Fundamentals of Spatial Data Quality [Hardcover]

This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context. Drawing together chapters written by authors who are specialists in their particular field, it provides both the data producer and the data user perspectives on how to evaluate the quality of vector or raster data which are both produced and used. It also covers the key concepts in this field, such as: how to describe the quality of vector or raster data; how to enhance this quality; how to evaluate and document it, using methods such as metadata; how to communicate it to users; and how to relate it with the decision-making process. Also included is a Foreword written by Professor Michael F. Goodchild.Foreword.

Introduction.

Chapter 1. Development in the Treatment of Spatial Data Quality (Nicholas Chrisman).

Chapter 2. Spatial Data Quality: Concepts (Rodolphe Devillers and Robert Jeansoulin).

Chapter 3. Approaches to Uncertainty in Spatial Data (Peter Fisher, Alexis Comber and Richard Wadsworth).

Chapter 4. Quality of Raster Data (Serge Riazanoff and Richard Santer).

Chapter 5. Understanding the Nature and Magnitude of Uncertainty in Geopolitical and Interpretative Choropleth Maps (Kim Lowell).

Chapter 6. The Impact of Positional Accuracy on the Computation of Cost Functions (Alfred Stein and Pepijn Van Oort).

Chapter 7. Reasoning Methods for Handling Uncertain Information in Land Cover Mapping (Alexis Comber, Richard Wadsworth and Peter Fisher).

Chapter 8. Vector Data Quality: A Data Provider’s Perspective (Jenny Harding).

Chapter 9. Spatial Integrity Constraints: A Tool for Improving the Internal Quality of Spatial Data (Sylvain Vallières, Jean Brodeur and Daniel Pilon).

Chapter 10. Quality Components, Slsè