Analysis of scale dependencies in an urban land‐use‐change model

Different processes shaping land‐use patterns are observed at different scales. In land‐use modelling, scale can influence the measurement and quantitative description of land‐use patterns and can therefore significantly impact the behaviour of model parameters that describe land‐use change processes. We present results of a rigorous sensitivity analysis of a cellular urban land‐use‐change model, SLEUTH, testing its performance in response to varying cell resolutions. Specifically, we examine the behaviour of each type of urban growth rule across different cell sizes, and explore the model's ability to capture growth rates and patterns across scales. Our findings suggest that SLEUTH's sensitivity to scale extend beyond issues of calibration. While the model was able to capture the rate of growth reliably across all cell sizes, differences in its ability to simulate growth patterns across scales were substantial. We also observed significant differences in the sensitivity of the growth rules across cell sizes, indicating that SLEUTH may perform better at certain cell sizes than at others. These findings emphasize the importance of scale considerations in land‐use‐change modelling research, particularly in terms of determining the relevant and appropriate scales of enquiry for the processes being simulated.

[1]  David R. Lee,et al.  A Method of Measuring Shape , 1970 .

[2]  R. H. Gardner,et al.  Quantifying scale-dependent effects of animal movement with simple percolation models , 1989, Landscape Ecology.

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

[4]  Helen Couclelis,et al.  From Cellular Automata to Urban Models: New Principles for Model Development and Implementation , 1997 .

[5]  Kasper Kok,et al.  A method and application of multi-scale validation in spatial land use models , 2001 .

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

[7]  N. Grimm,et al.  Integrated Approaches to Long-TermStudies of Urban Ecological Systems , 2000 .

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

[9]  K. Kok,et al.  Evaluating impact of spatial scales on land use pattern analysis in Central America , 2001 .

[10]  Stephen J. Walsh,et al.  A multiscale analysis of LULC and NDVI variation in Nang Rong district, northeast Thailand , 2001 .

[11]  Peter H. Verburg,et al.  Multiscale Characterization of Land-Use Patterns in China , 2000, Ecosystems.

[12]  Michael Batty,et al.  Agent-based pedestrian modelling , 2003 .

[13]  B. Soares-Filho,et al.  dinamica—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier , 2002 .

[14]  Michael Batty,et al.  Dynamics of urban sprawl , 1999 .

[15]  E. Ostrom,et al.  The concept of scale and the human dimensions of global change: a survey , 2000, Ecological Economics.

[16]  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 .

[17]  R. White,et al.  High-resolution integrated modelling of the spatial dynamics of urban and regional systems , 2000 .

[18]  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..

[19]  Robert A. Johnston,et al.  COMPREHENSIVE REGIONAL MODELING FOR LONG-RANGE PLANNING: LINKING INTEGRATED URBAN MODELS AND GEOGRAPHIC INFORMATION SYSTEMS. IN: THE AUTOMOBILE , 2000 .

[20]  Patrick L. Kinney,et al.  Assessing Potential Public Health Implications of Changing Climate and Land Uses: The New York Climate and Health Project , 2006 .

[21]  N. Bockstael Modeling Economics and Ecology: The Importance of a Spatial Perspective , 1996 .

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

[23]  N. Grimm,et al.  Integrated Approaches to Long-TermStudies of Urban Ecological Systems , 2000 .

[24]  Daniel Z. Sui,et al.  GIS-Based Urban Modelling: Practices, Problem, and Prospects , 1998, Int. J. Geogr. Inf. Sci..

[25]  Paul M. Torrens,et al.  Cellular Models of Urban Systems , 2000, ACRI.

[26]  Michael Batty Changes in the Journal , 2004 .

[27]  Xia Li,et al.  A Constrained CA Model for the Simulation and Planning of Sustainable Urban Forms by Using GIS , 2001 .

[28]  Jayantha Obeysekera,et al.  Selection of scale for Everglades landscape models , 1997, Landscape Ecology.

[29]  Michael Batty,et al.  Urban Evolution on the Desktop: Simulation with the Use of Extended Cellular Automata , 1998 .

[30]  Jianguo Wu,et al.  A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications , 2002 .

[31]  G. D. Jenerette,et al.  © 2001 Kluwer Academic Publishers. Printed in the Netherlands. Research Article Analysis and simulation of land-use change in the central Arizona – , 2022 .

[32]  Guy Engelen,et al.  Cellular Automata as the Basis of Integrated Dynamic Regional Modelling , 1997 .

[33]  A. Yeh,et al.  A Cellular Automata Model to Simulate Development Density for Urban Planning , 2002 .

[34]  John R. Skalski,et al.  Determination of ecological scale , 1989, Landscape Ecology.