AUM2020 Session 6 - Effects of the COVID-19 pandemic: from monitoring to modelling

Duration: 2 hours 4 mins

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Description:	1. A Bayesian approach to complex land use change modelling - Calibrating Cellular Automata land use models from urban genesis onwards with Markov Chain Monte Carlo Approximate Bayesian Computation. Dr Jingyan Yu, Dr Alex Hagen-Zanker, Dr Naratip Santitissadeekorn and Dr Susan Hughes (University of Surrey) 2. Assessing the spatial economic impacts of COVID-19 using the Edmonton PECAS model Prof. John Douglas Hunt (University of Calgary) Discussant: Prof. Geoffrey Caruso (University of Luxembourg) Session Chair: Dr Li Wan (University of Cambridge)

Description:

1. A Bayesian approach to complex land use change modelling - Calibrating Cellular Automata land use models from urban genesis onwards with Markov Chain Monte Carlo Approximate Bayesian Computation.
Dr Jingyan Yu, Dr Alex Hagen-Zanker, Dr Naratip Santitissadeekorn and Dr Susan Hughes (University of Surrey)

2. Assessing the spatial economic impacts of COVID-19 using the Edmonton PECAS model
Prof. John Douglas Hunt (University of Calgary)

Discussant: Prof. Geoffrey Caruso (University of Luxembourg)
Session Chair: Dr Li Wan (University of Cambridge)


Created:	2020-11-06 15:45
Collection:	Martin Centre AUM2020: Modelling the New Urban World
Publisher:	University of Cambridge
Copyright:	The Martin Centre
Language:	eng (English)
Keywords:	AUM2020; Effects of the COVID-19 pandemic: from monitoring to modelling; Modelling the New Urban World; session 6; Architecture;


Abstract:	1. We propose a Cellular Automata (CA) urban growth modelling framework and apply it to the English towns Oxford and Swindon. The model calibration is fully automated and a novel application of Markov Chain Monte Carlo Approximate Bayesian Computation (MCMC-ABC). The CA land use change model is formulated with a minimum of required parameters and calibrated from urban genesis onwards. Results suggest that our proposed calibration method effectively captures fundamental characteristics of urban spatial structure and can identify different modes of urban growth. The urban growth modelling framework predicts land use changes well agreeing with empirical observations, overcoming long-standing problems associated with calibration and application of complex and stochastic models over short time periods and with imperfect data. 2. The Province of Alberta in Canada has sponsored the development and application of ASET, the Alberta Spatial Economic Transport model based on the PECAS theoretical framework and software. The City of Edmonton in Alberta is using this model to consider the potential impacts of the changes in behavioural attitudes arising with COVID-19 on the spatial economic and transport system in the Edmonton Region. This presentation describes the assumptions made about the changes in behavioural attitudes arising with COVID-19 starting in 2020 and the indications provided by ASET regarding the impacts of these changes to the year 2039. This demonstrates the inner workings and results of the mechanisms and interactions represented in ASET, and how these as an integrated set of explicit model components can inform economic, land use and transportation planning and adjustments in this planning in response to COVID-19.

Abstract:

1. We propose a Cellular Automata (CA) urban growth modelling framework and apply it to the English towns Oxford and Swindon. The model calibration is fully automated and a novel application of Markov Chain Monte Carlo Approximate Bayesian Computation (MCMC-ABC). The CA land use change model is formulated with a minimum of required parameters and calibrated from urban genesis onwards. Results suggest that our proposed calibration method effectively captures fundamental characteristics of urban spatial structure and can identify different modes of urban growth. The urban growth modelling framework predicts land use changes well agreeing with empirical observations, overcoming long-standing problems associated with calibration and application of complex and stochastic models over short time periods and with imperfect data.

2. The Province of Alberta in Canada has sponsored the development and application of ASET, the Alberta Spatial Economic Transport model based on the PECAS theoretical framework and software. The City of Edmonton in Alberta is using this model to consider the potential impacts of the changes in behavioural attitudes arising with COVID-19 on the spatial economic and transport system in the Edmonton Region. This presentation describes the assumptions made about the changes in behavioural attitudes arising with COVID-19 starting in 2020 and the indications provided by ASET regarding the impacts of these changes to the year 2039. This demonstrates the inner workings and results of the mechanisms and interactions represented in ASET, and how these as an integrated set of explicit model components can inform economic, land use and transportation planning and adjustments in this planning in response to COVID-19.

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