GIS Tutorial 1. Lecture 2 Map design

Transcription

1 GIS Tutorial 1 Lecture 2 Map design

2 Outline Choropleth maps Colors Vector GIS display GIS queries Map layers and scale thresholds Hyperlinks and map tips 2

3 Lecture 2 CHOROPLETH MAPS

4 Choropleth maps Color-coded polygon maps Use monochromatic scales or saturated colors Represent numeric values (e.g. population, number of housing units, percentage of vacancies) 4

5 Choropleth map example Percentage of vacant housing units by county 5

6 Classifying data Process of placing data into groups (classes or bins) that have a similar characteristic or value Break points Breaks the total attribute range up into these intervals Keep the number of intervals as small as possible (5-7) Use a mathematical progression or formula instead of picking arbitrary values Break points 6

7 Classifications Natural breaks (Jenks) Picks breaks that best group similar values together naturally and maximizes the differences between classes Generally, there are relatively large jumps in value between classes and classes are uneven Based on a subjective decision and is the best choice for combining similar values Class ranges specific to the individual dataset, thus it is difficult to compare a map with another map 7

8 Classifications Quantiles Places the same number of data values in each class Will never have empty classes or classes with too few or too many values Attractive in that this method produces distinct map patterns Analysts use because they provide information about the shape of the distribution. Example: 0 25%, 25% 50%, 50% 75%,75% 100% 8

9 Classifications Equal intervals Divides a set of attribute values into groups that contain an equal range of values Best communicates with continuous set of data Easy to accomplish and read Not good for clustered data Produces map with many features in one or two classes and some classes with no features 9

10 Classifications Use mathematical formulas when possible. Exponential scales Popular method of increasing intervals Use break values that are powers such as 2 n or 3 n Generally start out with zero as an additional class if that value appears in your data Example: 0, 1 2, 3 4, 5 8, 9 16, and so forth 10

11 Classifications Use mathematical formulas when possible Increasing interval widths Long-tailed distributions Data distributions deviate from a bell-shaped curve and most often are skewed to the right with the right tail elongated Example: Keep doubling the interval of each category, 0 5, 5 15, 15 35, have interval widths of 5, 10, 20, and

12 Original map (natural breaks) U.S. population by state,

13 Equal interval scale Not good because too many values fall into low classes 13

14 Quantile scale Shows that an increasing width (geometric) scale is needed 14

15 Custom geometric scale Experiment with exponential scales with powers of 2 or 3. 15

16 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 number of vacant housing units by the total number of housing units yields the percentage of vacant units Dividing the population by area of the feature yields a population density 16

17 Nonnormalized data Number of vacant housing units by state,

18 Normalized data Percentage vacant housing units by state,

19 Nonnormalized data California population by county,

20 Normalized data California population density,

21 Lecture 2 COLORS 21

22 Color overview Hue is the basic color Value is the amount of white or black in the color Saturation refers to a color scale that ranges from a pure hue to gray or black 22

23 Color wheel Device that provides guidance in choosing colors Use opposite colors to differentiate graphic features Three or four colors equally spaced around the wheel are good choices for differentiating graphic features Use adjacent colors for harmony, such as blue, blue green, and green or red, red orange, and orange 23

24 Light vs. dark colors Light colors associated with low values Dark colors associated with high values Human eye is drawn to dark colors 24

25 Contrast The greater the difference in value between an object and its background, the greater the contrast 25

26 Monochromatic color scale Series of colors of the same hue with color value varied from low to high Common for choropleth maps The darker the color in a monochromatic scale, the more important the graphic feature Use more light shades of a hue than dark shades in monochromatic scales The human eye can better differentiate among light shades than dark shades 26

27 Monochromatic map Values too similar 27

28 Monochromatic map A better map, more contrast 28

29 Dichromatic color scale An exception to the typical monochromatic scale used in most choropleth maps Two monochromatic scales joined together with a low color value in the center, with color value increasing toward both ends Uses a natural middle point of a scale, such as 0 for some quantities (profits and losses, increases and decreases) 29

30 Dichromatic map Symmetric break points centered on 0 make it easy to interpret the map 30

31 Color tips Colors have meaning Political and cultural Cool colors Calming Appear smaller Recede Warm colors Exciting Overpower cool colors 31

32 Color tips Do not use all of the colors of the color spectrum, as seen from a prism or in a rainbow, for color coding If you have relatively few points in a point layer, or if a user will normally be zoomed in to view parts of your map, use size instead of color value to symbolize a numeric attribute 32

33 Color tips If you have many polygons to symbolize, it is better to use polygon centroid points with color rather than polygon choropleth maps. 33

34 Changing colors in ArcMap Choose color, more colors 34

35 Learn more about GIS colors Website Books Brewer, Cynthia A Designed Maps: A Sourcebook for GIS Users. Redlands: ESRI Press Brewer, Cynthia A Designing Better Maps: A Guide for GIS Users. Redlands: ESRI Press 35

36 Lecture 2 VECTOR GIS DISPLAY 36

37 Points, lines, polygons Point x,y coordinates Line starting and ending point and may have additional shape vertices (points) Polygon three or more lines joined to form a closed area 37

38 Feature attribute tables Store characteristics for vector features Layers can be displayed using attributes 38

39 Displaying points Single symbols All CAD calls 39

40 Displaying points Same features, different points Based on attributes 40

41 Displaying points Industry specific (e.g. crime analysis) Good for large scale (zoomed in) maps 41

42 Displaying points Industry specific (e.g. schools) Not good for multiple features at smaller scales Simple points better for analysis 42

43 Displaying points Quantities Use exaggerated sizes 43

44 Displaying lines For analytical maps, most lines are ground features and should be light shades (e.g. gray or light brown) 44

45 Displaying lines Consider using dashed lines to signify less important line features and solid lines for the important ones 45

46 Displaying polygons Consider using no outline or dark gray for boundaries of most polygons Dark gray makes the polygons prominent enough, but not so much that they compete for attention with more important graphic features 46

47 Displaying polygons Consider using texture for black and white copies 47

48 Graphic hierarchy Assign bright colors (red, orange, yellow, green, blue) to important graphic elements Features are known as figure All features in figure 48

49 Graphic hierarchy Assign drab colors to the graphic elements that provide orientation or context, especially shades of gray Features known as ground Circles in figure, squares and lines in ground 49 49

50 Graphic hierarchy Place a strong boundary, such as a heavy black line, around polygons that are important to increase figure Use a coarse, heavy cross-hatch or pattern to make some polygons important, placing them in figure 50

51 Graphic hierarchy example 51

52 Lecture 2 GIS QUERIES 52

53 GIS queries Powerful relationship between data table and vector-based graphics unique to GIS Records from a feature attribute table are selected by using query criteria Query will automatically highlight the corresponding graphic features 53

54 Simple attribute queries Simple query criterion <data attribute>< logical operator><value> NatureCode ='DRUGS' DATE >= ' ' % wild card % symbol stands for zero, one, or more characters of any kind NAME like ' BUR%' Selects any crime with names starting with the letters BUR, including burglaries (BUR), business burglaries(burbus), and residential burglaries (BURRES) 54

55 Simple attribute queries 55

56 Compound attribute queries Compound query criteria Combine two or more simple queries with the logical connectives AND or OR "NATURE_COD" = 'DRUGS' AND "DATE" > Selects records that satisfy both criteria simultaneously Result are drug crimes that were committed after August 1,

57 Compound attribute queries 57

58 Lecture 2 LAYER GROUPS, SCALE THRESHOLDS