Modelling behavioural responsiveness in city structuring

There is a growing imperative for infrastructure decisions in Australia to be based on evidenced based approaches which are data driven. Urban growth modelling is increasingly being used in strategic infrastructure planning practice. However, current models tend to be "once-off" applications based on static equilibrium approaches that represent little or no behavioural validity. To increase the uptake of urban models to support infrastructure planning we argue these models need to become more responsive to a more complex, multi-modal and demand-side policy environment, founded in behavioural and complexity sciences but also need to be facilitative of participatory planning approaches. This paper presents a critical review of two case study applications of alternative land use modelling approaches in the context of Australian local government areas, assessed against an evaluation framework developed from a set of best practice modelling criteria, sourced from the international literature. The first case study is an application of the more complex, detailed, agent-based model, UrbanSim, in Logan, Queensland (Qld) and the second, the more simple, rule-based model, Online What-if?, applied in the North-West subregion of Perth. These contrasting approaches are considered in terms of their performance in incorporating behaviour in relation to both internal model functionality and in terms of responsiveness to and interaction with the external user environment. Insights are offered into the trade- offs made in practice and what the learning is in relation to reconciling seemingly competing objectives of simplicity for better interaction with external users and complexity for better responsiveness to changing policy and behavioural responsiveness. • The papers presented at the 2015 State of Australian Cities National Conference (SOAC 7) were organised into seven broad themes but all shared, to varying degrees, a common focus on the ways in which high quality academic research can be used in the development and implementation of policy. The relationship between empirical evidence and theoretical developments that are presented as part of our scholarly endeavours and policy processes is rarely clear and straightforward. Sometimes, perhaps because of the fortuitous alignment of various factors, our research has a direct and positive impact on policy. Sometimes it takes longer to be noticed and have influence and, sometimes, there is no little or no evidence of impact beyond or even with the academy. And while there are things we can do to promote the existence of our work and to present it in more accessible formats to people we believe to be influential, ultimately the appreciation and application of our work lies in the hands of others. This paper is one of 164 papers that have each been reviewed and refereed by our peers and revised accordingly. While they each will have been presented briefly at the SOAC conference, they can now be read or re-read at your leisure. We hope they will stimulate further debate and discussion and form a platform for further research. Adapted from the SOAC 7 conference proceedings introduction by Paul Burton and Heather Shearer The State of Australian Cities (SOAC) national conferences have been held biennially since 2003 to support interdisciplinary policy-related urban research. SOAC 7 was held in the City of Gold Coast from 9-11 December 2015. The conference featured leading national and local politicians and policy makers who shared their views on some of the current challenges facing cities and how these might be overcome in the future.

[1]  Douglass B. Lee Requiem for Large-Scale Models , 1973 .

[2]  P. Healey Collaborative Planning: Shaping Places in Fragmented Societies , 1997 .

[3]  Lukas Furst Cities And Complexity Understanding Cities With Cellular Automata Agent Based Models And Fractals , 2016 .

[4]  Daniel Z. Sui RECONSTRUCTING URBAN REALITY: FROM GIS TO ELECTROPOLIS , 1997 .

[5]  Paul Waddell,et al.  Introduction to Urban Simulation: Design and Development of Operational Models , 2004 .

[6]  Ron Janssen,et al.  Effectiveness of collaborative map-based decision support tools: Results of an experiment , 2013, Environ. Model. Softw..

[7]  Andrew Macintosh,et al.  Environment Protection and Biodiversity Conservation Act , 2006 .

[8]  Michel Bierlaire,et al.  An UrbanSim Model of Brussels within a Short Timeline , 2007 .

[9]  M. Wegener Operational Urban Models State of the Art , 1994 .

[10]  Tom Wilston,et al.  A review of sub-regional population projection methods , 2011 .

[11]  Ian D. Bishop,et al.  An Online Landscape Object Library to Support Interactive Landscape Planning , 2011, Future Internet.

[12]  Alan Borning,et al.  Microsimulation of Urban Development and Location Choices: Design and Implementation of UrbanSim , 2003 .

[13]  Michael Batty,et al.  Cities and Complexity: Understanding Cities Through Cellular Automata, Agent-Based Models and Fractals , 2005 .

[14]  Liming Wang,et al.  Microsimulating Parcel-Level Land Use and Activity-Based Travel: Development of a Prototype Application in San Francisco , 2010 .

[15]  Eric J. Miller,et al.  Current operational urban land‐use–transport modelling frameworks: A review , 2005 .

[16]  Kan Chen,et al.  Urban Modeling , 1972, IEEE Trans. Syst. Man Cybern..

[17]  M. Wegener Overview of Land Use Transport Models , 2004 .

[18]  David Pullar,et al.  Subjectively Weighted Development Scenarios for Urban Allocation: A Case Study of South East Queensland , 2007, Trans. GIS.

[19]  Kay W. Axhausen,et al.  The Zurich Case Study of UrbanSim , 2011 .

[20]  David M Levinson,et al.  Models of Transportation and Land Use Change: A Guide to the Territory , 2008 .

[21]  Alice N. O'Connor,et al.  SIEVE: Collaborative Decision-making in an Immersive Online Environment , 2008 .

[22]  S. Glackin,et al.  Redeveloping the greyfields with ENVISION: using participatory support systems to reduce urban sprawl in Australia , 2013 .

[23]  Martin Tomko,et al.  The Online What if? Planning Support System , 2013 .

[24]  Adrian E. Raftery,et al.  Assessing Uncertainty in Urban Simulations Using Bayesian Melding , 2007 .

[25]  Christopher Pettit,et al.  Use of a Collaborative GIS-Based Planning-Support System to Assist in Formulating a Sustainable-Development Scenario for Hervey Bay, Australia , 2005 .

[26]  Juan de Dios Ortúzar,et al.  Modelling Transport, 2nd Edition , 1990 .

[27]  P. Waddell Integrated Land Use and Transportation Planning and Modelling: Addressing Challenges in Research and Practice , 2011 .

[28]  Richard E. Klosterman,et al.  The What If? Collaborative Planning Support System , 1999 .

[29]  Douglass B. Lee,et al.  Requiem for large-scale models , 1973, SIML.

[30]  Matthew Ian Burke,et al.  Improved modelling for urban sustainability assessment and strategic planning: local government planner and modeller perspectives on the key challenges , 2014 .

[31]  Elisabete A. Silva,et al.  Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal , 2002 .

[32]  Michael Batty,et al.  Cities and complexity - understanding cities with cellular automata, agent-based models, and fractals , 2007 .

[33]  Michael Batty Models Again: Their Role in Planning and Prediction , 2015 .

[34]  Richard E. Klosterman,et al.  The Online What if? Planning Support System: A Land Suitability Application in Western Australia , 2015 .

[35]  P. Waddell UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning , 2002 .

[36]  David Pullar,et al.  Using a large scale urban model to test planning scenarios in the Brisbane-South East Queensland region* , 2012 .

[37]  Martin Bell,et al.  Forecasting the pattern of urban growth with PUP: a web-based model interfaced with GIS and 3D animation , 2000 .