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GIS, GIScience, and Spatial Data: An American Perspective

GIS, GIScience, and Spatial Data: An American Perspective. Michael F. Goodchild University of California, Santa Barbara Walton Fellow, NCG. Uptake of GIS. What’s in a name? geospatial facilities management land information systems

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GIS, GIScience, and Spatial Data: An American Perspective

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  1. GIS, GIScience, and Spatial Data: An American Perspective Michael F. Goodchild University of California, Santa Barbara Walton Fellow, NCG

  2. Uptake of GIS • What’s in a name? • geospatial • facilities management • land information systems • Uptake in all areas that deal with the surface of the Earth • 3D GIS • mining, geophysics • atmospheric science

  3. Why GIS? • Management, inventory, maintenance • in any domain where location is important • Implementing policy • general principles applied in local context • database = local conditions • procedures, algorithms = general principles • simulating outcomes, what-if scenarios • Evaluating policy • mapping outcomes • identifying areas for intervention

  4. Identifying Ethnic Neighborhoods with Census Data: Group Concentration and Spatial Clustering: John R. Logan and Wenquan Zhang

  5. Planning Scenario Visualization and Assessment: A Cellular Automata Based Integrated Spatial Decision Support SystemRoger White, Bas Straatman, and Guy Engelen

  6. Simulations • 1.8 vehicles per driveway • Driver behavior influenced by: • lane width • slope • view distances • traffic control mechanisms • information feedback • driver aggressiveness • 770 homes • clearing times > 30 minutes 2D clip 3D clip

  7. Policy implications • Addition of new outlets • Better deployment of traffic control resources • Understanding the risk • Reduce cars used per household • Problems of shut-ins, elderly, latch-key kids

  8. New technologies • Google Maps • Google Earth • Published APIs • Abundant data • A simple user interface

  9. Animations • http://i.beatthetraffic.com/beatthetraffic3d2.mpg • Bedwell hike • Alan Glennon’s geo/vantage

  10. New application domains • Public health • health service delivery • location analysis • epidemiology • cluster detection • morbidity, mortality • data management • data modeling • GIS in the GP’s office

  11. New application domains • Disaster management • obvious case • all aspects

  12. Data acquisition Design Integration Analysis Interpretation Presentation Stages of problem solving Problem definition

  13. Why does it take so long? • Analysis at the speed of light • Why can't we solve problems in real time? • How can we make it faster? • Disaster management requires rapid response

  14. A 5-stage model 1. Specify 2. Search 3. Assess 4. Retrieve 5. Open

  15. A data model for disaster management • A prepared template • Rapidly populated • using prepared routines • Prepared analysis functions • Up and running within minutes

  16. Computing in the presence of the subject matter • U = S • or S = U1 through Un • Managing the disaster on the spot • Collaborative technologies • Augmented not virtual reality • Mobile, ubiquitous GIS • location-based services

  17. The technologies of U = S • Portable, wearable devices • user interfaces • Positioning • the device knows where it is • Wireless communication • The Spatial Web • everything knows where it is • GPS, RFID, etc.

  18. How does a system know where it is? • GPS onboard • cellphone • Triangulation from towers • Determined at system build time • IP address

  19. Geographic information science • The science behind the systems • Research that will improve future GIS • www.ucgis.org

  20. Current GIScience topics • Extending GIS representation • 3D, time, uncertainty • Extending GIS analysis • simulation modeling • data mining • visualization • Spatial data infrastructures • standards • geoportals

  21. GOS coverage, 1/05

  22. Concluding points • Strong uptake • some important gaps • New technologies • Google Earth, Spatial Web • GIScience • an active research community • SDI • strong institutional framework

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