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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
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.

 
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.


GIS movement tracks

Massive ice CA

GIS movement tracks

Spatiotemporal GIS

GIS movement tracks

Urban simulation in GIS

GIS movement tracks

Big data movement analytics

 

climate indicators spatial analysis

Land indicators of climate

geosimulation high performance computing

High-performance computing and networking for geosimulation

earthquake model agent based GIS

Earthquake models

CA ice sheet model

Ice-sheet modeling





kinect control of GIS and robots
Robot motion control



simulating disasters ABM GIS
Human behavior in critical scenarios



crowd model riot model simulation wired

Modeling riots



physics engine GIS

Dynamic physics for built infrastructure




moving agents through space and time

Moving agents through space and time




validating agent based models

Validating agent-based models




machine learning GIS

Machine-learning behavioral geography




high performance computing urban simulation emergence

Accelerating agent-based models




megacity models

Megacity futures




immersive modeling

Immersive modeling




space-time GIS

Space-time GIS and analysis




measuring sprawl

A toolkit for measuring sprawl




space-time GIS

Modeling time, space, and behavior




simulating crowd behavior

Simulating crowd behavior



wi-fi geography

Wi-Fi geography


Simulating sprawl

Simulating sprawl