1. Making Effective Maps Efficiently AIM: make the appropriate number of maps swiftly, without multiple revisions, that communicates to the intended audiences so as to accomplish our goals

2. ArcViews power paradoxically can limit efficient map production: § offers many options § doesnt help people make design choices § as computer-based tool, encourages managers to expect easy, multiple revisions § thus mapmakers rarely take time to consider communication effectiveness of their maps, reducing chances of success

3. . what data to map. how many maps are needed to present the message(s) to audience(s) in what locations. who your audience(s) is (are). what your message(s) will be. where the map will be used (oral presentation; report; newspaper/TV) Decisions to Get Started

4. Who Your Audience is § your immediate superior § fellow program staff § other programs staff § senior managers (Management Team, etc.) § legislature/Governor § stakeholders (industry, environmentalists…) § general public (attentive; non-attentive)

5. Why Considering Audiences is Important Effective communication depends upon: (1) understanding what information your audience wants about the topic (2) understanding how your audience might interpret the information you want to give them (3) incorporating (1) and (2) into map design

6. § What the agency knows § What the agency does/will do § What reactions the audience might take § Reasons for agency/audience reaction What the Message Will Be

7. Where the Map Will Be Used § Affects the complexity of the message that can be conveyed. § Affects the ability to offer supplementary information. (e.g. text, graphics) § Affects text and symbol choices. § Affects color choices (beware of designing in color but printing in black & white)

8. What Data to Map § The most current data § The most accurate data § Data that pertains to area of interest § Data that is readily understood by intended audience.

9. How Many Maps are Needed § Complex maps, especially those with more than one message, are not easily understood. § If you make your audiences work too hard to interpret your map, they may be distracted from your message

10. § Map Type, Display Type § Data Type § Symbolization § Graphic Hierarchy § Geographic Frame of Reference § Color Audience-Message- Venue-Data Affects:

11. Choose the most appropriate one based on your message, data, audience and venue Map Types

12. Standard

13. Images

14. Choropleth Unique Value

15. Choropleth Graduated Color

16. Graduated Symbol

17. Chart

18. Dot Density

19. 3-D

20. Result of a T- test performed to identify areas of significant change in deer harvest. Statistical Analysis

21. DATA TYPES The most important factor in determining map type and symbols

22. Point Differences in Kind Qualitative Data

23. Polygon

24. Line

25. . Polygon Data - Absolute vs. Ratio. Point Data - Discrete vs. Continuous Differences in amounts and measures e.g. number of persons (absolute) e.g. population density (ratio) e.g. chemical releases at a site (discrete) e.g. rainfall (continuous). Line Data e.g. flow lines, thickness of line Quantitative Data

26. Discrete vs. Continuous DiscreteContinuous Point Data

27. Population Pop Den CorrectIncorrect Polygon Data – absolute & ratio

28. Incorrect Population - 1990

29. Correct Population Density

30. Correct Population

31. Line Data

32. SYMBOLIZATION The key to communicating to your audience

33. Qualitative Data Make symbols as intuitive as possible Use professional standards whenever possible Legends

34. Natural Breaks (default) Quantile Equal Area Equal Interval Standard Deviation Quantitative Data

35. . ArcViews default classification method.. Identifies break points by looking for groupings and patterns inherent in the data. Extreme values are obvious. Natural Breaks

36. Natural Breaks - example

37. . Each class is assigned the same number of features.. It doesnt matter if features on either side of a class boundary have almost the same values.. Best suited for a data set that does not have a large number of features with similar values. Quantile

38. Quantile - example

39. . Classifies polygon features by finding breakpoints in the attribute values so that the total area of the polygons in each class is approximately the same.. Polygons with the largest values tend to hide variation in population between geographically smaller areas. Equal Area

40. Equal Area - example

41. . The range of attribute values is divided into equal sized sub-ranges.. Useful when you want to emphasize the amount of an attribute value relative to another value. (e.g. If you want to show that a municipality is part of a group of municipalities that make up the bottom 20% for population density).. Not good if you want to reveal subtle differences between features with similar values. Equal Interval

42. Equal Interval - example

43. . Shows you the extent to which an attributes values differ from the mean of all the values.. ArcView first finds the mean value and then places the class breaks above and below the mean at 1,.5, or.25 standard deviations.. ArcView will aggregate any values beyond three standard deviations from the mean into two classes: >3 Std Dev and <3 Std Dev. Standard Deviation

44. Standard Deviation - example

45. Loading Legend Symbols

46. Loading legend symbols continued

47. Loading and Saving a Legend

48. Loading and Saving a Legend continued

50. Point symbols can be rotated to symbolize additional information about features. e.g. wind direction Rotating

51. Used when you have two features represented by one line. e.g. pipelines and roads are sometimes represented by the same line. Line offset will allow you to display both as two separate features. Line Offset

52. GRAPHIC HIERARCHY Message should be high in the hierarchy, supporting information should be low.

53. Foreground Objects that stand out from the background. Background Not immediately noticeable, but enhances map design and understanding. - Contrast - Geographic Frame of Reference - Color Foreground/Background

54. Aids the eye in discerning differences on a map. Lack of visual contrast makes it difficult to distinguish important from unimportant parts. Contrast

55. Contrast – bad example

56. Contrast – good example

57. GEOGRAPHIC FRAME OF REFERENCE Aids orientation, thus enhances understanding for the map reader

58. Geographic Frame of Reference Aids orientation, thus enhances understanding for the map reader

59. Without a frame of reference

60. With a frame of reference

61. COLOR The distinction between foreground and background can be enhanced by choosing colors with their advancing and retreating characteristics in mind

62. Advancing/Receding §Advance l Warm hues l High values l Bright Colors §Recede l Cool hues l Low values l Dull colors

63. Yellow BEST Black WhiteBlue BlackOrange BlackYellow OrangeBlack BlackWhite WhiteRed RedYellow GreenWhite OrangeWhite Red WORST Green Foreground & Background Color Combinations

64. More COLOR Issues

65. . Affects clarity and legibility.Generates different visual hierarchical levels in the map. Hue Physiographic Provinces The name given to the colors we perceive Color Dimensions

66. . The most pleasant combinations result from significant differences in lightness (value).. A foreground color must stand out from the background by being definitely lighter or darker. The quality of lightness or darkness of a color. Value

67. Value - example

68. . Popular foreground colors are those containing little gray.. But vivid colors combined with a grayish background can be very effective. Amount or saturation of pigment. 0 % gray - 100% maximum color. Saturation

69. Blue - Water, Cool temperature Red - Warm temperature, warning, danger Green - Lush, thick vegetation, safety Yellow/Tan - Dry, little vegetation, caution Brown - Land surfaces (e.g. uplands, contours) Red/Yellow/Green - danger/caution/safety Qualitative Conventions

70. Color Plan - The way a designer chooses to use the color dimensions of hue, value, and brightness to symbolize different amounts of data on a map. Three commonly used color plans are... Quantitative Conventions

71. Single Hue Plan

72. Double-ended plan

73. Full-spectral plan

74. . Effectiveness of the use of color on the map.. Appropriateness of the conventional uses of color on the map.. Overall appropriateness of color selection relative to map content.. Easily recognized link between legend and map. Color Harmony

75. Some colors will be different on a computer screen than in the final product. (HP Printer, TV, Slides etc.) Maps designed in color but printed in black and white may produce shades of gray that are hard to interpret. Design with blacks, whites, and grays and vary the texture or pattern. Design for Final Product

76. CHARTS

77. . Presents complex tabular information effectively. Provides an immediate impact and takes less effort to understand.. Complements map information. Shows the same information in a different way, or provides additional information about map features. Charts

78. Good for comparing values and showing trends Bar Chart

79. Good for comparing values and showing trends Column Chart

80. Good for showing the relative value for each category as well as the total. Area Chart

81. Combines features of both the bar and area charts Cumulative Bar Chart

82. Shows relationships between the parts and the whole, particularly useful for showing proportions and ratios. Pie Charts

83. Emphasizes rate of change. Particularly good for representing trends over a period of time. Line Charts

84. Reveals trends or patterns in the data. Can help reveal associations, sometimes cause-and-effect relationships. Scatter Charts

85. Map, Data, and Symbolization - affect the message of your map Message - affects your choice of map, data and symbols. Summary