Post on 21-Dec-2015
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...
…where you spend it...
…who you talk to...
…where you live...
What your neighbours are like, what your house is
...Crime data and...
• crime type• crime location• insurance data
...Health data
• environmental data• socio-economic data• admissions data
The Cray T3D and T3E
• High Performance Computing
• Time machines• Just big enough for
modern geographical problems
The Internet
• GIS and the Web– Public participation in
planning
• Distributed Computing– “many hands make light
work”
What can we do with all this data and computer power?
•Explore it
•Explain it
•Exploit it
Exploration
• Given some (large amount of) data
• find anything that is “interesting” in that data
Pattern Analysis
• GAM• GEM• Automated analysis• Easy to understand
output• No statistical
assumptions• crime, health,
education ...
Spatial Search Agents
• If we don’t know where to look
• Look every where?• Or let something else
do the looking?
Urban Social Structure
Glasgow and London
Fourier-Mellin space
Glasgow and London
Rezoning
• Census variables and areas
• Sales areas• Voting districts
Explanation
• Having found something “interesting” in a data set
• Attempt to explain it or model it
Spatial Interaction Models
• Migration flows• Commuting flows
– GB Ward to Wards flows (10,000)
• Phone flows – (20+ Million)
• EU Flows
Cellular Automata
• Simple CA Life• Complex multi-state
CA forest fires• Pedestrian or traffic
movements
Neural Nets
• Black Box • Non-linear parameter
free estimations• Used any where a
“normal” model could be used.
Fuzzy Logic
• Allows the introduction of imprecision to model• More computation gives better answers
Agents on a Ring
• Catherine Dibble• Agents can move
along the lines GROW
MAKE
SERVSERV
INFOINFO
Generate reasonable patterns
Exploitation
• Having found something of interest
• and explained it (in some way)
• make use of this knowledge
Spatial Location Optimisation
• Based on spatial interaction model
• Run the model 1000’s of times
• In this case 10,000 zones
Flood Forecasting
• How likely is it to flood in the next 6 hours?
• Neural nets• Fuzzy Logic
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
Conclusions
• More data– better data
• More computing– better computing
• More models– better models