New urban development creates a need for additional public infrastructure, including improved transportation facilities and extended water and sewer utility services. At the same time, the provision of new public infrastructure can significantly affect the urban development patterns. Plans for public infrastructure must take into account both future urban development patterns and the effects of those plans on those future patterns. The Land Use in Central Indiana (LUCI) model simulates future urban development for a large region. The model generates alternative development scenarios incorporating different policy choices and assumptions about future development. These include choices about the provision of public infrastructure and the effects of such infrastructure on urban development. LUCI thus serves as a tool that can help people understand complex relationships between urban development and the provision of public infrastructure.
Get full access to this article
View all access options for this article.
References
1.
Agarwal, C., et al. (2000). A review and assessment of land-use change models: Dynamics of space, time, and human choice. Bloomington, IN: Center for the Study of Institutions, Population, and Environmental Change, Indiana University, and South Burlington, VT: USDA Forest Service.
2.
Avin, U. P., & Dembner, J. L. (2001). Getting scenario building right. Planning, 67(11), 22-27.
3.
Batty, M. (1994). A chronicle of scientific planning: The Anglo-American modeling experience. Journal of the American Planning Association, 60(1), 7-16.
4.
Brail, R. K., & Klosterman, R. E. (Eds.). (2001). Planning support systems. Redlands, CA: ESRI Press.
5.
Chapin, F. S., Jr. (1965). A model for simulating residential development. Journal of the American Institute of Planners, 31(2), 120-136.
6.
Chapin, F. S., Jr., & Weiss, S. F. (1968). A probabilistic model for residential growth. Transportation Research, 2, 375-390.
7.
Chen, J., et al. (2002). Assessment of the urban development plan of Beijing by using a CA-based urban growth model. Photogrammetric Engineering & Remote Sensing, 68(10), 1063-1071.
8.
Geertman, S., & Stillwell, J. (Eds.). (2002). Planning support systems in practice. Heidelberg: Springer.
9.
Gunter, J. T., Hodges, D. G., Swaim, C. M., & Regens, J. L. (2000). Predicting the urbanization of pine and mixed forests in Saint Tammany Parish, Louisiana. Photogrammetric Engineering & Remote Sensing, 66(12), 1469-1476.
10.
Harris, B. (1994). The real issues concerning Lee's “Requiem.” Journal of the American Planning Association, 60(1), 31-34.
11.
Harris, B. (2001). Sketch planning: Systematic methods in planning and its support. In R. K. Brail & R. E. Klosterman (Eds.), Planning support systems (pp. 59-80). Redlands, CA: ESRI Press.
12.
Harris, B., & Batty, M. (1993). Locational models, geographic information and planning support systems. Journal of Planning Education and Research, 12, 184-198.
13.
Hill, D. M. (1965). A growth allocation model for the Boston region. Journal of the American Institute of Planners, 3(2), 111-120.
14.
Hopkins, L. D. (1999). Structure of a planning support system for urban development. Environment and Planning B: Planning and Design, 26(3), 333-343.
15.
Indiana Department of Education. (2001). ISTEP total battery scores for 1999-2000 for school corporations [Online]. Available: http://www.doe.state.in.us/
16.
Kent State University, Applied Geography Laboratory. (2001). Urban growth simulator: Self-guided workbook [Online]. Available: http://empact.geog.kent.edu/
17.
Klosterman, R. E. (1994a). Large-scale urban models: Retrospect and prospect. Journal of the American Planning Association, 60(1), 3-6.
18.
Klosterman, R. E. (1994b). An introduction to the literature on large-scale urban models. Journal of the American Planning Association, 60(1), 41-44.
19.
Klosterman, R. E. (1997a). Planning support systems: A new perspective on computer-aided planning. Journal of Planning Education and Research, 17(1), 45-54.
20.
Klosterman, R. E. (1997b). The What-If? collaborative planning support system. Environment and Planning B: Planning and Design, 26(3), 393-408.
21.
Klosterman, R. E., et al. (2002). Farmland preservation policies studied with GIS. ArcNews, 24(1), 14-15.
22.
Landis, J. D. (1994). The California Urban Futures Model: A new generation of metropolitan simulation models. Environment and Planning B: Planning and Design, 21(4), 399-420.
23.
Landis, J. D. (1995). Imagining land use futures: Applying the California Urban Futures Model. Journal of the American Planning Association, 61(4), 438-458.
24.
Landis, J. D. (2001). CUF, CUF II, and CURBA: A family of spatially explicit urban growth and land-use policy simulation models. In R. K. Brail & R. E. Klosterman (Eds.), Planning support systems (pp. 157-200). Redlands, CA: ESRI Press.
25.
Landis, J. D., & Zhang, M. (1998a). The second generation of the California Urban Futures Model. Part 1: Model logic and theory. Environment and Planning B: Planning and Design, 25(5), 657-666.
26.
Landis, J. D., & Zhang, M. (1998b). The second generation of the California Urban Futures Model. Part 2: Specification and calibration results of the land-use change submodel. Environment and Planning B: Planning and Design, 25(6), 795-824.
27.
Lee, D. B. (1973). Requiem for large-scale models. Journal of the American Institute of Planners, 39(3), 163-178.
28.
Lee, D. B. (1994). Retrospective on large-scale urban models. Journal of the American Planning Association, 60(1), 35-40.
29.
Lee, J., Klosterman, R. E., Salling, M., & Kulikowski, T. D. (1999). Development of a community-accessible urban sprawl impact assessment system in northeast Ohio 15-county region for the Empact Project, phase one report: Literature review for urban growth modeling and environmental impact analysis [Online]. Available: http://empact.geog.kent.edu/
30.
Lee, J., Tian, L., Erickson, L. J., & Kulikowski, T. D. (1998). Analyzing growth-management policies with geographical information systems. Environment and Planning B: Planning and Design, 25(6), 865-879.
31.
Li, X., & Yeh, A.G-O. (2002). Urban simulation using principal components analysis and cellular automata for land-use planning. Photogrammetric Engineering & Remote Sensing, 68(4), 341-351.
32.
Pack, J. R. (1978). Urban models: Diffusion and policy applications. Philadelphia: Regional Science Research Institute.
33.
Pijanowski, B. C., Brown, D. G., Shellito, B. A., & Manik, G. A. (2002). Using neural networks and GIS to forecast land use changes: A Land Transformation Model. Computers, Environment and Urban Systems, 26(6), 553-575.
34.
Pijanowski, B. C., Gage, S. H., Long, D. T., & Cooper, W. E. (2000). A Land Transformation Model for the Saginaw Bay watershed. In J. Sanderson & L. D. Harris (Eds.), Landscape ecology: A top-down approach (pp. 183-198). Boca Raton, FL: Lewis Publishers.
35.
Putman, S. H. (1983). Integrated urban models: Policy analysis of transportation and land use. London: Pion.
36.
Putman, S. H., & Chang, S-L. (2001). The METROPILUS planning support system: Urban models and GIS. In R. K. Brail & R. E. Klosterman (Eds.), Planning support systems (pp. 99-128). Redlands, CA: ESRI Press.
37.
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(6), 525-552.
38.
Southworth, F. (1995). A technical review of urban land use-transportation models as tools for evaluating vehicle travel reduction strategies. Washington, DC: U.S. Department of Energy.
39.
Timmermans, H. (Ed.). (1997). Decision support systems in urban planning. London: E & F Spon.
40.
U.S. Bureau of the Census. (1996). ZIP code business patterns, 1994 on CD-ROM [machine-readable data file]. Washington, DC: Author.
41.
U.S. Bureau of the Census. (2000). ZIP code business patterns, 1998 on CD-ROM [machine-readable data file]. Washington, DC: Author.
42.
U.S. Bureau of the Census. (2002). Census 2000. Summary File 1, Indiana [Online]. Available: http://www.census.gov
43.
U.S. Environmental Protection Agency. (2000). Projecting land-use change: A summary of models for assessing the effects of community growth and change on land-use patterns. Washington, DC: Author.
44.
Waddell, P. (2000). A behavioral simulation model for metropolitan policy analysis and planning: Residential location and housing market components of Urban Sim. Environment and Planning B: Planning and Design, 27(2), 247-263.
45.
Waddell, P. (2001). Between politics and planning: Urban Sim as a decision support system for metropolitan planning. In R. K. Brail & R. E. Klosterman (Eds.), Planning support systems (pp. 201-228). Redlands, CA: ESRI Press.
46.
Wegener, M. (1994). Operational urban models: State of the art. Journal of the American Planning Association, 60(1), 17-30.
47.
Wrigley, N. (1985). Categorical data analysis for geographers and environmental scientists. New York: Longman.
