Intro to GIS Winter Data Visualization Part I
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1 Intro to GIS Winter 2011 Data Visualization Part I
2 Cartographer Code of Ethics Always have a straightforward agenda and have a defining purpose or goal for each map Always strive to know your audience Do not intentionally lie with data Always show all relevant data whenever possible Data should not be discarded simply because they are contrary to the position held by the cartographer At a given scale, strive for an accurate portrayal of the data The cartographer should avoid plagiarizing; report all data sources Symbolization should not be selected to bias the interpretation of the map The mapped result should be able to be repeated by other cartographers Attention should be given to differing cultural values and principles
3 UNDERSTANDING YOUR DATA
4 Qualitative Qualitative & Quantitative Data classified by category Soil types, animals by species Quantitative Data grouped by measurement or numerical value Population, % of forest cover Type of data will influence your choice of data symbolization/visualization
5 DATA ATTRIBUTE TYPES
6 Types of Attributes Ordinal Nominal Interval Ratio
7 Nominal Data identify one instance from another; establish the group, class, member, or category with which the object is associated; these values are qualities, not quantities
8 determine position show place, such as first, second, third, and so on, but they do not establish magnitude or relative proportions how much better, worse, healthier, and stronger cannot be demonstrated from ordinal numbers Ordinal (rank)
9 Ratio values derived relative to a fixed zero point on a linear calibrated scale examples of ratio measurements are age, distance, cost and elevation mathematical operations can be used on these values with predictable and meaningful results
10 Interval values on a linear calibrated scale but not relative to a true zero point in time or space time of day, years on a calendar, most temperature scales are all examples of interval measurements because there is no true zero point, relative comparisons can be made between the measurements, but ratio and proportion determination are not useful
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12 Types of Attributes The computer does not decide between the 4 attribute types (you do) Most mathematical operations work well on ratio Most mathematical operations work well on ratio values, but when interval, ordinal, or nominal values are multiplied or divided, the results are typically meaningless
13 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 Nominal Nominal Nominal Nominal - Unique values 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
14 Single Value Each geographic feature is represented by a single color
15 Unique Value Each geographic feature is represented by a different color
16 Unique Values Geographic features are grouped and each group is represented by a color
17 DIFFERENT TYPES OF MAPS
18 Why Maps? Spatial visualization, as opposed to charts, graphs, tables Communicate information to others Explore, query, and analyze information Used to generate hypotheses or questions Inform decision making Synthesize layers of information
19 COROPLETH MAPS & DATA CLASSIFICATION
20 Choropleth Maps Widely used mapping method Based on numeric attributes of non-overlapping areas Areas are shaded based on the value of the attribute spatially-sensitive values should be normalized Different classification methods influence data visualization
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22 Natural Breaks (Jenks) Quantile Equal Interval Defined Interval Standard Deviations Classification Methods
23 Classification Methods The purpose of classification Ease of reading & understanding the map Show info about an area that is not self evident Must decide method & number of classes More classes show complex patterns Less classes show distinct patterns
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25 Classes are based on natural groupings of data Statistical methods that Statistical methods that minimizes the sum of variance within each group Natural Breaks
26 Equal: Divided equally into a set number of intervals (user sets # of classes) Defined: Divided into classes based on a set interval range (user sets Interval range) Intervals
27 Each class contains (approx) the same number of features Best suited for data that is Best suited for data that is uniformly distributed; data that does not have a disproportionate number of features with similar values Quantile
28 Shows distance from the mean Places class breaks at Places class breaks at intervals (1/4, 1/5, or 1) based the standard deviation Standard Deviation
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30 Symbology Demo ArcMap
31 ISOLINE MAPS
32 Isoline Maps Used for continuous surfaces Lines joining points of equal value (usually generalized) Phenomena must vary smoothly across the map two types: isometric (measured values) isopleth (areal averages)
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35 CARTOGRAMS
36 Cartograms Distort area, shape or distance for a specific purpose Reveal or enhance patterns that might not be visually apparent on a normal map Sometimes used to promote legibility
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41 DENSITY MAPS
42 Density Maps Repeated, uniform symbols representing spatial distribution Purpose to identify dense vs. sparse distribution Do not show exact quantities; instead give an overall impression of distribution/density
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45 3D VISUALIZATION
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