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Urban settlements -- intensely affecting the use of terrestrial, atmospheric, and hydrologic resources -- and their connectivity will be the dominant driver of global change during the twenty-first century.

Forty years ago Jean Gottmann named the huge urban agglomerate that stretched from Washington, D.C. to Boston "Megalopolis", the city of millions. Urban dynamics has surpassed the merely regional scale of Megalopolis, and must now be considered as a continental and global scale phenomenon. Gigalopolis is the growing urban structure containing billions of people worldwide.

Project Gigalopolis extends and refines the Clarke urban growth model, looking toward predictions at regional, continental and eventually global scales.

The goals of the project are to build digital map data sets describing the historical growth and change of urban areas in North America, and to use:

• The historical data to calibrate a cellular automaton model of urban spread and land cover change.
• The model to predict future urban area coverage, land use changes, and the environmental consequences attributable to them.

The work has involved linking models together as well as applying those models.

Broader goals of immediate practical impact have been to:

• Release to the public Federal Geographic Data Committee-compatible data that describe changes in selected urban areas.
• Build and test a cellular automaton model of urban growth and land cover change.
• Calibrate, test and predict the future urban patterns for several key urban areas using the model.
• Examine how local results may be scaled up into national and global land cover change estimates that would be useful in climate and global change modeling.

Funding has been provided by USGS, the State of California, and the National Science Foundation and other support comes from USGS, EPA, and NSF. It involves collaboration with Los Alamos National Laboratory, the National Autonomous University of Mexico (UNAM), and the Santa Barbara Urban Modeling Project.

Web site: http://www.ncgia.ucsb.edu/projects/gig