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The Future of GeoComputation

The Future of GeoComputation. Ian Turton Centre for Computational Geography University of Leeds. Summary. People Data Space Time Computing Methods Explorative Explanative Exploitative. The CCG. Some of them anyway. Mountains of Data. Swamps of Data. We know what you spend.

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The Future of GeoComputation

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  1. The Future of GeoComputation Ian Turton Centre for Computational Geography University of Leeds

  2. Summary • People • Data • Space • Time • Computing • Methods • Explorative • Explanative • Exploitative

  3. The CCG Some of them anyway

  4. Mountains of Data

  5. Swamps of Data

  6. We know what you spend...

  7. …where you spend it...

  8. …who you talk to...

  9. …where you live... What your neighbours are like, what your house is

  10. ...Crime data and... • crime type • crime location • insurance data

  11. ...Health data • environmental data • socio-economic data • admissions data

  12. The Cray T3D and T3E • High Performance Computing • Time machines • Just big enough for modern geographical problems

  13. The Internet • GIS and the Web • Public participation in planning • Distributed Computing • “many hands make light work”

  14. What can we do with all this data and computer power? • Explore it • Explain it • Exploit it

  15. Exploration • Given some (large amount of) data • find anything that is “interesting” in that data

  16. Pattern Analysis • GAM • GEM • Automated analysis • Easy to understand output • No statistical assumptions • crime, health, education ...

  17. Spatial Search Agents • If we don’t know where to look • Look every where? • Or let something else do the looking?

  18. Urban Social Structure Glasgow and London

  19. Fourier-Mellin space Glasgow and London

  20. Rezoning • Census variables and areas • Sales areas • Voting districts

  21. Explanation • Having found something “interesting” in a data set • Attempt to explain it or model it

  22. Spatial Interaction Models • Migration flows • Commuting flows • GB Ward to Wards flows (10,000) • Phone flows • (20+ Million) • EU Flows

  23. Cellular Automata • Simple CA Life • Complex multi-state CA forest fires • Pedestrian or traffic movements

  24. Neural Nets • Black Box • Non-linear parameter free estimations • Used any where a “normal” model could be used.

  25. Fuzzy Logic • Allows the introduction of imprecision to model • More computation gives better answers

  26. Agents on a Ring • Catherine Dibble • Agents can move along the lines • GROW • MAKE • SERV • INFO • Generate reasonable patterns

  27. Exploitation • Having found something of interest • and explained it (in some way) • make use of this knowledge

  28. Spatial Location Optimisation • Based on spatial interaction model • Run the model 1000’s of times • In this case 10,000 zones

  29. Flood Forecasting • How likely is it to flood in the next 6 hours? • Neural nets • Fuzzy Logic

  30. Sensitivity Analysis on Models • Run the model 1000’s of times with perturbations to inputs • Get out real error estimates • Population Models • Flood Models • Drainage Models

  31. Conclusions • More data • better data • More computing • better computing • More models • better models

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