Improving the representation of major landforms in analytical relief shading

Abstract

Relief shading is the most common type of cartographic relief representation for print and digital maps. Manual relief shading results in informative and visually pleasing representations of terrain, but it is time consuming and expensive to produce. Current analytical relief shading can be created quickly, but the resulting maps are not as aesthetically appealing and do not show landscape features in an explicit manner. This article introduces an automated digital method that produces shaded relief with locally adjusted illumination directions to simulate the techniques and cartographic principles of manual relief shading. Ridgelines and valley lines are derived from a digital terrain model, vectorized, and used in a diffusion curve algorithm. A graph analysis generalizes the lines before using them for diffusion curve shading. The direction of illumination is adjusted based on the spatial orientation of ridgelines and valley lines. The diffusion curve shading is combined with standard analytical relief shading to create a final diffusion relief shading image. Similar to manual relief shading, major landforms and the structure of the terrain are more clearly shown in the diffusion relief shading. The presented method best highlights major landforms in terrain characterized by sharp, clearly defined ridges and valleys.

Keywords:

• terrain mapping
• diffusion curves
• relief shading
• shaded relief
• hill shading
• Swiss-style
• diffusion relief shading

Acknowledgements

The authors would like to thank William McNulty of Google for his support and the following organizations for funding assistance: Google, Oregon State University, the Alpha Chapter of Phi Beta Kappa at the University of Colorado at Boulder, the Association of American Geographers Cartography Specialty Group, and the International Cartographic Association Commission on Mountain Cartography. The authors would also like to thank Tom Patterson at the National Park Service for his valuable insight and assistance in this research.