Geographical information systems (GISs) are capable of simulating a geography-based approach to problem solving. This approach is applicable in many areas including commerce, industry, and everyday life. One problem with geographical data is that it stems from different sources. In turn, this often results in data that is imprecise, uncertain, incomplete, qualitative and difficult to combine with quantitative information in an existing GIS. To get rid of this uncertainty, techniques taken from various industries have been developed in an effort to standardise geographical information. The REVIGIS project aimed at discovering new theories and tools which can help increase the accuracy of uncertain geographical information. Using fuzzy logic, that is approximate rather than precise reasoning, the project research employed a fusion of various formal techniques in order to handle spatial data uncertainty. This was applied to map products which all represent a part of the real world. Despite this, they also vary greatly in terms of their particular purpose and set of specifications. For example a geological map has a very different purpose from a topographical map. What's more, only a small part of the available detail is transferred into metadata even though more areas of specification exist. The aim was to consider all the specifications in their entirety and create a logical adaptation based on that. This allows the data to be checked as to whether or not a logically proven model for the particular specifications exists and allows the specifications to evolve on a continual basis. The regular fusion of external data is also possible. This approach is of particular importance to mapping agencies, map data providers and logic programmers.
Uncertain Knowledge Maintenance and Revision in Geographic Information Systems
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28 September 2016
24 January 2020