Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000004716357 | Z699.5.C55 E96 2004 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
Geocomputation has come of age. The whirlwind of change experienced in Geographical Information Science (GIS) - developments in IT, and new data gathering and earth observing technologies - has taken GIS beyond mere data and towards its analysis, modeling, and use in problem solving. Geocomputation is now at the dynamic edge of this revolution. Bringing together the leading researchers in geocomputation, this volume provides an up-to-date overview of the development of new artificial intelligence principles and technologies (NN, CA, Multi-agent Systems and Evolutionary Algorithms) used for the analysis, development and evaluation of urban planning policies and programmes. Charting the new approaches to data-processing, the book provides pointers on how to harness these technologies, advancing the knowledge level of planning by multiplying the information capacity of GIS, and offering a new approach to territorial modeling and micro-scale descriptions of socio-economic, behavioural and micro-spatial theories of urban processes and land use change.
Author Notes
Lidia Diappi is a Professor in the Department of Architecture and Planning at the Polytechnic of Milan, Italy.
Table of Contents
| List of Figures | p. vii |
| List of Tables | p. ix |
| List of Contributors | p. xi |
| Foreword | p. xiii |
| 1 Introduction | p. 1 |
| Part I The Spatial Investigation Capabilities of Neural Networks | |
| 2 Neural Classifiers for Land Cover Recognition: Merging Radiometric and Ancillary Information | p. 11 |
| 3 Spatial Interaction Modelling: Neural Network Methods and Global Optimization | p. 45 |
| 4 Complexity in Sustainability: an Investigation of the Italian Urban System through Self-Reflexive Neural Networks | p. 63 |
| Part II Land use Dynamics Through Artificial Intelligence Tools | |
| 5 Knowledge Discovery and Data Mining to Investigate Urban and Territorial Evolution: Tools and Methodologies | p. 85 |
| 6 Learning about Land Use Change in Rome and in Pisa Urban Areas | p. 103 |
| 7 The Identification and Simulation of the Urban Spatio-temporal Dynamic. The Case Study of Rome | p. 121 |
| Appendix An Overview of SSI Handbook | p. 138 |
| 8 Land Use Dynamics: a Stochastic Forecasting Model Based on SOM Neural Nets Knowledge | p. 143 |
| Part III Multi-Agent Systems: Interactions Among Actors and Their Behaviours | |
| 9 Multi-agent Simulations for Traffic in Regional Planning | p. 171 |
| 10 Traffic-related Air Pollution in an Urban Environment: a KBDSS for Improving the Decisional Context | p. 195 |
| 11 The Chaotic Nature of Urban Neighbourhood Evolution | p. 211 |
| Index | p. 225 |
