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 GISUptake 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
Why GIS?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
Identifying Ethnic Neighborhoods with Census Data: Group Concentration and Spatial Clustering: John R. Logan and Wenquan Zhang
Planning Scenario Visualization and Assessment: A Cellular Automata Based Integrated Spatial Decision Support SystemRoger White, Bas Straatman, and Guy Engelen
SimulationsSimulations 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
Policy implicationsPolicy 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
New technologiesNew technologies
Google Maps Google Earth Published APIs Abundant data A simple user interface
AnimationsAnimations
http://i.beatthetraffic.com/beatthetraffic3d2.mpg
Bedwell hike Alan Glennon’s geo/vantage
New application domainsNew application domains
Public health– health service delivery
• location analysis
– epidemiology• cluster detection• morbidity, mortality
– data management• data modeling
– GIS in the GP’s office
New application domainsNew application domains
Disaster management– obvious case– all aspects
Stages of problem solvingStages of problem solving
Problem definition
Problem definition DesignDesign Data
acquisition
Data acquisition
IntegrationIntegration
AnalysisAnalysis
InterpretationInterpretationPresentationPresentation
Why does it take so long?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
A 5-stage modelA 5-stage model
1. Specify1. Specify
2. Search2. Search
3. Assess3. Assess
4. Retrieve4. Retrieve
5. Open5. Open
A data model for disaster managementA data model for disaster management
A prepared template Rapidly populated
– using prepared routines Prepared analysis functions Up and running within minutes
Computing in the presence of the subject matterComputing 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
The technologies of U = SThe 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.
How does a system know where it is?How does a system know where it is?
GPS onboard– cellphone
Triangulation from towers Determined at system build time IP address
Geographic information scienceGeographic information science
The science behind the systems Research that will improve future GIS www.ucgis.org
Current GIScience topicsCurrent GIScience topics
Extending GIS representation– 3D, time, uncertainty
Extending GIS analysis– simulation modeling– data mining– visualization
Spatial data infrastructures– standards– geoportals
GOS coverage, 1/05
Concluding pointsConcluding points
Strong uptake– some important gaps
New technologies– Google Earth, Spatial Web
GIScience– an active research community
SDI– strong institutional framework