dda5a710659f
ORCID for Tafta Nugraha: ORCID iD orcid.org/0000-0002-4754-4713

Catalogue record

Date deposited: 14 Jul 2020 16:32
Last modified: 18 Feb 2021 16:31

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