Texture Synthesis & Pseudo-natural Maps

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A pseudo-natural map with texture, orthoimagery and shading effects (left) compared to a traditional vector map (right, OSM).

Pseudo-natural maps (also called natural-color maps) are topographic maps with a particularly vivid and comprehensible symbolization, uniting cartographic abstraction with natural appearance. Traditionally, this style can be found in manually created natural color relief representations and hand-painted landscape panoramas. The goal of this research is to formalize and extend these manual techniques in the form of computer graphics algorithms. The aim is to develop a more engaging and expressive map style that web mapping services can offer in addition to their traditional vector and satellite mapping modes.

Researcher: Jane Darbyshire
The goal of this project is to develop automatic and semi-automatic methods to create maps and other visualizations with pseudo-natural appearance.

Pseudo-natural maps have a long tradition in manual cartography in 2D and 3D, for example, as natural-color reliefs, winter maps and hand-painted panoramas. Such manual map creation is very time intensive and requires significant artistic talent. In digitally cartography, pseudo-natural map appearance is very rare, as specialized software for their creation is not available to cartographers.

Software will be developed to render pseudo-natural visualizations at various scales from OpenStreetMap data. The symbolization will be continuously adapted to local vegetation and climate zone.

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Grimsel, Christian Kägi

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Newport (Oregon) by Jacob Wasilkowski, Clark University, 2012

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Rome (Oregon) by Jacob Wasilkowski, Clark University, 2012


Jenny, H. and Jenny, B. (2013)
Challenges in adapting example-based texture synthesis for panoramic map creation: a case study.
Cartography and Geographic Information Science, 40-4, p. 297–304.

Jenny, H., Jenny, B. and Cron, J. (2012).
Exploring transition textures for pseudo-natural maps.
In: Jekel, T., Car, A., Strobl, J. and Griesebner, G. (eds), GI_Forum 2012: Geovisualization, Society and Learning, Berlin: Wichmann, p. 130–139.