Understanding GIS. David Smith
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Quantitative symbology is flexible, and you can present data in many ways. Because all you want right now is a general sense of viable areas for your project, and because you’re going to look at a couple of variables together, you should keep your presentation simple.
1)Change the Classes drop-down box to 3.
2)Set the classification method to Quantile.
Using three classes, you’ll easily be able to see high, medium, and low values. The quantile method guarantees that an equal number of tracts will fall into each class. It should be noted that there are no inherently good or bad ways to classify data—different classifications may be more or less appropriate to the purpose of your map and the background knowledge of your audience.
3)Change the first upper value to 8000 by double-clicking the label, typing the value into the Upper value cell, and pressing Enter. The second class break point is selected and editable.
4)Change the second upper value to 16000.
Notice that the classification method has been reset to Manual Interval because you’ve changed the class breaks. The histogram is updated, too. You no longer have a pure quantile classification, but having your classes break at round numbers makes intuitive sense.
The outlines of the polygons are currently overwhelming the map in some of the areas with the highest densities, making it difficult to interpret the classifications.
5)Click the More button on the Classes tab and select Format all symbols. Any changes made here will apply to all the classifications.
6)If necessary, change to the Properties tab (near the top of the pane). Change the Outline color to No Color.
7)Click Apply at the bottom of the pane, and then click the back arrow at the top of the Symbology pane to return to the classification settings.
You’re removing the outlines because you don’t need to see the tract boundaries on the map. For now, you’re interested in them as areas, not specifically as tracts.
8)In the Label column, double-click on the first label (< 8000) to make it editable. Type Low, and press Enter.
9)Replace the second label with Medium. Press Enter.
10)Change the third label to High. Click outside the edit box to commit the edit.
11)Change the transparency of the tracts layer to 50% (from the Appearance ribbon).
12)In the Contents pane, drag the tracts layer under the Parkland layer.
On the map, you can now see where population is concentrated along the river, and you can see it in relation to existing parks.
Measure distance from the river to parks
Making a few measurements will improve your ability to estimate distance on the map and give you a better intuitive sense of how close to the river the new park should be.
1)Select the Dodger Stadium bookmark (if necessary, turn off the tracts layer).
2)Pan the map so that a number of parks are in the view. Feel free to zoom in or out.
3)On the Map tab, in the Inquiry group, click the Measure > Measure Distance button to open the Measure Options.
4)Click the Options drop-down arrow. Set the Distance units to Miles and turn off Feet.
On the map, the pointer changes to a ruler with inscribed crosshairs.
5)Point to a park, such as Cypress Park (northeast of Dodger Stadium on the east side of the river).
6)Click to start a measurement.
7)Point (you don’t have to drag the pointer) to the river. The measurement result is displayed along the line and in the Measure dialog box.
8)Double-click to end the measurement.
9)Click on another park and measure its distance to the river.
The new result replaces the previous one in the Measure dialog box.
10)Measure the distances from a few more parks.
Cypress Park, Elysian Valley Recreation Center Park, and Downey Playground are close to the river. Elyria Canyon Park, a little over three-quarters of a mile away (at its nearest edge), stretches the notion of proximity. Bear in mind that these measurements are straight-line distances, not the distance along streets.
11)Switch back to the Explore tool
12)Zoom to the City of Los Angeles bookmark.
Add a layer of census block groups
Another requirement for the new park is that it be located in a lower-income neighborhood. To symbolize an income attribute, you must add another layer to the map. (It’s not that income data isn’t reported at the census tract level, it’s just that your particular tracts layer doesn’t happen to include it.)
The same census folder that contains tracts.shp also has a shapefile dataset named block_groups.shp.
1)Open the Catalog pane and add the block_groups shapefile to the map from ParkSite > SourceData > census.
The new layer is added above the other layers. Like the tracts layer, the block_groups layer covers Los Angeles County. And like the census tracts, the block group polygons resemble a jigsaw puzzle. Block groups are another Census Bureau statistical unit: they’re smaller than tracts and nest inside them. We’ll talk more about census geography in lesson 2.
2)Open the attribute table of the block_groups layer and scroll across the attributes.
Most of these attribute names are cryptic. One of the last fields in the table is called MEDHINC_CY. For now, take it on faith that this acronym stands for median household income. Each block group value is a median value, in which half the households earn more than the median income value and half earn less.
3)Right-click on the MEDHINC_CY field name and Choose Statistics.
The statistics of the MEDHINC_CY for block_groups show a range from the lowest value of 0 to the highest of 200,001.
4)Close the table, histogram, and Chart Properties pane.
Symbolize census block groups by median household income
If you symbolize the block_groups layer with graduated colors, you won’t be able to evaluate income and population density at the same time. Instead, you’ll represent each block group’s median household income as a point drawn inside the block group polygon.