Compare methods

	Urban Growth Boundary Analysis	Urban Simulation Model
Field	Urban Studies	Urban Studies
Family	Process / pipeline	Process / pipeline
Year of origin	1997	2002
Originator	Cellular-automata urban growth lineage (Clarke et al., SLEUTH); UGB policy from Oregon land-use planning	Paul Waddell (UrbanSim); related lineage: cellular automata and agent-based modelling
Type	Scenario simulation and evaluation of urban containment policies	Dynamic computational model of urban development and land use
Seminal source	Clarke, K. C., Hoppen, S., & Gaydos, L. (1997). A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24(2), 247–261.	Waddell, P. (2002). UrbanSim: Modeling urban development for land use, transportation, and environmental planning. Journal of the American Planning Association, 68(3), 297–314.
Aliases	UGB Analysis, Urban Containment Modelling, Growth Boundary Scenario Simulation, Urban Containment Policy Evaluation	Land-Use Microsimulation, Urban Growth Simulation, Agent-Based Urban Model, Integrated Land-Use Transport Simulation
Related	4	4
Summary	Urban growth boundary (UGB) analysis uses spatial simulation to design and evaluate containment lines that separate land where urban development is allowed from land to be kept rural. Built on the cellular-automata urban-growth tradition exemplified by Clarke, Hoppen, and Gaydos's self-modifying SLEUTH model, it calibrates how a region urbanizes, then imposes candidate boundaries as hard or soft constraints and simulates land conversion forward in time. By comparing scenarios with and without a boundary, the method estimates how much farmland and open space a UGB would protect, how much it would densify the interior, and whether it would push leapfrog development beyond the line.	Urban simulation models reproduce the dynamics of urban growth and land-use change by simulating, over time, the decisions of agents — households, firms, developers — or the transitions of cells on a grid. They span agent-based models, cellular automata such as SLEUTH, and microsimulation platforms such as Paul Waddell's UrbanSim, which represents individual households and jobs choosing locations through discrete-choice models linked to a transport network. Rather than predicting a single equilibrium, these models let many local rules and choices interact and feed back through prices and accessibility, generating emergent patterns of sprawl, densification, and redevelopment under alternative policies.