Urban Sim

UrbanSim Documentation

URBANSIM is a project of the Urban Analytics Lab

View slide presentation about UrbanSim

The project to develop land use models for the Bay Area was initiated by the Metropolitan Transportation Commission (MTC) in support of Plan Bay Area (the Bay Area’s first Sustainable Communities Strategy). The project was motivated by the need to develop regional plans to reduce greenhouse gas emissions in response to state legislation that set targets for such reduction, by considering changes in land use patterns in combination with transportation investments.

UrbanSim is a modeling system developed to support the need for analyzing the potential effects of land use policies and infrastructure investments on the development and character of cities and regions. The system has been developed using the Python programming language and supporting libraries, and is licensed as Open Source software. Urban- Sim has been applied in a variety of metropolitan areas in the United States and abroad, including Detroit, Eugene- Springfield, Honolulu, Houston, Paris, Phoenix, Salt Lake City, Seattle, and Zürich. The application of UrbanSim for the Bay Area has been developed by the Urban Analytics Lab at UC Berkeley under contract to MTC.

UrbanSim has been developed to support land use, transportation and environmental planning, with particular attention to the regional transportation planning process. The kinds of tasks for which UrbanSim has been designed include the following:

  • Predicting land use information for input to the travel model, for periods of 10 to 40 years into the future, as needed for regional transportation planning.
  • Predicting the effects on land use patterns from alternative investments in roads and transit infrastructure, or in alternative transit levels of service, or roadway or transit pricing, over long-term forecasting horizons. Scenarios can be compared using different transportation network assumptions, to evaluate the relative effects on development from a single project or a more wide-reaching change in the transportation system, such as extensive congestion pricing.
  • Predicting the effects of changes in land use regulations on land use, including the effects of policies to relax or increase regulatory constraints on development of different types, such as an increase in the allowed Floor Area Ratios (FAR) on specific sites, or allowing mixed-use development in an area previously zoned only for one use.
  • Predicting land use development patterns in high-capacity transit corridors.
  • Predicting the effects of environmental policies that impose constraints on development, such as protection of wetlands, floodplains, riparian buffers, steep slopes, or seismically unstable areas.
  • Predicting the effects of changes in the macroeconomic structure or growth rates on land use. Periods of more rapid or slower growth, or even decline in some sectors, can lead to changes in the spatial structure of the city, and the model system is designed to analyze these kinds of shifts.
  • Predicting the possible effects of changes in demographic structure and composition of the city on land use, and on the spatial patterns of clustering of residents of different social characteristics, such as age, household size and income.
  • Examining the potential impacts on land use and transportation of major development projects, whether actual or hypothetical. This could be used to explore the impacts of a corporate relocation, or to compare alternative sites for a major development project.