Spatially aware agents: An effective and efficient use of GIS data within an agent-based model

Ryan C. Kennedy; Kelly E. Lane; Agustin Fuentes; Hope Hollocher; Greg Madey

Spatially aware agents: An effective and efficient use of GIS data within an agent-based model

Ryan C. Kennedy, Kelly E. Lane, Agustin Fuentes, Hope Hollocher, Greg Madey

Research output: Contribution to conference › Paper › peer-review

Abstract

Agent-based modeling (ABM) is quickly becoming a choice tool for researchers, as it is very adept at modeling natural phenomena. Real-world data has the ability to further increase the usefulness of agent-based models. This can be achieved through the inclusion of geographical information system (GIS) data. Such integration between ABM and GIS may sound trivial, but is difficult to do effectively, particularly as the complexity of GIS data and the amount of agents increase. Here, we present methods and recommendations on including GIS data in a complex simulation model. We demonstrate our techniques to an advanced epidemiological model.

Original language	English (US)
State	Published - Mar 22 2009
Externally published	Yes
Event	2009 Spring Simulation Multiconference, SpringSim 2009 - San Diego, United States Duration: Mar 22 2009 → Mar 27 2009

Conference

Conference	2009 Spring Simulation Multiconference, SpringSim 2009
Country/Territory	United States
City	San Diego
Period	3/22/09 → 3/27/09

All Science Journal Classification (ASJC) codes

Modeling and Simulation

Keywords

Epidemiological modeling
Performance
Raster data
Scientific simulation
Vector data

Cite this

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title = "Spatially aware agents: An effective and efficient use of GIS data within an agent-based model",

abstract = "Agent-based modeling (ABM) is quickly becoming a choice tool for researchers, as it is very adept at modeling natural phenomena. Real-world data has the ability to further increase the usefulness of agent-based models. This can be achieved through the inclusion of geographical information system (GIS) data. Such integration between ABM and GIS may sound trivial, but is difficult to do effectively, particularly as the complexity of GIS data and the amount of agents increase. Here, we present methods and recommendations on including GIS data in a complex simulation model. We demonstrate our techniques to an advanced epidemiological model.",

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author = "Kennedy, {Ryan C.} and Lane, {Kelly E.} and Agustin Fuentes and Hope Hollocher and Greg Madey",

year = "2009",

month = mar,

day = "22",

language = "English (US)",

note = "2009 Spring Simulation Multiconference, SpringSim 2009 ; Conference date: 22-03-2009 Through 27-03-2009",

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TY - CONF

T1 - Spatially aware agents

T2 - 2009 Spring Simulation Multiconference, SpringSim 2009

AU - Kennedy, Ryan C.

AU - Lane, Kelly E.

AU - Fuentes, Agustin

AU - Hollocher, Hope

AU - Madey, Greg

PY - 2009/3/22

Y1 - 2009/3/22

N2 - Agent-based modeling (ABM) is quickly becoming a choice tool for researchers, as it is very adept at modeling natural phenomena. Real-world data has the ability to further increase the usefulness of agent-based models. This can be achieved through the inclusion of geographical information system (GIS) data. Such integration between ABM and GIS may sound trivial, but is difficult to do effectively, particularly as the complexity of GIS data and the amount of agents increase. Here, we present methods and recommendations on including GIS data in a complex simulation model. We demonstrate our techniques to an advanced epidemiological model.

AB - Agent-based modeling (ABM) is quickly becoming a choice tool for researchers, as it is very adept at modeling natural phenomena. Real-world data has the ability to further increase the usefulness of agent-based models. This can be achieved through the inclusion of geographical information system (GIS) data. Such integration between ABM and GIS may sound trivial, but is difficult to do effectively, particularly as the complexity of GIS data and the amount of agents increase. Here, we present methods and recommendations on including GIS data in a complex simulation model. We demonstrate our techniques to an advanced epidemiological model.

KW - Epidemiological modeling

KW - Performance

KW - Raster data

KW - Scientific simulation

KW - Vector data

UR - http://www.scopus.com/inward/record.url?scp=84985884219&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84985884219&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84985884219

Y2 - 22 March 2009 through 27 March 2009

ER -

Spatially aware agents: An effective and efficient use of GIS data within an agent-based model

Abstract

Conference

All Science Journal Classification (ASJC) codes

Keywords

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Cite this