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Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation
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Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation

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"Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation", Mark Birkin, March 2010

"Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis. Presentation", Mark Birkin, March 2010

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  • Macroscopic model: not sensitive to e.g. doubling in physical size of Leeds or dramatic counter-urbanisation? (maybe just needs a tweak for average trip length).
  • Transcript

    • 1. Spatial Microsimulation for City Modelling, Social Forecasting and Urban Policy Analysis<br />Mark Birkin 6649386<br />
    • 2. Example: Urban Simulation<br />MoSeS Project<br /><ul><li>Can we project the population of a city forwards in time over a 25 year period?
    • 3. technically & intellectually demanding
    • 4. policy relevant
    • 5. housing, transport, health care, education, …
    • 6. Three components
    • 7. Population reconstruction
    • 8. Dynamic simulation
    • 9. Activity and behaviourmodelling</li></li></ul><li>Health and social care...<br />2006<br />2001<br />2031<br />2016<br />
    • 10. Health and Social Care…<br />2001<br />2031<br />Co-dependency<br />LLTI<br />2031<br />2001<br />
    • 11. Health and Social Care…<br />2001<br />2031<br />Ethnicity<br />2031<br />2001<br />Multiple<br />Deprivation<br />
    • 12. Moses Dynamic Model<br />Transition rates for fertility, mortality and migration are spatially disaggregated<br />E.g. fertility: rates by age, marital status and location<br />Event is simulated as a Monte Carlo process<br />Example: married woman, aged 28, living in Aireborough<br />Probability of maternity is 0.127<br />Pull a probability from a distribution of random numbers; if <= 0.127 then the event occurs<br />All events in discrete intervals of one year<br />
    • 13. MoSeS Data Sources<br />Census Small Area Statistics<br />Special Migration Statistics<br />Health Survey for England<br />Household and Individual SARS<br />International Passenger Statistics<br />National Travel Survey<br />ONS Vital Statistics<br />BHPS<br />General Household Survey<br />Hospital Episode Statistics<br />EASEL Housing Needs Study<br />Google Maps<br />
    • 14. Moses Dynamic Model<br />
    • 15. Moses Dynamic Model<br />
    • 16. Moses Dynamic Model<br />
    • 17. Moses Dynamic Model<br />
    • 18. Moses Dynamic Model<br />
    • 19. Moses Dynamic Model<br />
    • 20. Moses Dynamic Model<br />
    • 21. Moses Dynamic Model<br />
    • 22. MoSeS Dynamic Model<br />
    • 23. Transport…<br />Population and average speed changes in Leeds from 2001 to 2031<br />
    • 24. 2031<br />2001<br />Transport…<br />2015<br />Traffic Intensity *<br />* Traffic Intensity=Traffic load/Road capacity<br />
    • 25. Scenario-based forecasting<br />
    • 26. Public Policy<br /> Source: MAPS2030<br />
    • 27. Simulation of Epidemics<br />Ferguson et al, Nature, 2006<br />
    • 28. The El Farol Bar Problem<br /><ul><li>Everyone wants to go the bar </li></ul> - unless it’s too crowded!<br /><ul><li>Must relax neoclassical economic assumptions (homogeneity of preferences, simultaneous decision-making)
    • 29. Individual actors/ agent-based decision-making</li></ul> - generic template for real markets<br /> heterogeneous<br /> out of equilibrium<br /> (Arthur, 1994)<br />
    • 30. NeISS Architecture<br />
    • 31. NeISS Portal<br />
    • 32. NeISS Portal<br />
    • 33.
    • 34. Data Issues and Questions<br /><ul><li>Complexity
    • 35. Visualisation
    • 36. Integration
    • 37. Proliferation
    • 38. Generation</li></li></ul><li>Complexity of data<br />Complexity, scale and volume of data inputs<br />
    • 39. Data visualisation<br />
    • 40. Data integration<br />Modelling and simulation as data integration<br /><ul><li>“Data diarrhoea, information constipation”
    • 41. -> data compression
    • 42. -> missing data</li></li></ul><li>Proliferation of data domains<br /><ul><li>“customer science”
    • 43. public/ private/ commercial
    • 44. Crowd-sourced data</li></li></ul><li>Data Generation<br />Example 1. (Silverburn)<br /><ul><li>400 post sectors
    • 45. 100 destinations
    • 46. 6 ages
    • 47. 4 ethnic groups
    • 48. 4 social/ income groups
    • 49. 2 car ownership
    • 50. 516 inputs; 8 million model flows (sparse matrix!)</li></ul>Example 2. (MoSeS)<br /><ul><li>25 years of simulation
    • 51. 60 million individuals
    • 52. 200? characteristics
    • 53. 20? scenarios</li></ul>Example 1. (Silverburn)<br /><ul><li>400 post sectors
    • 54. 100 destinations
    • 55. 6 ages
    • 56. 4 ethnic groups
    • 57. 4 social/ income groups
    • 58. 2 car ownership
    • 59. 516 inputs; 8 million model flows (sparse matrix!)</li></ul>Example 2. (MoSeS)<br /><ul><li>25 years of simulation
    • 60. 60 million individuals
    • 61. 200? characteristics
    • 62. 20? scenarios</li></ul>Example 3. (Epstein, 2009)<br /><ul><li>8 billion agents!
    • 63. Dynamic resolution at 10 minute intervals?!!</li></ul>Example 3. (Epstein, 2009)<br /><ul><li>8 billion agents!
    • 64. Dynamic resolution at 10 minute intervals?!!</li></li></ul><li>Conclusion<br /><ul><li>Social simulation involves quite a lot of data intensive research!!
    • 65. Note that quite a lot of social scientists have so far failed to appreciate this important fact!!!</li>

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