Foreword Michael Batty.- Acknowledgements.-Biographies of the Editors and Contributors.- I Introduction: 1. Geospatial Analysis and Modeling of Urban Structure and Dynamics: An Overview.- II. Individual-Based Data Capture for Modeling Urban Structure and Dynamics: 2. High-resolution Geographic Data and Urban Modeling: The Case of Residential Segregation.- 3. Space Syntax and Pervasive Systems.- 4. Decentralized Spatial Computing in Urban Environments.- III. Modeling Urban Complexity and Hierarchy: 5. Network Cities: a Complexity-Network Approach to Urban Dynamics and Development.- 6. Scaling Analysis of the Cascade Structure of the Hierarchyof Cities.- IV. Simulating and Modeling Urban Transportation Systems: 7. The Dilemma of On-street Parking Policy: Exploring Cruising for Parking Using an Agent-based Model.- 8. Multiscale Modeling of Virtual Urban Environments and Associated Populations.- 9. Imageability and Topological Eccentricity of Urban Streets.- 10. A Spatial Analysis of Transportation Convenience in Beijing:Users' Perception versus Objective Measurements.- 11. Object-oriented Data Modeling of an Indoor/outdoor Urban Transportation Network and Route Planning Analysis.- V. Analyzing and Modeling Urban Grown, Urban Changes and Impacts: 12. Integration of Remote Sensing with GIS for Urban Growth Characterization.- 13. Evaluating the Ecological and Environmental Impact of Urbanization in the Greater Toronto Area through Multi-Temporal Remotely Sensed Data and Landscape Ecological Measures.- 14. Modeling Urban Effects on the Precipitation Component of the Water Cycle.- 15. Interpolating a Consumption Variable for Scaling and Generalizing Potential Population Pressure on Urbanizing Natural Areas.- 16. Modeling Cities as Spatio-Temporal Places.- VI. Studying other Urban Problems Using Geospatial Analysis and Modeling: 17. Geospatial Analysis and Living Urban Geometry.- 18. Analyzing Spatial Patterns of Late-StageBreast Cancer in Chicago Region: A Modified Scale-Space Clustering Approach.- 19. Influence of Job Accessibility on Housing Market Processes: Study of spatial stationarity in the Buffalo and Seattle metropolitan areas.- 20. How do Socioeconomic Characteristics Interact with Equity and Efficiency Considerations? An Analysis of Hurricane Disaster Relief Goods Provision.- 21. Visualizing and Diagnosing Coefficients from Geographically Weighted Regression Models.- Epilog Michael F. Goodchild.- Index

A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century Forty years ago when spatial analysis first emerged as a distinct theme within geography's quantitative revolution, the focus was largely on consistent methods for measuring spatial correlation. The concept of spatial au- correlation took pride of place, mirroring concerns in time-series analysis about similar kinds of dependence known to distort the standard probability theory used to derive appropriate statistics. Early applications of spatial correlation tended to reflect geographical patterns expressed as points. The perspective taken on such analytical thinking was founded on induction, the search for pattern in data with a view to suggesting appropriate hypotheses which could subsequently be tested. In parallel but using very different techniques came the development of a more deductive style of analysis based on modelling and thence simulation. Here the focus was on translating prior theory into forms for generating testable predictions whose outcomes could be compared with observations about some system or phenomenon of interest. In the intervening years, spatial analysis has broadened to embrace both inductive and deductive approaches, often combining both in different mixes for the variety of problems to which it is now applied.