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Dr. Paul M. Torrens, Center for GIS, Department of Geographical Sciences, and UMIACS, University of Maryland |
Spatiotemporal GIS for big, complex models
Publications are here | Project overview | Eye candy | |
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Project overview | |
Our work in agent-based models often generates huge volumes of data, which we must then sweep, intelligently, to explore phenomena and outcomes in simulation. As our models have grown in size and detail, we have been forging new schemes for organizing the data that they produce, and new media for exploring the dynamics that they suggest. Much of this is based around spatio-temporal GIS, which fuse data models, data access schemes, and visualization approaches that treat dimensions of both space and time. |
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Eye candy | |
The image above shows movement paths for individual, synthetic "agent" pedestrians in our immersive urban model. Agent paths are color-coded by their origin in the simulation, so that we can keep track of group behavior as dynamics of the simulated events unfold. The geovisualization of the paths is used to illustrate geography of movement (sinuosity along the two-dimensional plane that the street network affords) as well as progression in time (the height of the path-ribbon indicates the speed of movement at that place and time; where the ribbon "drops", an agent has slowed-down, usually to avoid a collision or to steer to pursue a new waypoint in their journey). More details of some of the movement analytics that we use to build these geovisualizations are here. |
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![]() Robot motion control |
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![]() Human behavior in critical scenarios |
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![]() Modeling riots |
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A toolkit for measuring sprawl
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![]() Simulating crowd behavior |
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![]() Wi-Fi geography |
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![]() Simulating sprawl |
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