Modelling Scale In Geographical Information Science

Scale has long been a fundamental concept in geography. Its importance is emphasised in geographical information science (GIScience) where the computational domain necessitates the rigorous definition and handling of scale. Geographical information systems are now used in almost every walk of life, but scale is often handled poorly in such systems. Modelling Scale in Geographical Information Science is written by an international team of contributors drawn from both industry and academia, and considers models and methods of scaling spatial data in both human and physical systems.

Divided into three sections to give a balanced coverage of the key problems, tools and models associated with scale:
* Fractal Models
* The Modifiable Areal Unit Problem
* Changing the Scale of Measurement
This book is an essential read for all GIScience researchers, advanced students and practitioners who want to delve more deeply into the scale issues of the spatial data and spatial models that form the basis of their analyses.

List of Contributors.

Foreword (Michael Batty).

Preface.

INTRODUCTION.

Models of Scale and Scales of Modelling (Michael F. Goodchild).

PART 1: FRACTAL MODELS.

Fractal Characterization of Multitemporal Remote Sensing Data (Dale A. Quattrochi, et al.).

Fractals and Scale Dependencies in Topography (Nicholas J. Tate and Jo Wood).

Measuring the 'Urban':Measuring and Modelling a Regional Settlement Hierarchy (Victor Mesev and Paul A. Longley).

The Multifractal Structure of the Human Population Distribution (Iqbal Adjali and Stephen Appleby).

PART 2: THE MODIFIABLE AREAL UNIT PROBLEM.

Behaviour of Regression Models under Random Aggregation (Robin Flowerdew et al).

Using Local Census Data to Investigate Scale Effects (Mark Tranmer and David Steel).

Scale Issues and Geographically Weighted Regression (A. Stewart Fotheringham, et al.).

Zone Design as a Spatial Analysis Tool (Seraphim Alvanides, et al.).

PART 3: CHANGING THE SCALE OF MEASUREMENT.

Measuring Scale Effects caused by Map Generalization and the Importance of Displacement (Elsa M. Joao).

Modelling Wildlife Distribution from Multi-Scale Spatial Data with GIS (Richard J. Aspinall).

Determining the Spatial Scale of Variation in Environmental Properties using the Variogram (Margaret A. Oliver).

Scaling Up and Scaling Down: The Relevance of the Support Effect on Remote Sensing of Vegetation (Jennifer L. Dungan).

Geostatistical Regularization in Remote Sensing (Peter M. Atkinson).

CONCLUSION.

Five Key Recommendations for GI Science (Peter M. Atkinson and Nicholas J. Tate).

Index.