Terrain generalization with line integral convolution

ABSTRACT

Line integral convolution is a technique originally developed for visualizing vector fields, such as wind or water directions, that places densely packed lines following the direction of movement. Geisthövel and Hurni adapted line integral convolution to terrain generalization in 2018. Their method successfully removes details and retains sharp mountain ridges; it is particularly suited for creating generalized shaded relief. This paper extends line integral convolution generalization with a series of enhancements to reduce spurious artifacts, accentuate mountain ridges, control the level of detail in mountain slopes, and preserve sharp transitions to flat areas. The enhanced line integral convolution generalization effectively removes excessive terrain details without changing the position of terrain features. Sharp mountain ridgelines are accentuated, and transitions to flat waterbodies and valley bottoms are preserved. Shaded relief imagery derived from generalized elevation models is visually pleasing and resembles manually produced shaded relief.

KEYWORDS:

• Terrain generalization
• line integral convolution
• shaded relief
• curvature-adaptive Gaussian blurring

Acknowledgments

The author would like to thank Tom Patterson (U.S. National Park Service, ret.) for providing feedback on this manuscript and the developed generalization methods, Paulo Raposo, (University of Twente) for providing details on his adaptive entropy filter, Jane Darbyshire (Esri Inc.) for copy editing this manuscript, the anonymous reviewers for their valuable comments, as well as the following experts for participating in the study to evaluate generalization methods: Roman Geisthövel, Jürg Gilgen and Anna Leonowicz (all with swisstopo), Lorenz Hurni, Marianna Farmakis-Serebryakova, Stefan Räber and Christian Häberling (all with ETH Zurich), Alex Tait (National Geographic Society), Tom Patterson and Jim Eynard (both with the U.S. National Park Service), Robert Weibel (University of Zurich), David Imus (Imus Geographics), Markus Hauser (Orell Füssli Kartographie AG), Patrick Kennelly (Central Oregon Community College), Timofey Samsonov (Lomonosov Moscow State University), Paulo Raposo (University of Twente), and Brooke Marston.

Data availability statement

Digital elevation models and shaded relief images used for the evaluation with experts (Figures 7 and 8), as well as anonymised pair-wise rankings by experts are openly available in a Zenodo repository at Jenny (2020) “Terrain Generalization with Line Integral Convolution”, https://doi.org/10.5281/zenodo.4050768.

Disclosure statement

No potential conflict of interest was reported by the author.