Lecture 2:

1. Lecture 2: Part 1. Understanding Spatial Data Structures Part 2. Legend editing & choropleth mapping Part 3. Map layouts

2. Part 2. Spatial Data StructuresBy Austin Troy & Brian Voigt

3. Spatial Data Model • Features • cartographic object • Entities • spatial location • non-spatial properties

5. Vector • Points (no dimensions) • Lines, or “arcs” (1 dimension) or • Areas, or “polygons” (2 or 3 dimensions)

6. Introduction to GIS Point layer Examples: Stream gauge / wave buoy, stoplight, survey location / respondent, residence / business, etc. X,Y coordinates 5 3 4 1 3 2 2 4 1 0 1 2 3 4 5

7. Introduction to GIS Line (Arc) layer • Points define lines (arcs) Arc • Feature is the ARC, not the line segments Line segment • Arcs meet at the nodes Vertex Node Image source: ESRI Arc Info electronic help

8. Introduction to GIS Line (Arc) layer • Each point has a unique location

9. Lines (Arcs) Points Introduction to GIS Polygon layer • In a polygon layer, lines (arcs) define areas • Closed region • Boundaries: line segments • Area of homogenous phenomena

10. Raster • Grids, or pixels • Cell size is constant • Area of each cell defines the resolution • Raster files store only one attribute, in the form of a “z” value, or grid code.

11. Raster and Vector representations of the same terrain Raster: great for surfaces Vector: limited with surfaces

12. Raster and Vector representations of the same land use:

13. Vector vs. Raster: bounding Raster: bad with bounding Vector: boundary precision

14. Vector vs. Raster: Sample points Cancer rates across space

15. Vector / Raster Representation Points

16. Vector / Raster RepresentationLines

17. Vector / Raster RepresentationPolygons

18. WHEN TO USE RASTER OR VECTOR???

19. Raster and Vector • Analytic advantage and disadvantages • Technical advantages and disadvantages • Specific Usages • Tossups

20. Part 2. Legend editing, choropleth mappingBy Austin Troy & Brian Voigt

21. Mapping Attribute Data Two basic approaches for visually displaying attribute data: • Quantities approach • Category approach

22. Mapping Attribute Data Quantity approach: applies to numeric >> ordinal Category approach: text values; order is irrelevant

23. Mapping Attribute Data Quantity approach, example: population

24. Mapping Attribute Data Category approach, example: vegetation type

25. Mapping Categories Examples: vegetation types, land use, soil types, geology types, forest types, party voting maps, land management agency, recategorizations of numeric data (“bad, good, best” or “low, medium, high’). Can you think of any others?

26. Mapping Categories • Access layer properties: • right-click layer in the TOC • double-click layer in TOC • Symbology tab >>> Categories >>> Unique values • Set Value Field to desired attribute • Click the Add All Valuesbutton

27. Mapping Categories

28. Mapping Categories Often categories must be aggregated and redefined: this land use map had over 110 categories that were condensed to 12

29. Grouping Categories In this case 1262, 1263, 1264, 1265, etc. refers to different subcategories of commercial land use Can then save symbology as .lyr or in .mxd

30. Quantity Mapping Also known as “choropleth mapping” • For points, lines and polygons: graduated color, or color ramping • For lines and points can also do graduated symbol

31. Graduated Color • Layer Properties >>> Symbology >>> Quantities >>> Graduated colors • Set the Value field to desired attribute • In this case we choosemedian house value • It automatically assigns five classes for the data

32. Graduated Color The map shows high value housing with dark colors and low value housing with light colors

33. Graduated Color Same map, but this time with 3 classes

34. Graduated Color …and with 15 classes

35. Graduated Color These are the class breaks (based on the distribution of the data) Classification interface Classification method (default= Jenks) small large

36. Graduated Color • Classification Method: Equal Interval • What kind of data does this work for?

37. Graduated Color Here’s what the same distribution looks like with only 5 equal intervals.

38. Graduated Color • Data representing # of vacant structures • Potential problem(s) with this method of classification

39. Graduated Color This map of vacant properties tells us almost nothing, because almost all the records fall into the first class

40. Graduated Color • Natural Breaks: Notice how there are now more classes on the left side, where most of the data are. • Minimize each class’s average deviation from the class mean, while maximizing each class’s deviation from the means of the other groups • Reduce the within class varianceand maximize the between class variance

41. Graduated Color This map of vacant properties, made with Natural Breaks, is more intelligible

42. Graduated Color Quantile method: sets the class boundaries so as to maximize the perceived variation in the map; equal number of data points in each class

43. Graduated Color Map of vacant properties using the Quantile classification method

44. Graduated Color Graduated color can also be applied to points. Here are houses display by sales price Equal interval Natural breaks

45. Graduated Symbol In this case housing price is expressed by symbol size

46. Graduated Symbol The same thing can also be done with lines—for instance, traffic volumes

47. Introduction to GIS Symbol Styles We can also choose to “match to symbols in a palette” and then apply the “transportation.style” palette to the FCC, or road category, attribute in our roads layer Choose your style palette here Must click here to match Results in this map

48. Symbol Styles

49. Introduction to GIS Symbol Styles One could also manually create symbol styles for each street type. Clicking on each symbol in either the TOC or properties windows brings up a manual symbol selector. You can assign a separate one to each category. Includes many classes of industry standard symbols

50. Introduction to GIS Symbol Styles There are also a huge variety of industry-specific point symbols that can be either assigned through matching symbols to a predefined style or manually assigning those symbols