May 6 – 11 , 2001, Dagstuhl Seminar 01191

Computational Cartography and Spatial Modelling


Marc van Kreveld (Utrecht University, NL)
Robert Weibel (Universität Zürich, CH)
Michael Worboys (University of Maine, US)

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List of Participants
Dagstuhl-Seminar-Report 305


This seminar aims to bring together researchers from the areas of computational geometry, automated cartography, geographic information systems (GIS) and spatial analysis, and practitioners from institutions and industries that deal with spatial information and GIS. After two successful interdisciplinary meetings where cartographers and computational geometers exchanged ideas on automated cartography and algorithms, this third seminar should provide new links between computer science and the spatial sciences (cartography, geography, surveying, etc.).

Two of the most important capabilities of GIS are the visualization of geographical data through maps, and the modeling and quantitative analysis of spatial data. This seminar will focus on both issues. Since cartographic visualization generally concerns large quantities of data, efficient algorithms for handling the data are essential. Similarly, for spatial modeling and analysis, models and tools that allow efficient representation and analysis operations are needed. This is particularly critical in the context of spatial decision making systems, where efficiency is key to supporting an exploratory and highly interactive workstyle.

Main topics are:

  • Cartographic methods: automated map labeling and automated map generalization remain crucial issues both in research and software for automated cartography.
  • Interactive, dynamic, and animated maps: these provide important new visualization possibilities for spatial data, particularly in the context of exploratory visualization systems and the Internet.
  • Spatial data analysis: combination of themes through overlay or spatial statistics, spatial interpolation methods, and terrain modeling, shape analysis, and visualization. Also, multi-scale issues.
  • Spatio-temporal data modeling: the use of fundamental geometric concepts and structures to assist modeling (alpha shapes, Voronoi diagrams, clustering), and data structures for the representation of spatio-temporal data models.
  • Spatio-temporal data analysis: methods and algorithms for change detection, clustering in space and time, correlation in space and time, and simulation of spatial processes.

The technological advances of the recent past -- steadily increasing graphics capabilities, multimedia technology, distributed computing and the Internet, to name just a few -- have lead to increased possibilities of visualization and maps in the spatial sciences. Cartographic products are seen not only in conjunction with GIS, but also in everyday life applications, such as access to indicator and locator maps via the Internet (so-called Internet map servers). Despite the growing importance of such cartographic products, however, the further spread of maps is impeded by the fact that digital products in most cases still cannot be produced automatically with high cartographic quality, and/or in a sufficiently efficient manner, largely for lack of suitable algorithms.

In the spatial modeling and analysis domain, the field is lacking an integrated approach to deal with space, time, attributes and their interrelations. Multi-scale issues complicate matters even more, because certain patterns or processes only show up or play a role at specific scales. Most studies so far have concentrated on two of the issues space, time, attribute, and scale simultaneously. Models that exists in such situations require analysis algorithms to detect patterns, clusters or processes. When more issues are involved, models and representations of these models are needed to capture this in an appropriate manner.

The above main topics for the seminar have been selected because they provide areas where spatial scientists and computer scientists have shared interests and the combined knowledge can help advance the issues in the automation of cartography, spatial modeling, and analysis. They provide cartographic functionality to users of GIS as well as to users of other systems working with spatial data. Common to all of the aforementioned problems is that they are complex, resisting a straightforward formalization. To address them fundamentally, a collaborative effort from an interdisciplinary community is needed which consists of cartographers, spatial scientists, algorithms researchers, and GIS specialists.

In the previous seminar of this type, which focused mainly on the cartographic issues, industry participation proved to be valuable to the insights and requirements of practice. In this seminar, companies that are more focused on spatial modeling and analysis will be represented as well.

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