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

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