1. Down in the Trenches Automating Label Placement in Dense Utility Maps Jill Phelps Kern

3. 3 Definition Literature review Research problem Approach and timeline The Map Label Placement Problem

4. 4 Problem Definition The Map Label Placement Problem Placing map feature labels legibly without overlap (features / other labels) maintaining visual association of labels with their features

5. 5 Densely Labeled Maps

6. 6

7. 7 Literature Review Themes Label Placement rules quality metrics algorithms

8. 8 Label Placement Rules Area features Point features Line features Label placement most difficult Label placement least constrained

9. 9 W i s s o t a R. Label Placement Rules Potomo Franklin County Davis County Lakeview Menemsha Lake Winnipesauke Potomo Lakeview Sources: Imhof (1962, 1975); Wood (2000)

10. 10 Label Placement Quality Metrics Aesthetics Label visibility Feature visibility Association R i v e r R i v e rR i v e r City ATown BTown ATown BTown Peak Based on Van Dijk et al. (1999)

11. 11 Label Placement Quality Metrics Aesthetics5 of 20 papers reviewed Label visibility20 Feature visibility10 Association11

12. 12 Automating Label Placement Area features Point features Line features Label placement most difficult Label placement least constrained Frequent research target for label placement automation

13. 13 Automating Label Placement Area features Point feature label placement Line features models algorithms

14. 14 Automated Point Feature Label Placement Models 1 3 2 4 Discrete label position priorities: Yoeli (1972) 65 8 7 Slider model: Van Kreveld et al. (1999) Continuous circumferential movement: Hirsch (1982), Kameda & Imai (2003)

15. 15 Automated Point Feature Label Placement Algorithms Local Search Global Optimization

16. 16 Automated Point Feature Label Placement Algorithms Local Search Rule-based exhaustive search Gradient descent Global Optimization Force-directed Simulated annealing

17. 17 Exhaustive Search Rule … Place labels according to rules until violation Backtrack and adjust to maximize number of labels placed x Local Search Algorithms

18. 18 Local Search Algorithms Develop initial label placement Compute overlap vectors to guide next movement Iterate From Hirsch (1982), p. 13 Gradient Descent

19. 19 Local Search Algorithms Develop initial label placement Compute overlap vectors to guide next movement Iterate Can cycle between local minima (a) and (b) without finding preferred placement (c) From Christensen et al. (1995), p. 213 (a) (b) (c) From Hirsch (1982), p. 13 Gradient Descent

20. 20 Automated Point Feature Label Placement Algorithms Local Search Rule-based exhaustive search Gradient descent Global Optimization Force-directed Simulated annealing

21. 21 From Stadler et al. (2006), p. 211 Global Optimization Algorithms Force-Directed

22. 22 Global Optimization Algorithms Based on Zoraster (1997) and Christensen et al. (1995) Simulated Annealing

23. 23 Automated Label Placement Software Yoeli priorities Slider models Simulated annealing Iteration and backtracking Optimization Imhof (and others’) labeling rules Force-directed methods Label / feature visibility Association Aesthetics 9.2

24. 24 Project Objectives Evaluate the automated labeling capabilities of current GIS software when applied to dense maps Identify factors which necessitate manual label placement

25. 25 Project Context Town of Concord Sewer Map Book

26. 26 Point feature: Sewer manhole Attributes: Facility ID, station number, rim elevation, invert elevation Sewer Infrastructure Features

27. 27 Sewer Infrastructure Features Line feature: Sewer main Attributes: Size, material (VCP = vitreous clay pipe)

28. 28 Line feature: Sewer main Attributes: Slope and slope direction Sewer Infrastructure Features

29. 29 Line feature:Sewer tie Attribute: Service number Sewer Infrastructure Features

30. 30 Sewer Labeling Quality Metrics A.Number of Labels Placed Total and % of ideal Minimal leader length Importance: Critical – Major – Minor C. No Overlap Label-label Label-sewer tie B. Labels in Preferred Position Point (manhole) Line (sewer mains & ties) Area (streets)

31. 31 Sewer Labeling Quality Metrics A.Number of Labels Placed Total and % of ideal Minimal leader length Importance: Critical – Major – Minor C. No Overlap Label-label Label-sewer tie B. Labels in Preferred Position Point (manhole) Line (sewer mains & ties) Area (streets)

32. 32 Sewer Labeling Quality Metrics A.Number of Labels Placed Total and % of ideal Minimal leader length Importance: Critical – Major – Minor C. No Overlap Label-label Label-sewer tie B. Labels in Preferred Position Point (manhole) Line (sewer mains & ties) Area (streets)

33. 33 Approach and Timeline 1. Prepare for research (Dec – Feb) 2. Conduct research (Mar – May) 3. Develop conclusions (Jun – Jul) 4. Present findings (Aug – Oct)

34. 34 1. Prepare for Research Conduct literature review - COMPLETE Select case study maps - COMPLETE Design label classes, styles and hierarchy / weighting - COMPLETE Develop label placement quality metrics - COMPLETE

35. 35 Research Preparation

36. 36 2. Conduct Research A. Automated Labeling Apply automated ESRI labeling tools to case study maps Standard labeling engine Maplex Measure quality of automated results Iterate to improve quality using automated tools Select highest quality result (standard vs. Maplex) for remaining steps

37. 37 2. Conduct Research B. Manual labeling Complete manual adjustments Measure quality of manual results Compare quality of final automated vs manual

38. 38 3. Develop Conclusions Strengths and limitations of current automated labeling tools Conditions under which manual placement becomes preferable Research limitations and potential for future study

39. 39 4. Present Findings Prepare for conference presentation Present at NACIS 2007 conference

40. 40 Preliminary Findings Standard Labeling EngineMaplex PoorAcceptableIdeal

41. 41 Questions?

42. 42 References Christensen, Jon, Joe Marks, and Stuart Shieber. 1994. Placing text labels on maps and diagrams. Graphics Gems IV, Cambridge MA: Academic Press, 497-504. Christensen, Jon, Joe Marks, and Stuart Shieber. 1995. An empirical study of algorithms for point-feature label placement. ACM Transactions on Graphics (14)3: 203-232. Cook, Anthony C. and Christopher B. Jones. 1990. A Prolog interface to a cartographic database for name placement. In Proceedings of the International Symposium on Spatial Data Handling, International Geographical Union and International Cartographic Association, pp. 701-710. Doerschler, Jeffrey S. and Herbert Freeman. 1992. A rule-based system for dense-map name placement. Communications of the ACM (35)1: 68- 79. Ebner, Dietmar, Gunner W. Klau and Rene Weiskirscher. 2003. Force-based label number maximization. Technical Report TR 186-1-03-02, Vienna: Vienna University of Technology. Edmondson, Shawn, Jon Christensen, Joe Marks, and Stuart M. Shieber. 1996. A general cartographic labeling algorithm. Cartographica (33)4: 13-23. Freeman, Herbert and John Ahn. 1984. AUTONAP – an expert system for automatic name placement. Proceedings of the International Symposium on Spatial Data Handling, International Geographical Union and International Cartographic Association, pp. 544-569. Freeman, Herbert and John Ahn. 1987. On the problem of placing names in a geographic map. International Journal of Pattern Recognition and Artificial Intelligence 1(1): 121-140. Hirsch, Steven A. 1982. An algorithm for automatic name placement around point data. The American Cartographer 9(1): 5-17. Imhof, Eduard. 1962. Die Anordnung der Namen in der Karte [Positioning names on maps]. Internationales Jahrbuch fur Kartographie, vol. 2, Verlagsgruppe Bertelsmann GmbH/Kartographisches Institut Bertelsman, pp. 93-129. Imhof, Eduard. 1975. Positioning names on maps. The American Cartographer 2(2): 128-144. Jones, Christopher B. 1989. Cartographic name placement with Prolog. IEEE Computer Graphics and Applications 9(5): 36-47. Kameda, Takayuki, and Keiko Imai. 2003. Map label placement for points and curves. IEICE Transaction Fundamentals E86-A(4): 835-840. Stadler, Georg, Tibor Steiner and Jurgen Beiglbock. 2006. A practical map labeling algorithm utilizing morphological image processing and force- directed methods. Cartography and Geographic Information Science 33(3): 207-215. Van Dijk, S., M. Van Krefeld, Tycho Strijk, and Alecander Wolff. 1999. Towards an evaluation of quality for label placement methods. Proceedings of the 19th International Cartographic Conference and 11th General Assembly, ed. by C. P. Keller, Ottawa, Ontario, pp. 57-64. Van Kreveld, M., Tycho Trijk and Alexander Wolff. 1999. Point labeling with sliding labels. Computational Geometry 13: pp. 21-47. Wood, Clifford H. 2000. Descriptive and illustrated guide for type placement in small scale maps. The Cartographic Journal 37(1): 5-18. Yoeli, P. 1972. The logic of automated map lettering. The Cartographic Journal 9(2): 99-108. Zoraster, Steven. 1997. Practical results using simulated annealing for point feature label placement. Cartography and Geographic Information Science 24(4): 228-238.