Spatial Differences in Multi‐Resolution Urban Automata Modeling

The last decade has seen a renaissance in spatial modeling. Increased computational power and the greater availability of spatial data have aided in the creation of new modeling techniques for studying and predicting the growth of cities and urban areas. Cellular automata is one modeling technique that has become widely used and cited in the literature; yet there are still some very basic questions that need to be answered with regards to the use of these models, specifically relating to the spatial resolution during calibration and how it can impact model forecasts. Using the SLEUTH urban growth model (Clarke et al. 1997), urban growth for San Joaquin County (CA) is projected using three different spatial grains, based on four calibration routines, and the spatial differences between the model outputs are examined. Model outputs show that calibration at finer scaled data results in different parameter sets, and forecasting of urban growth in areas that was not captured through the use of more coarse data.

[1]  S. Goetz,et al.  Using the Sleuth Urban Growth Model to Simulate the Impacts of Future Policy Scenarios on Urban Land Use in the Baltimore-Washington Metropolitan Area , 2004 .

[2]  R. Stimson,et al.  An On-line Planning Support System to Evaluate Urban and Regional Planning Scenarios , 2003 .

[3]  Timothy Evans,et al.  A Review and Assessment of Land-Use Change Models Dynamics of Space, Time, and Human Choice , 2002 .

[4]  Keith C. Clarke,et al.  A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area , 1997 .

[5]  Roger White,et al.  Towards an automatic calibration procedure for constrained cellular automata , 2004, Comput. Environ. Urban Syst..

[6]  Jennifer L. Dungan,et al.  A balanced view of scale in spatial statistical analysis , 2002 .

[7]  Alan T. Murray,et al.  A stochastically constrained cellular model of urban growth , 2000 .

[8]  M. Wegener.  Operational Urban Models State of the Art , 1994 .

[9]  Richard E. Klosterman,et al.  The What If? Collaborative Planning Support System , 1999 .

[10]  Douglass B. Lee,et al.  Requiem for large-scale models , 1973, SIML.

[11]  P. Torrens,et al.  Cellular Automata and Urban Simulation: Where Do We Go from Here? , 2001 .

[12]  Xiaojun Yang,et al.  Modelling urban growth and landscape changes in the Atlanta metropolitan area , 2003, Int. J. Geogr. Inf. Sci..

[13]  Ann-Margaret Esnard,et al.  Descriptive and Comparative Studies of 1990 Urban Extent Data for the New York Metropolitan Region , 2002 .

[14]  Keith C. Clarke,et al.  Geographic Information Systems and Environmental Modeling , 2001 .

[15]  E. Silvaa,et al.  Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal , 2002 .

[16]  Douglass B. Lee.  Retrospective on Large-Scale Urban Models , 1994 .

[17]  Ming Zhang,et al.  The Second Generation of the California Urban Futures Model. Part 2: Specification and Calibration Results of the Land-Use Change Submodel , 1998 .

[18]  Anthony Gar-On Yeh,et al.  Zoning land for agricultural protection by the integration of remote sensing, GIS, and cellular automata , 2001 .

[19]  Thomas Maxwell,et al.  Resolution and predictability: An approach to the scaling problem , 1994, Landscape Ecology.

[20]  PETER H. VERBURG,et al.  Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model , 2002, Environmental management.

[21]  Douglass B. Lee.  Requiem for Large-Scale Models , 1973 .

[22]  Richard E. Klosterman,et al.  Planning Support Systems: Integrating Geographic Information Systems,Models,and Visualization Tools , 2001 .

[23]  John Stillwell,et al.  Planning Support Systems in Practice , 2003 .

[24]  M. Batty,et al.  Modeling urban dynamics through GIS-based cellular automata , 1999 .

[25]  Elisabete A. Silva,et al.  Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal , 2002 .

[26]  Michael Batty,et al.  Modelling Inside GIS: Part 2. Selecting and Calibrating Urban Models Using ARC-INFO , 1994, Int. J. Geogr. Inf. Sci..

[27]  M. Batty,et al.  Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation , 2003, Comput. Environ. Urban Syst..

[28]  Fulong Wu,et al.  Calibration of stochastic cellular automata: the application to rural-urban land conversions , 2002, Int. J. Geogr. Inf. Sci..

[29]  Keith C. Clarke,et al.  Loose-Coupling a Cellular Automaton Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore , 1998, Int. J. Geogr. Inf. Sci..

[30]  Roger White,et al.  Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns , 1993 .

[31]  Helen Couclelis,et al.  Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics , 1985 .