Geographical Data Imperfection 2: Use Cases (Information Systems, Web and Pervasive Computing)

Geographical data often contains imperfections associated with insufficient precision, errors or incompleteness. If these imperfections are not identified, taken into account and controlled when using the data, the potential for errors may arise, leading to significant consequences with unforeseeable effects, particularly in a decisionmaking context. It is then necessary to characterize and model this imperfection, and take it into account throughout the process.

In the previous volume, we introduced different approaches for defining, representing and processing imperfections in geographic data. Volume 2 will now present a number of concrete applications in a variety of fields, demonstrating the practical application of the methodology to use cases such as agriculture, natural disaster management, mountain hazards, land management and assistance for the visually impaired.

François Pinet is a researcher at the French National Research Institute for Agriculture, Food and the Environment.

Mireille Batton-Hubert is a professor at the École Nationale Supérieure des Mines de Saint- Étienne, France.

Eric Desjardin is a lecturer at the University of Reims Champagne-Ardenne within the STIC Research Center (CReSTIC), France.