Improving the Representation of Major Landforms in Analytical Relief Shading

Brooke Marston
Bernhard Jenny
Oregon State University
#nacis2015

Transcript

1. Improving the Representation of Major Landforms in Analytical Relief Shading Brooke Marston Bernhard Jenny NACIS Minneapolis October 14–17, 2015
2. Relief Shading Analytical Manual Source: shadedreliefarchive.com
3. Adjustment to Illumination Direction Global Local
4. Why is manual preferred? • Locally bright and dark slopes improve legibility • Easier and faster to interpret topography • Better for small-scale maps where contours degenerate Source: shadedreliefarchive.com
5. Why aren`t there more manually
6. Benefits of Automation • Faster production of shaded relief adhering to manual design principles • More aesthetically pleasing maps • Explicit terrain visualization • Improve quality of maps produced by non-professionals
7. Source: Orzan, A., et al., 2008. Diffusion Curves: A Vector Representation for Smooth-Shaded Images. ACM Transactions on Graphics (Proceedings of SIGGRAPH 2008), 27, Article 92:1–8. Diffusion Curves • Introduced by Orzan et al., 2008 • Create images with smooth color gradients using cubic Bézier splines with control points • Colors diffused independently on left and right sides of curves by linear interpolation
8. Ridgelines Valley lines Diffusion curve shading
9. Identifying valley lines
10. Identifying ridgelines
11. Terrain Tilting •  Wedge-shaped base with artificial elevation grade (γ) applied to terrain model 8 times (N, E, S, W, NE, NW, SE, SW) •  Ridgelines are filtered based on their stability
12. Extracting Skeletal Lines Flow accumulation Maximum branch length Ridgeline and valley line vectors
13. Illumination Adjustment
14. Illumination Adjustment
15. Aspect Simplification • Reduces variability of adjusted illumination directions • Results in more regular gray values along ridges and valleys Original Low tolerance High tolerance
16. Diffusion Curve Shading
17. Valley Floor Mask • Detected using seed fill algorithm • Visually connects adjacent mountain slopes Seed points Valley floor
18. Standard analytical shading Diffusion Relief Shading Diffusion curve shading Valley floor mask + +
19. Study Sites 1.  Alpine terrain 2.  Pre-alpine terrain 3.  Terrain with complex drainage network
20. 1. Alpine Terrain Analytical Diffusion relief shading DEM Source: Federal Office of Topography swisstopo
21. 1. Alpine Terrain Manual Diffusion relief shading DEM Source: Federal Office of Topography swisstopo
22. 2. Pre-alpine Terrain Analytical Diffusion relief shading DEM Source: Federal Office of Topography swisstopo
23. 3. Complex Drainage Network Analytical Diffusion relief shading DEM Source: USGS
24. Limitations • Runtime • Spatial extent of terrain model • Unwanted artifacts in valley floor mask
25. Conclusions • Diffusion curve shading enhanced analytical shading • Best results in terrain with sharp, clearly defined ridges and valleys • Tilting removes irrelevant or visually disturbing ridgelines • Our method presents alternative to other filter-based generalization approaches
26. Future Work • Incorporate colors modulated by elevation and exposure to illumination (Jenny and Hurni 2006) • Integrate software applications
27. Acknowledgments •  Tom Patterson, National Park Service •  OSU Cartography and Geovisualization Group •  Oregon State University, AAG Cartography Specialty Group, Google, ICA Commission on Mountain Cartography, Phi Beta Kappa
28. Thank you Questions?
29. Gray value = 255 × cos(α) Analytical Relief Shading Lambert Shading Algorithm
30. Why is manual preferred? • Locally bright and dark slopes improve legibility and aesthetic quality • Easier and faster for the user to interpret topography • Better for small-scale maps where contours degenerate Source: reliefshading.com, Google Maps
31. Why is manual preferred? • Better for small-scale maps where contours degenerate Source: shadedreliefarchive.com
32. Identifying ridgelines
33. Methods
34. Diffusion Relief Shading E. Imhof manual relief shading Reproduction using Diffusion Curves Source: library.ethz.ch
35. Graph-based Network Analysis • Series of vertices connected by edges • Generalizes line geometry and filters out short, unimportant ridgelines (a) Identify shortest leaf edge (b) Remove edge (c) Remove degree- two vertex (d) Connect remaining edges
36. Methods
37. Number of overlaps between maximum branch length grids Terrain Tilting (N, S, E, W) 1 2 3 4
38. Extracting Skeletal Lines 1. Grayscale 2. Binary and skeletonize 3. Tracing from branch points 4. Vectors
39. Methods
40. Illumination Adjustment (a) northeast (b) northwest (c) north-south Dst – β = 0 Dst – β = π/2 Dst Dst – β = 3π/4 Dst Dst Dst + Dmax Dst + D No adjustment
41. Skeletal Line Simplification • Line simplification algorithm simplifies diffusion curve geometry Original Simplified
42. Methods
43. Methods
44. Methods
45. Methods
46. Methods
47. Methods