Study Guide, Chapters 16 and 17 G337 / G537

Transcription

1 Study Guide, Chapters 16 and 17 G337 / G537 This study guide introduces Chapters 16 and 17 from Thematic Cartography and Geographic Visualization. Beware: a study guide is not a replacement for thoughtfully reading the chapters! Chapter 16 introduces proportional symbol mapping. These types of maps are very common, and fairly easy to produce in ArcMap. That said, their legends can be difficult to understand so pay close attention to the textbook s discussion of this matter. 1. Recall that Chapter 4 s discussion of symbolization included a subsection on proportional symbols. Take a few moments to review this information from Chapter Section 16.1 raises the issue of data. Can proportional symbol maps display nominal data? How about with ordinal data? Leaf through Chapter 16 and examine the illustrations: What kind of data is the proportional symbol best suited for? 3. Proportional symbol maps can display standardized and unstandardized data. It is also pretty easy to scale the symbols to represent the data. These two factors wide applicability and ease of construction explain why this is such a popular display choice. 4. Note that both choropleth and proportional symbol maps can be used to represent standardized data. Which one to use is a matter of preference. Perhaps the best advice is to use proportional symbols if you fear that the size of the enumeration units will obscure the pattern you are trying to emphasize. Review the discussion on pages if this makes no sense. 5. We also learn in Section 16.1 that proportional maps can be used to represent both point and sort of point data. Yet another two for one bonus with proportional symbol mapping! The authors refer to this pseudo point data as conceptual point data. 6. On page 312 the authors discuss standardized data. They offer a very smart example when they compare out of wedlock births and population: the distributions are nearly the same; this suggests that one factor is Study Guide 6 1

2 related to the other. The map in Figure 16.2 C is more informative because the numbers were standardized. The authors divided teen, out of wedlock births by total number of births. Choosing a meaningful denominator makes all the difference. Notice that it wouldn t make much sense to divide the data by area. 7. Section 16.2 makes the point that the proportional symbol you choose need not always be a circle. Myself, I like the circle and sphere, but go ahead and experiment. Beware, however, of cartoonish symbols: they can damage your credibility. 8. Figure 16.5 does a nice job of displaying the utility of three dimensional symbols. That said, three dimensional symbols can obscure whatever lies behind them. Perhaps they are best saved for a multimedia, interactive environment wherein the map can be spun around and viewed from multiple perspectives? 9. Remember to say thank you to the computer and his trusty programmer after reading the formulae on pages Calculating the appropriate proportions were a standard part of the cartographer s task not long ago. For our purposes, simply be aware that the formulae are available in a pinch. 10. Regarding the different terms used to refer to scaling, refer to Assignment Range grading generally works very well (see Figure 16.17), although take care and heed the warnings on page 319: readers may over interpret the symbols and the distinction between the symbols may imply a pattern that in fact is not meaningful. 12. While nested legends look good they are not particularly legible. For a reminder of just how difficult they can be to interpret, take another look at Color Plate Left or right, up or down? There are so many choices when pulling together your legend. The authors offer their usual brand of smart advice: with a linear, horizontally oriented legend, mimic the number line and the Study Guide 6 2

3 direction that we (in the Latin tradition) read a text. For linear, vertically oriented legends they leave the choice to you. Myself, I like to have the largest symbols at the bottom. It appears more stable and balanced to my eye. 14. Check out the care that has been taken to align the numbers and symbols in Figure I like overlaying the symbols with the actual data values, although I think the numbers could potentially obscure of the symbols. 15. The big challenge with overlapping symbols is making the connection between a given symbol and its corresponding piece of territory. Alas, given the generally sad state of geographic literacy, I would be cautious and err on the side of less overlap. The smaller the symbols, however, the more likely your map will be very boring to look at. What a dilemma! The authors offer that transparent symbols allow you to link symbol and territory. They also like the fact that it is easier to estimate the size of transparent symbols. I would not get too excited by this; if your mapreader wants super precision, refer him or her to the data table! 16. Further, the transparent symbols in Figure look like pie charts to me. I really like the manner in which the opaque symbols create a figureground relationship. 17. I think redundant visual variables get a bad rap. While the map in Figure has too much overlap for my taste, I like the use of value to link the legend and the map symbols. Frankly, I often find it difficult to judge symbol size so the use of another visual variable like value is very helpful. Chapter 17 introduces dot and dasymetric maps. It is an application chapter and considerably easier to comprehend than what you have faced thus far. FYI: dasy comes from the Greek for dense. This makes sense inasmuch as dasymetric maps try to take density into consideration. 18. The use of dot maps reminds me of Page 68 s discussion of raw totals and standardized numbers. Rates are very important; they allow us to make Study Guide 6 3

4 valid comparisons. That said, if the underlying totals are extremely different, the comparison will not be valid. Dot maps allow you to use raw totals while visually communicating a sense of density. Dasymetric maps rely upon data presented as a rate. 19. Related to this matter of totals and rates, return to Chapter 4 where you originally encountered the dot and dasymetric maps. Dot and dasymetric maps are an appropriate alternative to the choropleth map when you want to portray the variation within an enumeration unit. Specifically, note Figure 4.1 and the fact that the dot and dasymetric occupy different rows in the table. The dot map is used for data whose location is discrete and whose value varies from abrupt to smooth. The dasymetric map is used for data that are continuous across an area and whose value lies at the midpoint of the abrupt to smooth variation continuum. 20. Although data frequently are collected for enumeration units and mapped at that level, the resulting maps can be misleading because the distribution of the underlying phenomenon often varies within enumeration units (p328). That is where dot and dasymetric maps come into the picture. Ideally, these mapping techniques allow the cartographer to pass along more information to the map reader. Ideally. 21. The only problem is that there is no easy way to accurately and reliably place those little dots or draw the dasymetric boundaries: In practice some experimentation is generally required to select an appropriate dot size and unit value (p332). That is to say, fiddle around until the dots look right. So, for our purposes, understand the concepts, but do not worry about the specific application. For the time being, we are going to let ArcGIS pick the dot locations for us. 22. Generally, use the smallest enumeration unit possible so as to diminish the area over which the software randomly distributes the dots. So, if you have the choice of using county level or state level data, use the county data because there will be less random noise associated with dot placement. Study Guide 6 4

5 23. A good rule of thumb when placing dots: Generally, it has been argued [Nice passive voice!] that dots in the densest area should just begin to coalesce (p331). This fits with the authors earlier advice (p73) that we generally do not expect readers to acquire precise numerical information from maps; rather maps are primarily used to show spatial patterns. 24. The nomograph I love that name! is total overkill for us. Likewise, you can skip over page 334 and 335 s discussion of An Approach for Automatic Dot Placement for the time being. 25. Give subsections 17.4 and 17.5 the lightest of skims. These sections provide a glimpse into the future of thematic mapping. Intra enumeration unit variation is commonly hidden for the sake of privacy. Really accurate dot and dasymetric maps raise all sorts of privacy issues. Just what are these maps going to be used for? Study Guide 6 5