The scale of a map is defined as the ratio of a distance on the map to the corresponding distance on the ground. Humans have been using the concept of map scale since the early days. When moving to a digital environment, the old map scale concept is maintained and for each different scale the whole data of a map are separately produced and stored. This is a labor intensive and expensive process and in practice results in inconsistencies. We propose a new concept named "vario-scale" where the data once stored in a vario-scale data structure can be used for generating all wanted scales in a smooth digital way.
There are already map user interfaces providing the feeling of vario-scale by supporting smooth zoom; e.g. Google Maps and/or Microsoft Bing Maps. However, this is just an illusion as the solution behind the "curtains" is still based on a number of redundant and fixed map scale representations. The central question that drives the research is:
How can we realize a paradigm shift towards dynamic vario-scale geo-information with minimal redundancy, supporting delivery of representations at arbitrary scale for different user contexts and progressive transfer for the delivery of refinements?
The start of the research is the vario-scale data structure called tGAP (topological Generalized Area Partition), of which recently we have implemented a static version for the first time ever. However, important aspects of the vario-scale theory (and tGAP structure) are still missing, such as formalization of the data structure, support for point and line objects (besides area objects), more thematic support (via semantic web technology), better cartographic generalization quality, ability to handle massive data sets (over 100 million features) and support for dynamic updates. We propose to study existing solutions, design and engineer new solutions, and run experiments and tests on created prototypes. Solutions will be investigated by also exploiting the expertise of the international (generalization research) network of the team members, such as ICA, EuroSDR and via involvement in European activities (INSPIRE).
This research is financially supported by the Dutch Technology Foundation STW, which is part of the Netherlands Organisation for Scientific Researsch (NWO) and which is partly funded by the Ministry of Economic Affairs (project code 11185).