New forms of data about people and cities, often termed ‘Big’, are fostering research that is disrupting many traditional fields. This is true in geography, and especially in those more technical branches of the discipline such as computational geography / geocomputation, spatial analytics and statistics, geographical data science, etc. These new forms of micro-level data have lead to new methodological approaches in order to better understand how urban systems behave. Increasingly, these approaches and data are being used to ask questions about how cities can be made more sustainable and efficient in the future.
This session will bring together the latest research in urban analytics. We are particularly interested in papers that engage with the following domains:
- Agent-based modelling (ABM) and individual-based modelling;
- Machine learning for urban analytics;
- Innovations in consumer data analytics for understanding urban systems;
- Real-time model calibration and data assimilation;
- Spatio-temporal data analysis;
- New data, case studies, demonstrators, and tools for the study of urban systems;
- Complex systems analysis;
- Geographic data mining and visualisation;
- Frequentist and Bayesian approaches to modelling cities.
For those interested specifically in the interface between research and policy, they might consider submitting their paper to the session “Computation for Public Engagement in Complex Problems” (http://www.gisagents.org/2017/10/call-for-papers-computation-for-public.html).
|Presenter||Andrew Crooks*, George Mason University, Annetta Burger, George Mason University, Xiaoyi Yuan, George Mason University, William G Kennedy, George Mason University, The Generation and Application of Large Scale Synthetic Populations for Disease Outbreaks and Disasters||20||8:00 AM|
|Presenter||Achilleas Psyllidis*, Delft University of Technology, Hendra Hadhil Choiri, Delft University of Technology, A Convolutional Neural Network-based Model for Predicting the Perceived Attractiveness of Urban Places||20||8:20 AM|
|Presenter||Jonathan Reades*, King's College London, Jordan de Souza, King's College London, Elizabeth Sklar, King's College London, Predicting Neighbourhood Change in London with Random Forests||20||8:40 AM|
|Presenter||Nick Malleson*, University of Leeds, Tomas Crols, University of Leeds, Jonathan Ward, University of Leeds, Andrew Evans, University of Leeds, Forecasting Short-Term Urban Dynamics: Data Assimilation for Agent-Based Modelling||20||9:00 AM|
|Presenter||Tomas Crols*, University of Leeds, Nick Malleson, University of Leeds, Calibrating an Agent-Based Model of the Ambient Population using Big Data||20||9:20 AM|
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