Chapter 8 - Map Generalization and Classification

LEARNING OBJECTIVES

1. Describe how maps generalize a very complex world into something easier to understand.
2. Define data classification
3. Compare and contrast qualitative and quantitative classification
4. Discuss the different types of quantitative classification

TERMS TO KNOW

• generalization
• classification
• simplification
• smoothing
• selection
• displacement
• quantitative
• qualitative
• quantile scheme
• equal-interval scheme
• natural-breaks scheme
• unique scheme

LECTURE POWERPOINT SUPPLEMENT

READING ASSIGNMENT

Chapter 8 of your text - MakingMaps: A Visual Guide to Map Design for GIS

The author's outline for this chapter from the class he teaches using this book - Thanks for sharing Dr. Krygier!

Ways to map quantitative data - ESRI ArcGIS 9.2 WebHelp

ACTIVE LEARNING EXERCISE
Create a map with at least 4 data frames. In each data frame, map Buncombe County census data using a different quantitative scheme.

STUDY QUESTIONS

1. Sometimes, fewer data are often better. Give an example of this.
2. What is the point of map generalization and data classification?
3. List and describe the types of map generalization techniques.
4. Why do we classify data?
5. What is the difference between qualitative classification and quantitative classification? Give an example of each.
6. When determining the number of classes to put your data into, what are some things to consider about whether to use relatively few classes or more classes?
7. What is an advantage and disadvantage to using the quantile scheme for classifying your data?
8. When is an equal-interval classification a good choice?
9. When is an unique scheme a good choice for data classification?