what is geosimulation mark birkin school of geography, university of leeds
TRANSCRIPT
What Is GeoSimulation
Mark Birkin School of Geography, University of Leeds
What happens to a “system” under certain (extreme) conditions?
How can users be trained cost effectively and at low risk?
What is the performance of new components and design concepts?
GeoSimulation• Attempts to achieve some of the same objectives
as physical simulations through representation of a spatial social system (‘the city’) as a computational model
• Possible goals:– Better understanding of how the system works and its
most important features– Train the drivers of the system (e.g. planners) to make
more effective decisions– Impact analysis: ‘what if?’ scenarios
FOR REAL...
What can I do with a GeoSimulation?
Long-term analytics
Short-term analytics
Real-time analytics
Performanceevaluation
Operations
Tactics
Strategy Housing
Transport
Emergency services
Policing
Hospitals
Schools
Understand policy optionsOptimise
delivery
Evaluate scenarios
Projection of future trends
Observation of historical trends
Visualise demand patterns
Visualise interaction patterns
Visualise supply patterns
Examples of (simulation) models
Examples of (simulation) models
Examples of (simulation) models
Examples of (simulation) models• Bank account?• Building plans?• Map!– A simplified and abstract representation of a ‘real‘
phenomenon– It can be manipulated in some useful way• Can I afford to go on holiday?• Will all the children fit into our new house?• What time should I set off to get to the match?
History of GeoSimulation• Most migrants move only a short distance. • There is a process of absorption, whereby people immediately
surrounding a rapidly growing town move into it and the gaps they leave are filled by migrants from more distant areas, and so on until the attractive force [pull factors] is spent.
• There is a process of dispersion, which is the inverse of absorption. • Each migration flow produces a compensating counter-flow. • Long-distance migrants go to one of the great centers of commerce
and industry. • Natives of towns are less migratory than those from rural areas. • Females are more migratory than males. • Economic factors are the main cause of migration.EG Ravenstein (1885) The Laws of Migration, Journal
of the Royal Statistical Society, 48, 167-227.
History of GeoSimulation
Upper-middle and Upper Classes. Wealthy.
Mixed. Some comfortable, others poor.
Lowest class. Vicious semi-criminal.
Fairly comfortable. Good ordinary earnings.
Very poor, casual. Chronic want. Poor. 18s-21s a week for a moderate family.
Middle class. Well-to-do.
Charles Booth Online Archive, booth.lse.ac.uk
History of GeoSimulation
Park, R., & Burgess, E. (Eds.) (1925). The city. Chicago: University of Chicago Press.
History of GeoSimulation
H Fagin (1963). The Penn Jersey Transportation Study: The Launching of a Permanent Regional Planning Process, Journal of the American Institute of Planners.
History of GeoSimulation• Hollerith’s tabulating machine – introduced in
the US Census 1890
Applications of GeoSimulation• Critiques of the modelling approach:– Douglass Lee (1973) Requiem for Large Scale Urban
Modelling– Andrew Sayer (1976) Understanding Models versus
Understanding Cities– David Harvey (1973) Social Justice and the City
• Provide a framework for:– articulating the scope and boundaries of the methods– prioritising development and evaluating progress
Applications of GeoSimulation• Lee’s Seven Deadly Sins...– Hypercomprehensiveness– Complicatedness– Expensiveness– Hungriness– Wrong-headedness– Grossness– Mechanicalness
Lee, D.B. (1973) Requiem for Large Scale Urban Models, Journal of the American Institute of Planners, 39, 3, 163-178.
Applications of GeoSimulation
Ferguson, N. M., Cummings, A. T., Cauchemez, S., Fraser, C., Riley, S., Meeyai, A., Iamsirithaworn, S. & Burke, D. S. 2005 Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature 437, 209–214.
Applications of GeoSimulationProphylaxis Social Distance
Applications of GeoSimulation• Ferguson– Challenge – investment (3 month sim)– Limitations – simplistic behavioural interactions?– Weaknesses: morphing of virus? Panic behaviour?
• But power – strategic planning; assess merits of alternative interventions; a framework for policy action
Applications of GeoSimulation
Thompson C, Birkin M, McLaughlin F, Hodgson S (2010) The Impact of Target Hardening Policy on Spatial Patterns of Urban Crime in Leeds, GISRUK, London.Malleson, N., L. See, A. Evans, and A. Heppenstall (2011). Implementing comprehensive offender behaviour in a realistic agent-based model of burglary. Simulation. Malleson, N., Birkin, M., Hirschfield, A. & Newton, A. (2012). GeoCrimeData: Understanding Crime Context with Novel Geo-Spatial Data. Paper presented to the Association of American Geographers (AAG) Annual Meeting, February 2012, New York.
Applications of GeoSimulation
Long-term analytics
Short-term analytics
Real-time analytics
Performanceevaluation
Operations
Tactics
Strategy
Housing
Transport
Emergency servicesPolicing
Hospitals
Schools
Understand policy options
Optimise delivery
Evaluate scenarios
Projection of future trends
Observation of historical trends
Visualise demand patterns
Visualise interaction patterns
Visualise supply patterns
The elements• Moving towards Talisman– Data – Visualisation– Computation– Models– Training
The elements• FuturICT
TALISMAN
TALISMAN is a node of the NCRM and is based at the University of Leeds and University College London.TALISMAN’s key objectives are to:• Develop state-of-the-art geospatial models in the form of new data analysis
techniques and simulation models.
• Build new methods of data acquisition and visualisation.• Improve the uptake and dissemination of skills in spatial analysis through
training and capacity-building activities.
For further information about TALISMAN visit: www.geotalisman.org