1. ©2005 by Austin Troy. All rights reserved Lecture 5: Introduction to GIS Legend Visualization Lecture by Austin Troy, University of Vermont

2. ©2005 by Austin Troy. All rights reserved Visual Analysis The most intuitive form of vector analysis is visual analysis, where we code features with colors or symbols to deliver information Frequently, we code features by an attribute value and let the color or symbol express the attribute value Understanding legend editing and map classification is critical to making maps that effectively deliver information Introduction to GIS

3. ©2005 by Austin Troy. All rights reserved Mapping of Attribute Data In GIS, each feature can have a number of attributes attached to it (e.g. land parcel>> property ID, assessed value, square footage) We can map out these attribute values by their corresponding geography Two basic approaches for classifying the data: 1.Quantities approach 2.Category approach Introduction to GIS

4. ©2005 by Austin Troy. All rights reserved Mapping of Attribute Data Quantity approach: applies to numeric attributes that are ordinal (have order to them); this means one values is greater than or less than another; good for continuous data. Category approach: applies to categorical data, where the categories can have, but don’t need to have, order. If they do have order, the category approach ignore that order The same layer can have some quantitative and some categorical attributes Introduction to GIS

5. ©2005 by Austin Troy. All rights reserved Mapping of Attribute Data Category approach, example: vegetation type Introduction to GIS

6. ©2005 by Austin Troy. All rights reserved Mapping of Attribute Data Quantity approach, example: population Introduction to GIS

7. ©2005 by Austin Troy. All rights reserved Mapping Categories This is the simplest type of mapping: we are simply assigning a different color or symbol to each feature with a given category value 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? Introduction to GIS

8. ©2005 by Austin Troy. All rights reserved Mapping Categories To map categories in ArcGIS, we simply double click on the layer in the TOC and, in “layer properties,” click on the “symbology” tab Generally,we will choose “Categories>> Unique values” Introduction to GIS The we choose our values field that contains the attribute and then click the “Add all values” button

9. ©2005 by Austin Troy. All rights reserved Mapping Categories The symbology in the last slide gives us conservation lands, categorized by type of ownership Introduction to GIS

10. ©2005 by Austin Troy. All rights reserved Mapping Categories Often categories must be aggregated and redefined: this land use map had over 110 categories that were condensed to 12 Introduction to GIS

11. ©2005 by Austin Troy. All rights reserved Mapping Categories Do do this, we must group the “group values” function in the symbology properties window Introduction to GIS We can then give that grouping a label In this case 1262, 1263, 1264, 1265, etc. refers to different subcategories of commercial land use This classification is saved when I save my ArcMap Document

12. ©2005 by Austin Troy. All rights reserved Quantity Mapping This is more complex, because there are so many ways to map out quantities Mapping options depends on the feature type: For points, lines and polygons, we can darken or lighten the color to express magnitude: this is called graduated color, or color ramping For lines and points we can increase symbol size to express greater magnitude: this is called graduated symbol; we can do this because points and lines have fewer than 2 dimensions Introduction to GIS

13. ©2005 by Austin Troy. All rights reserved Choropleth Mapping a thematic mapping technique that displays a quantitative attribute using ordinal classes applied as uniform symbolism over a whole areal feature. Sometimes extended to include any thematic map based on symbolism applied to areal objects. -Nick Chrisman A map that shows numerical data (but not simply "counts") for a group of regions by (i) classifying the data into classes and (ii) shading each class on the map. -Keith Clarke Introduction to GIS

14. ©2005 by Austin Troy. All rights reserved Graduated Color In Arc GIS layer properties>>symbology, we choose Quantities>>graduated color We then choose a value to represent In this case we choose median house value It automatically chooses five classes for the data Introduction to GIS

15. ©2005 by Austin Troy. All rights reserved Graduated Color The resulting map shows high housing value areas with dark colors and low with light Introduction to GIS

16. ©2005 by Austin Troy. All rights reserved Graduated Color In that case we used 5 classes. Changing the number of classes changes the information delivered; more classes: more info, but harder to see differences Introduction to GIS 3 classes for median value

17. ©2005 by Austin Troy. All rights reserved Graduated Color In that case we used 5 classes. Changing the number of classes changes the information delivered; more classes: more info, but harder to see differences Introduction to GIS 15 classes for median value

18. ©2005 by Austin Troy. All rights reserved Graduated Color The Classification Method also affects how the mapped attributes will look. Arc GIS normally defaults to the Jenks, or natural breaks, method Introduction to GIS These are the breaks it makes, based on the distribution of the data largesmall

19. ©2005 by Austin Troy. All rights reserved Graduated Color Now, here’s an equal interval approach. Notice how all the breaks are evenly spaced. With a fairly normal distribution of data, this is usually OK Introduction to GIS

20. ©2005 by Austin Troy. All rights reserved Graduated Color Here’s what the same distribution looks like with only 5 equal intervals. Introduction to GIS

21. ©2005 by Austin Troy. All rights reserved Graduated Color However, when the distribution is skewed, or there are significant outliers, then equal interval is problematic because most intervals have no data in them. Here’s an example, with number of vacant houses per tract—most have near none, but a very few have a lot Introduction to GIS

22. ©2005 by Austin Troy. All rights reserved Graduated Color This map of vacant properties tells us almost nothing, because almost all the records fall into the first class Introduction to GIS

23. ©2005 by Austin Troy. All rights reserved Graduated Color Notice how with natural breaks there are now more classes on the left side, where most of the data are Introduction to GIS

24. ©2005 by Austin Troy. All rights reserved Graduated Color Introduction to GIS This map, made with Natural Breaks, is more intelligible

25. ©2005 by Austin Troy. All rights reserved Graduated Color There is a similar approach to Natural Breaks called Quantile. This method sets class boundaries so each class has equal numbers of observations in it Introduction to GIS

26. ©2005 by Austin Troy. All rights reserved Graduated Color This essentially sets the class boundaries so as to maximize the perceived variation in the map, as we see here Natural Breaks is similar, but does not necessarily result in an equal number of data points in each class; rather it uses Jenks' Goodness of Variance Fit (GVF) statistic Introduction to GIS

27. ©2005 by Austin Troy. All rights reserved Graduated Color Graduated color can also be applied to points. Here are houses display by sales price Introduction to GIS Natural breaks Equal interval

28. ©2005 by Austin Troy. All rights reserved Graduated Symbol Since points and lines are not dimensionally realistic, the symbols representing them can also be graduated. Here the size of the dot represents the house price Introduction to GIS

29. ©2005 by Austin Troy. All rights reserved Graduated Symbol The same thing can also be done with lines—for instance, the width of a line feature showing rivers can be made to represent the flow of that river segment. For many line features, like streets, ArcGIS comes preloaded with symbol palettes that recognize the attribute codes and put the appropriate symbol Introduction to GIS

30. ©2005 by Austin Troy. All rights reserved Symbol Styles We can also choose to “match to symbols in a palette” and then apply the “transportation.style” palette to the CFCC, or road category, attribute in our roads layer Introduction to GIS Results in this map Must click here to match Choose your style palette here

31. ©2005 by Austin Troy. All rights reserved 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. Introduction to GIS Includes many more classes of symbols that are industry standar

32. ©2005 by Austin Troy. All rights reserved 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 Introduction to GIS

33. ©2005 by Austin Troy. All rights reserved Charts displayed geographically Attributes for point, line or polygon features can also be displayed as charts on the map Introduction to GIS

34. ©2005 by Austin Troy. All rights reserved Normalization With graduated color or symbol, we can also show an attribute normalized by another attribute or expressed as a percentage of total. Here we have number of vacancies per tract as a percentage of total households. Otherwise we’re only tracking total number. Introduction to GIS numerator denominator