GEOG 413 - Computer Cartography

Lab 4 - Classification methods and choropleth map production.

The purpose of this exercise is to introduce you to three common ways of classifying data for representation as a choropleth map. The word "choropleth" comes fromt he Greek words 'choros' meaning place or area of magnitude and 'plethos' meaning graphic. Thus, the choropleth map is used to illustrate the relative magnitude of places. The cartographer will normally represent different magnitudes by the use of colors or shading - having each class represented by a variance in color or grey tone. It is convention and perceptually correct to represent classes with lower magnitudes with lighter shades (or values) than those with higher magnitudes for media with a white background such as a printed map.

The main objective of a choroplethic classification procedure is to reduce the number of individual data values transmitted to the map reader. Ther eis no one best way of devising class intervals and class boundaries for choropleth maps. Simplicity is a major goal. It is also worth considering that the class interval system should include the full range of the data and reflect some logical division of the data array in order to portray both the data distribution and the purpose of the map.

Developing class intervals and class boundaries for conventional choropleth maps remains largely an experimental activity. Each geographical phenomenon being mapped presents a unique set of circumstances. Mapping purposes vary, as does the intended readership. The cartographer must look at each new choropleth map from a fresh perspective, without feeling constrained to follow a given method of classification.

The objective of this lab is to play with classification methods in order to understand the different stories different classifications (and numbers of classes) can tell.

For this lab, you will be using the GIS software ArcGIS.

First, download the data to your disk by grabbing cart_tut5.zip from the data drive. Do not change the name of the file. The file you downloaded is a .zip file - in other words, I have compressed a number of files into a single, smaller file. After you have downloaded it, goto your drive (using Windows Explorer) and unzip the files. Then double chect to make sure that 5 files (all "wash" with different extensions) are where you want them.

OK - you're ready to start working in ArcGIS.

Start by opening ArcGIS: Start - Programs - ArcGIS - ArcMap.

When a window pops up asking about what to open - keep the default which is a new project.

Add your Washington map to the view by selecting File - Add Data. Navigate to wherever you put your WA data and select your data (wash.shp).

Click on the little box next to the file name - this will draw the map. Obviously, it is a map of the state of Washington, including county boundaries. There is a data file associated with this map. To view it, right click on the filename to the left of the ArcMap window and select Open Attribute Table. Check it out and take a look at the available data. Some of the headings are a bit cryptic - you know as much as I do....

We will start with a couple of choropleth maps. Make sure the map is active (click on it). Right click on the "wash.shp" text in what sort of appears to be the legend and goto Properties. This little window is where you play around with how you map things. Goto Fields and select the dataset you want to map (primary display field). Next, move over to Symbology (one of the top tabs in this properties box). Depending on what you're mapping (nominal data, select unique values; interval/ration, select Quantiles), you need to select a mapping scheme. As you will first map, say, population, select quantiles - graduated colors. Also, select the field you want to map, colors, etc. Once you select your field to map, you will notice that the Classification area becomes active. Here you can play with the number of classes. Also, hit the Classify button - a new window pops up that gives you details regarding classification method, number of classes, the data, and the breaks. You will note that, somehow, ArcMap decided on 5 classes with the breaks given in the legend area. Red is also the default color ramp. Play around a little (draw a bunch of different maps with different data/classifications/#of classes. To change this to, say, greyscale (for printing to the laser printer), click on the color ramp options and change this. To find out more about how the natural breaks thing happened, click the classify button. You will note that the classification type used was natural breaks with 5 classes. This is nothing more than ArcMap's default number of classes - it has no relation to the number of clusters in the dataset. Change the classification types to quantile and equal interval (you have to hit OK, then APPLY to view the changes. Note that you can change the number of classes.

OK - you now have enough info to change your classifications. To actually make a map that you can print, go back to your map interface. Click - View - Layout View. You'll see something that looks more like a production map pop up. Add a title and legend (insert - legend). The title should include both what the data is and the classification method used. Never forget neatlines! Use the various text and drawing buttons to add a neatline and a bit of text which explains what you did regarding classification. Make sure the title describes your dataset. This can now be printed to the ole laser printer if you really want.

Now - make a quick series of maps - pick any of the WA datasets you wish. Print each map as you finish it, as making a new one will overwrite your earlier map. Note - these will be printed to the laser printer, so make sure your output looks good in greyscale.

• Quantile (equal frequency) classification - 4,6, and 8 classes (3 maps)
• Equal Interval classification 4, 6, and 8 classes (3 maps)

Now, we need to use the natural breaks classifier - to do this, you have to first take a look at the data. Fortunately, you can do this in the histogram that you saw in the classifierer box earler. Look at where you would put class breaks. And how many. Write down where these breaks should occur (hint - placing the mouse over the boxes along the line will give you the actual value of those points). As the breaks may not be super obvious, make two sets (different breakpoints and different number of classes). Now, you've figured out what you think are the best options given the data (these may not be the best maps overall, just given what you can see). Now, using the manual classifier, make the maps that represent these two different classification schemes. Print 'em out.

In total, you should now have 8 maps of the same data using different numbers of classes and different classification methods.

Examine all 8 maps. Given that you have some knowledge of Washington and the data you have been mapping, writeup the following:

1. Which map(s) seem to give the best representation of the data? Why?
2. Which map(s) seem to give the worst representation of the data? Why?
3. Each of the maps tells a different story - pick two of the maps and explain what story they are telling, how that story is being told, and why you (as a cartographer) might want to tell that particular story. Note - only one of the two maps in questions 1 and 2 may be used for this question.

Hand in the 8 maps and the answers (typed) to the three questions.

Due date: Tuesday, 12 February, 2008. 5 points.

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