Kannich, Rosene
(2007)
Automated selection of topographic base information for thematic maps.
MSc(R) thesis, University of Glasgow.
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Abstract
Modern GIS are capable of producing well designed maps but offer little assistance to users with little cartographc knowledge. Maps which are produced by such users may have a lot of cartographic errors and be of poor design. Thus, it is very necessary to build cartographic knowledge into GIS to help users to make effective use of such programs and produce basic maps conforming to basic principles of design. One possible way of improving map design in GIS is to build cartographic knowledge into the system.
One particular area where such cartographic knowledge could be applied is in the selection of base (topographic) information for special topic maps. The selection will depend upon map topic, map purpose, map scale, and the amount of detail required for the particular map. A topographic database at 1:250 000 has been used to starting point for this study and the scale of output maps limited to the 1:250 000 to 1:1000 000 range. To build a knowledge base of map content, published maps have been examined, and two aspects have been considered: maps with the same topic at different scales; and maps at the same scale but with different topics. For further development to the knowledge base, a questionnaire has been sent to cartographers and expert map users to determine what they consider should be the map content for maps on a range of topics at several scales. An initial examination of the knowledge base produced from the survey of published mapping highlights some anomalies, but by using the knowledge of the cartographers and map users, the knowledge base is revised.
To apply this knowledge, a formula for selecting appropriate base information is tested and the results show that the approach does produce satisfactory results. It is suggested this is implemented within a GIS to allow users to focus on the analysis data, with maps produced having appropriate base information depending on the topic, scale and the required level of detail automatically.
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