Robert Jeansoulin

Fundamentals of Spatial Data Quality

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.

An application of problem and product ontologies for the revision of beach nourishments

An ontological approach in GIS serves as a framework for the conceptualization of processes in the real world. In this paper, we examine an application in coastal change in the Netherlands, whereby beaches are subject to artificial nourishment to offset the effect of severe erosion. The use of ontologies helps to define two scenarios: SI determined by the regulations from the Ministry for Public Works; SII grounded on the abilities from an existing spatial dataset. A comparison between SI and SII shows that 72.8% of the objects suitable and unsuitable for nourishment are correctly classified. A higher overlap is found in areas where actual beach nourishments were carried out. Inaccuracies in attributes influence the determination of the objects. A sensitivity analysis applied to altitude illustrates a significant increase of objects suitable for nourishment for both scenarios, when altitude is decreased within the lower limit of the root mean square error for the 95% confidence interval. Moreover, the sensitivity of altitude shows that artificial boundaries for beach nourishment objects are not reasonable and consequently should be treated as vague objects.

Spatial Information Revision: A Comparison between 3 Approaches

The present paper deals with spatial information revision in geographical information system (GIS). These systems use incomplete and uncertain information and inconsistency can result, therefore the definition of revision operations is required. Most of the proposed belief revision operations are characterized by a high complexity and since GIS use large amount of data, adjustments of existing strategies are necessary. Taking advantage of the specificity of spatial information allows to define heuristics which speed up the general algorithms. We illustrate some suitable adjustments on 3 approaches of revision: binary decision diagrams, preferred models and Reiters algorithm for diagnostic. We formally compare them and we experiment them on a real application. In order to deal with huge amount of data we propose a divide and revise strategy in the case where inconsistencies are local.