Vector GIS. GIS 2 Graphic Features on the World Copyright – Kristen S. Kurland, Carnegie Mellon University.

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Presentation transcript:

Vector GIS

GIS 2 Graphic Features on the World Copyright – Kristen S. Kurland, Carnegie Mellon University

GIS 3 GIS Map Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 4 Vector GIS Point Line Polygon Lines Polygons Points Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 5 Points Data Attached to Points Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 6 Points Burglaries Drug Calls Same data displayed as two different points Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 7 Queries and Restrictions Restricts the features to a specific subset Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 8 Lines Roads Conditions, Major Streets Curbs Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 9 Vector GIS Point Line Polygon Polygons Residential vs Commerical Land Uses Copyright– Kristen S. Kurland, Carnegie Mellon University

Graphic Elements

GIS 11 Jacques Bertin Visualization Information “What should be printed to facilitate “communication”, that is, to tell others what we know without a loss of information” -Jacques Bertin, Paris, February 1983 Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 12 Bertin’s Graphic Variables Saturation Value Hue More Value Shape Texture Size Orientation Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 13 Saturation Value Hue More ValueTexture Orientation Size Shape Point Symbols Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 14 Use Solid Point Markers Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 15 Use Three to Seven Categories Max. Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 16 Saturation Value Hue More Value Shape Texture Size Orientation Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 17 Saturation Value Hue More Value Shape Orientation Size Texture Polygon Symbols Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 18 Texture Black and White Prints Polygons Large Areas Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 19 Texture Brings object to the front (figure) long wavelength hues coarse texture Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 20 Saturation Value Hue More Value Shape Texture Orientation Size >9 Size – Point Symbols Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 21 Size Graduated Symbols Show Size or Amount Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 22 Shape Texture Orientation Size Saturation Hue More Value Value Values Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 23 Values Increase/Decrease Contrast The greater the difference in value between an object and its background, the greater the contrast. Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 24 Values By creating a pattern of dark to light values, even when the objects are equal in shape and size, it leads the eye in the direction of dark to light Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 25 Values Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 26 Shape Texture Orientation Size Saturation Value More Value Hue Color Hues Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 27 Shape Texture Orientation Size Saturation Value Hue More Value Color Values Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 28 Shape Texture Orientation Size Value Hue More ValueSaturation Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 29 Saturation You can change the saturation of a hue by adding black (shadow) or white (light). The amount of saturation gives us our shades and tints. Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 30 Saturation Customize the Properties…of a layer Copyright– Kristen S. Kurland, Carnegie Mellon University

Color

GIS 32 Color Hues and Values Each of individual color is a hue Colors have meaning (i.e. cool colors, warm colors, political meanings) - Cool colors calming -Warm colors exciting - Cool colors appear smaller than warm colors and they visually recede on the page so red can visually overpower and stand out over blue even if used in equal amounts. Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 33 Color Wheel red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 34 Color Wheel Harmony two adjacent hues red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 35 Color Wheel Harmony two adjacent hues red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 36 Color Wheel Harmony two adjacent hues red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 37 Color Wheel Harmony two adjacent hues Contrast two hues with one hue skipped in between red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 38 Color Wheel Harmony two adjacent hues Contrast two hues with one hue skipped in between red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 39 Color Wheel Harmony two adjacent hues Contrast two hues with one hue skipped in between red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 40 Color Wheel Harmony two adjacent hues Contrast two hues with one hue skipped in between red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 41 Non-Contrasting vs. Contrasting Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 42 Color Wheel Harmony two adjacent hues Contrast two hues with one hue skipped in between Clash Opposites red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 43 Color Wheel Review Harmony two adjacent hues Contrast two hues with one hue skipped in between Clash Opposites red violet blue orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 44 Double-Ended Scales Extremes Emphasized critical value of zero e.g., regression residuals, time change blue and red contrast white center is ground -4 to to 2 <-4 2 to 4 <=4 red blue white Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 45 Change Map Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 46 Double-Ended Scales Balance Emphasized 50% is desired yellow contrasts with white paper green and orange contrast % 40-60% 0-20% 60-80% 20-40% orange yellow green Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 47 Color Spot White background allows yellow color spot to be visualized Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 48 Color Spot Ramps Copyright– Kristen S. Kurland, Carnegie Mellon University

Graphical Hierarchy

GIS 50 Graphical Hierarchy Goal direct attention toward or away from available Information Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 51 Graphical Hierarchy Goal direct attention toward or away from available Information Figure-Ground visual separation of a scene into recognizable figures and inconspicuous background (ground) Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 52 Graphical Hierarchy Ground larger of two contrasting areas Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 53 Graphical Hierarchy Ground larger of two contrasting areas grays, light browns, heavily saturated hues Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 54 Graphical Hierarchy Ground larger of two contrasting areas grays, light browns, heavily saturated hues Figure long wavelength hues coarse texture Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 55 Graphical Hierarchy Ground larger of two contrasting areas grays, light browns, heavily saturated hues Figure long wavelength hues coarse texture strong edge Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 56 Crimes in Pittsburgh, 2004

GIS 57 Crimes in Pittsburgh, 2004

Choropleth Maps

GIS 59 Choropleth Maps Map using different colors or patterns to show different values over space Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 60 Classifications Process of placing data into groups that have a similar characteristic or value Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 61 Natural Breaks Classes are based on natural groupings inherent in the data. Looks for where there are big jumps in data Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 62 Quantiles Each class contains an equal number of features Good for linearly distributed data Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 63 Equal Interval Divides the range of attribute values into equal-sized Subranges (e.g. 0–100, 101–200, and 201–300) Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 64 Standard Deviation Calculates the mean of the data distribution and then maps one or two standard deviations above or below the mean Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 65 Custom Scales Know your data! Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 66 Custom Scales Edit the legend Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 67 Custom Scales Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 68 Custom Scales Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 69 Normalizing Data Divides one numeric attribute by another in order to minimize differences in values based on the size of areas or number of features in each area Examples: Dividing the 18- to 30-year-old population by the total population yields the percentage of people aged 18–30 Dividing a value by the area of the feature yields a value per unit area, or density Copyright– Kristen S. Kurland, Carnegie Mellon University

Map Layers, Scale Thresholds, and Hyperlinks

GIS 71 Map Layers Organizes your layers Group logically and rename Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 72 Scale Thresholds Minimum Scale Range - If you zoom out beyond this scale, the layer will not be visible Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 73 Scale Thresholds When you zoom in, the layers are visible Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 74 Scale Thresholds Maximum Scale Range - If you zoom in beyond this scale, the layer will not be visible - State Capitals not visible at this scale Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 75 Hyperlinks Accesses images, documents, WEB pages, etc. via features on a map Copyright– Kristen S. Kurland, Carnegie Mellon University

GIS 76 Hyperlinks Link to images Copyright– Kristen S. Kurland, Carnegie Mellon University