Spatio-temporal differences in model outputs and parameter space as determined by calibration extent 7 th International Conference on Geocomputation Charles K. Dietzel Department of Geography University of California – Santa Barbara

Acknowledgements Public Policy Institute of California Dr. Keith C. Clarke, Advisor, UCSB USGS Rocky Mountain Mapping Center –Mark Feller (Geographic Analysis and Monitoring Program)

Presentation Outline Introduction Methods Results Conclusions Broader impacts

Introduction Increased computational power of computers More geospatial data sources Dependence on both of these to better urban and land use models Do outside areas influence the focal study area? To what degree? SLEUTH urban growth model (Clarke et al, 1997)

Methods SLEUTH (Slope, Land use, Exclusion, Urban, Transportation, Hillshade) Cellular Automata Rigorously tested and widely used –Santa Barbara (Candau and Goldstein, 2002) –San Francisco (Clarke et al, 1997) –New York (Esnard and Yang, 2002) –Washington-Baltimore (Clarke and Gaydos, 1998) –Lisbon and Porto (Silva and Clarke, 2002) ‘Brute force’ calibration of historical data

Methods Five parameters of calibration –Diffusion –Breed –Spread –Slope resistance –Road gravity

Methods Calibrated San Joaquin Valley dataset at three extents –San Joaquin County (local) –Bay Area Influenced (regional) –Entire San Joaquin Valley (global)

Results

Conclusions Calibration at different extents shows that local, regional, and global growth cannot be generally characterized Relative to regional and global growth, San Joaquin County is growing faster This method may be used to explore growth dynamics in any system

Broader Impacts Areas outside the focal study area can change the parameter space, and hence the forecasting, of models Inclusion of outside areas can characterize local growth relative to a larger scale Increased computing power warrants modelers including possibly influential areas in future efforts Modelers should spend more time considering the geographic extent of their models

References Candau, J., Goldstein, N.C. (2002). Multiple scenario urban forecasting for the California South Coast region. Proceedings of the 40 th Urban Regional Information Systems Association, Chicago, IL, October 26-30, Clarke, K.C., Gaydos, L. (1998). Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore. International Journal of Geographic Information Science, 12 (7): Clarke, K.C., Hoppen, S., Gaydos, L. (1997). A self-modifying cellular automata model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24: Esnard, A.M., Yang, Y. (2002). Descriptive and Comparative Studies of 1990 Urban Extent Data for the New York Metropolitan Region. URISA Journal, 14 (1): Silva, E. A., Clarke, K.C. (2002). Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems 26: