Intro to GIS Summer 2012 Data Visualization

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1 Intro to GIS Summer 2012 Data Visualization

2 UNDERSTANDING YOUR MAP DATA

3 Qualitative vs. Quantitative Data Qualitative Data classified by category e.g. Soil types, Animal Species Quantitative Data grouped by numerical value e.g. Population (# of people), Forest cover (%) Why is understanding this so important? Data type will influence your choice of map symbolization and visualization

4

5 DATA ATTRIBUTE TYPES

6 What Types of Attributes can be shown on a map? Nominal Ordinal Interval Ratio (Cyclic)

7 Establish the group, class, member, or category with which an object is associated; or Identify one instance from another Qualitative, not quantitative data. Nominal Attributes

8

9 Ordinal (Ranked) Attributes Show place in a ranking, e.g. 1 st, 2 nd, 3 rd, etc. Better vs. worse, higher vs. lower, etc. Does not establish magnitude; cannot demonstrate how much better or worse, etc. Quantitative data

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11 Interval Attributes Numerical values derived from a linear calibrated scale There is no true zero point on the scale Appropriate for showing relative comparisons between measurements; mathematical operations on this kind of data will not have meaningful results e.g. Time of day, most temperature scales Quantitative data

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13 Ratio Attributes Numerical values derived from a linear calibrated scale Relative to a fixed zero point Mathematical operations can be used on these values with predictable and meaningful results Examples: Age, Distance, Cost, Elevation Quantitative data

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16 Which Attributes are in my Data? The software does not decide between nominal ordinal interval ratio data. Who does? That would be you The Cartographer

17 Displaying data attributes in ArcMap ArcMap Method Point Line Area Raster Feature (shows location) Nominal Ordinal Interval Cyclic Ratio Nominal Ordinal Interval Cyclic Ratio Nominal Ordinal Interval Cyclic Ratio Categories - Unique values Nominal Nominal Nominal Nominal Quantities -Graduated color -Graduated symbols -Proportional symbols Ordinal Interval Cyclic Ratio Ordinal Interval Cyclic Ratio Ordinal Interval Cyclic Ratio Ordinal Interval Cyclic Ratio Charts Ratio Ratio Ratio Multiple Ratio Ratio Ratio David Theobald

18 SHOWING QUALITATIVE DATA ON MAPS

19 Features (Showing Location) Each geographic feature is represented by a single color

20 Categories (Unique Values) Each geographic feature is represented by a different color

21 Categories (Unique Values Grouped) Geographic features are grouped and each group is represented by a color

22 SHOWING QUANTITATIVE DATA ON MAPS

23 Quantitative Map Types Choropleth (Classification) Isoline Cartogram Density New types of Visualization

24 CHOROPLETH MAPS & DATA CLASSIFICATION

25 Choropleth Maps Widely-used method for showing quantitative data Based on numeric attributes of non-overlapping areas Areas are shaded based on the value of the attribute Spatially-sensitive values should be normalized Convert raw count data to ratio (density); this is done by dividing raw data by another attribute (e.g. area) e.g. Raw count data: Total Population per County e.g. Density data: Population/mi 2 per County

26 How do these % values get grouped into classes?

27 Classification Methods Different ways to show how data is grouped into classes Classification goals: Make the map easy to read and understand Communicate info that is not self-evident about an area Cartographer must decide which method to use

28

29 Natural Breaks (Jenks) Method Classes are based on natural groupings of data Statistical method that minimizes the total variance within each group (i.e. similar things are put into the same group) Cartographer sets number of classes; ArcMap finds natural groupings

30 Quantile Method Each class contains (approx) the same # of features Best suited for data that is uniformly distributed; data that does not have a disproportionate number of features with similar values Cartographer sets number of classes; ArcMap assigns data to each class

31 Interval Methods Equal Intervals: Features are divided equally into a set number of intervals. Cartographer sets number of intervals (e.g. 3); ArcMap calculates interval range (e.g. 0-5, 6-10, etc.) and assigns data to each interval. Defined Intervals: Features are divided based on a set interval range. Cartographer sets intervals (e.g. 0-7, 7-9, 9-15); ArcMap assigns data to each interval.

32 Standard Deviation Method Shows distance from the data mean (average) Places class breaks at intervals (1/4, 1/5, or 1) away from mean, based on the type of standard deviation Cartographer sets type; ArcMap assigns data to intervals

33 Normal Distribution Curve

34 Which method(s) are appropriate for data values that naturally clump into different groups?

35 Which method(s) are appropriate for data that has uniformly distributed values?

36 Which method(s) are appropriate for data values that follows a normal distribution?

37 Classification Methods Natural groupings of features into classes Features classified by distance from mean Class values are equally spaced Same # of features in each class

38 Normalizing Data When geographic features vary in size, then data should be displayed as densities; i.e. Spatiallysensitive values should be normalized Raw count data converted to a ratio (density) Divide raw data by another attribute (e.g. area) Let s look at a visual example

39 If Raw count data is Total Population per State, then

40 The corresponding density is Population per mi 2 (by State)

41 ISOLINE MAPS

42 Isoline Maps Lines joining points of equal value (usually generalized) Used for continuous surfaces; phenomena must vary smoothly across the map Common example is contour lines but isolines can show other data besides elevation! Two types: Isometric (measured values) Isopleth (areal averages)

43 Example - Isometric map

44 Example - Isopleth map

45 CARTOGRAMS

46 Cartograms Distort area, shape or distance of map symbols for a specific purpose Reveal or enhance patterns that might not be visually apparent on a normal map Sometimes used to promote legibility

47

48 WorldMapper World Population Atlas

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50 DENSITY MAPS

51 Density Maps Uniform symbols repeated across map Exact quantities not shown Instead, goal is to give an overall impression of data distribution across an area (i.e. density) Distribution of symbols represents distribution of data

52

53

54 NEW TYPES OF VISUALIZATION

55 3D Visualization

56 3D Visualization

57 Temporal Visualization GAPMINDER WORLD Hans Rosling Statistics shown using Graphs & Maps

58 Interactive/Crowd-Sourced Visualizations TED Talk: Aaron Koblin Artfully visualizing our humanity

59 ADVANCED MAP DESIGN

60 Elements of Good Map Design If a map is Graphically balanced Easy to read Limits redundant or unnecessary information Then it will Communicate a strong visual message to audience Convey the intended information (i.e. function properly) Satisfy purpose of designer (or the client!)

61 Map Layout Map Elements Components of map layout Main Map Visual representation of data What is the main map called in ArcMap?

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63 Map Layout Visual Hierarchy how different elements are positioned on the map, e.g. Color contrast Line weights Amount of detail

64 Possible Improvements Class Discussion: How else would you improve the layout for this map?

65

66 Refining Map Layout

67 Poor Attention to Detail Good Attention to Detail

68 Choosing Appropriate Map Projections

69 Decorative Design Elements

70 Same Map Emphasizing important map content, not decorative elements

71 MAP DESIGN RESOURCES

72 Resources for Map Design General Resources Designing Better Maps, Cynthia Brewer How to Lie With Maps, Mark Monmonier Making Maps: A Visual Guide to Map Design for GIS, John Krygier How Maps Work: Representation, Visualization, and Design, Alan M. MacEachren The Power of Maps, Denis Wood Especially for Color Blindness vcgiblog.wordpress.com/2010/11/02/designing-maps-for-the-color-blind/ colororacle.org/ mappingcenter.esri.com/index.cfm?fa=arcgisresources.gateway#arcgisresourcescd freegeographytools.com/2008/evaluating-map-graphics-for-color-blind-viewers

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