The map has three thematic layers—Cities, Roads, and Provinces—and two basemap layers. You'll symbolize the provinces polygons first, because it is the most important layer in your map. You'll turn the other layers off for now, so you can focus better on the provinces.

The Symbology pane appears. The provinces are symbolized with Single Symbol symbology, which is good when you only want to convey the location of things. But in this map, you also want to convey one of the layer's attributes: population.

Several of the available methods draw quantities using colors.

The map now shows more populous provinces in red and less populous ones in yellow. One way to test how well your symbols convey your intended message is to look at the legend.

The cut-off values aren't necessarily meaningful, and they create a map that suggests that a value of 2,060,000 is more similar to 700,000 than it is to 2,050,000.

You could choose better cut-off values, either by rounding them or choosing a different classification method. But for this map, categorizing the data is not necessary. The data is continuous, not discrete, and the goal of this map is to help a general audience visualize populations as either more or less than other provinces. Classifying the data into discrete partitions does not improve the clarity of this map.

The legend now shows that the symbol colors change gradually from a minimum value to a maximum value.

This approach is simpler and more appropriate for the purposes of your map.

The symbology of this map still has a problem. Central Kalimantan (on the island of Kalimantan, or Borneo) and the Special Region of Yogyakarta (on the island of Java) appear to have similar populations. But one is many times larger than the other, so population density must be very different. This map is misleading because it doesn't indicate well where most of the population lives. Instead of mapping population, it would be better to map population density.

When mapping geographic areas with colors, it's important to normalize your data, usually by converting counts to rates or ratios. The point of normalization is to convert values to a standardized scale so that comparisons are meaningful. To normalize this population data, you'll divide the population of each province by its area to calculate the population density.

Now the colors on your map represent the number of people per square kilometer in each province.

The map shows you that population density is far greater in the Special Capital Region of Jakarta than in any other province.

While this is true, it is not a very interesting map. It only tells you about one province, instead of all of them. You'll adjust the range of the color scheme to better show the comparisons between the other provinces.

In the lower half of the Symbology pane, a vertical histogram shows the distribution of population density values. Most of the data is at the very top (low density), with one outlier—Jakarta—at the bottom (high density). Two bounding handles on the side of the histogram represent the cut-off values for the darkest and lightest colors. You'll adjust these handles to limit the influence of Jakarta and make variations between the other provinces visible.

The handle moves closer to the top of the histogram.

Now all values greater than 1,500 draw with the darkest blue, reserving the range of colors between white and blue for the bulk of the data range.

The map now shows that population density is highest on the island of Java. In fact, Java is the world's most populous island. You can also discern more variation on the islands of Borneo, Sumatra, and Sulawesi.

Now that you have altered the range of the colors, the legend for this map may be deceiving. The legend ranges from 9.8 to 12,940.6 people per square mile, while the map colors only range between 9.8 and 1,500. You'll improve the legend so the symbology of your map can be more easily interpreted.

You are almost done symbolizing the province polygons. The last thing you'll do is change the color scheme. All colors have connotations (which vary by culture). To many people, blue suggests water, so a casual map reader might think this map was about rainfall or flooding. Population and urbanism are often represented on maps with pinks or purples, since these colors are less common in nature.

Most map readers interpret dark colors to mean more while light colors mean less, so a good color scheme choice for a population map will be one that ranges evenly from light to dark colors.

You'll finish this layer by changing its name to make it clear to map readers what it represents.

You've now made a choropleth map that symbolizes the provinces of Indonesia by population density. You learned when to use unclassed colors versus graduated colors, why to use rates or ratios instead of counts, how to adjust the range of the symbology, and how to choose an appropriate color scheme. Next, you'll symbolize cities.

The Symbology pane updates to show symbology for the Cities layer.

Proportional symbols are similar to unclassed colors, where the symbols range evenly and continuously from a minimum value to a maximum value.

On the map, the capital Jakarta stands out as the largest city in Indonesia. Unfortunately, it also hides other important map information. You'll make the symbols transparent to prevent this problem. You'll also change the symbol color to match the darkest purple province.

The Symbology pane displays further symbol options.

This tool allows you to choose existing colors from your map.

Now both the point and the polygon layers of the map will use the same color to represent the same theme: urbanism. Using similar colors for similar things makes your map easier to interpret. You'll save this color to a style so you can reuse it elsewhere in your map.

The Color Editor window appears.

Now that you've saved a fully opaque version of the color for later use, you'll make the color transparent.

A thicker outline will make the smaller circles bolder and easier to see.

Now when you make changes to the symbology properties, they will be automatically updated on the map.

The transparent circles no longer hide other parts of the map. This is important, because while Jakarta has 10 million people, there are also several other cities just outside of its boundaries with large populations of their own. Clearly the metropolitan area of Jakarta extends beyond the boundaries of its province.

To finish this layer, you'll ensure that the legend is clear and does not take up too much space on your map.

In the Contents pane, the legend shrinks to only a small and large circle.

You've now symbolized points with size. You learned how to borrow colors from other map symbols, save a color to a style, and how to create transparent overlapping symbols

The city points and province polygons work together to tell a story about population distribution. While the provinces carry the entire population—urban and rural—the cities provide more context about where most of the population is concentrated. In particular, they help to highlight the prominence of Jakarta.

So far in this tutorial, you have symbolized quantitative data. Next, you'll symbolize qualitative data, or data that varies by types or categories rather than numeric values. Unique Values is the best choice for mapping types.

A table appears on the Symbology pane, listing four symbol classes:

• Major Highway
• Road
• Unknown
• <all other values>

The difference between major highways and roads will vary from one dataset to another. Knowing how many features of each category you have on your map will help you understand the role each type plays.

A Count column was added to the table.

There are no features on your map in the <all other values> symbol class. This symbol class will only clutter your legend, so you will remove it.

Of the remaining symbol classes, Unknown represents the majority of features on the map. There are only a few Major Highway lines, all of them near Jakarta. You'll group the Major Highway and Road classes together.

There are now only two symbol classes. Often, your data will have more symbol classes than are needed on your map. Combining them into a simpler set of symbols will make a map that is easier to interpret. Next, you'll improve the legend.

The pale symbol colors are hard to see on the map. You'll make them darker and give them a dashed pattern to help distinguish them from the province borders.

You do not have any ferry route lines on your map, but system symbols intended for other purposes can be useful starting points for your own symbols.

Both symbol classes are now represented with dashed blue lines.

You've now symbolized lines by type.

You learned how to group and rename symbol classes and redesign template symbols for your own purposes. In this tutorial, you symbolized one layer at a time. When you work on your own map projects, you will often switch back and forth between layers to ensure that all map symbols work together in a cohesive map design.

The map updates. The new map background now appears simpler and better highlights the thematic content.

Gray is a useful basemap color because it is typically interpreted as no data. Being pale and desaturated allows it to read as background information, rather than foreground. However, in the case of the Indonesian archipelago, most of the map is water, so the majority of the map is grey. You may find this to be a bit drab. Next, you'll change the color of your basemap to change the tone of your map.

This layer is a large rectangle that covers the entire world. You'll use it to change the color of all the layers underneath it. It is added to the map above the provinces layer. You only want it to affect the basemap, so you'll reorder the layer.

The green color is very dark and overwhelms the map. You'll make the green layer blend with the layers underneath, instead of hiding them.

Layer blending determines how layers combine with the layers underneath. The expected result for this blend mode is to recolor everything except white to a shade of green. But instead the map returns to gray. You'll investigate the basemap to discover why it was not recolored.

The Human Geography Map basemap contains three layers. Human Geography Label and Human Geography Detail draw on top of your thematic map layers, while Human Geography Base draws underneath. Layer order is an important aspect of symbology.

This layer carries most of the basemap information. The green layer is drawing underneath the Human Geography Detail layer and therefore has no effect on it.

Next, you'll remove the Human Geography Base layer. This layer only contains a pale background for land areas and isn't needed in your map.

The basemap changes from gray to green, colored by the GlobalBackground layer, which blends with anything drawing underneath it.

In addition to reordering, you can also add and remove basemap layers. Next, you'll add a hillshade layer to bring back some texture and topographic context.

The new layer is added to the map beneath all of the other layers. It is colored green by the GlobalBackground layer, but it is only visible in neighboring countries. It is hidden in Indonesia by the province polygons.

If you move the hillshade layer above the provinces, it will hide them instead. To get around this issue, you'll use another blend mode.

Multiply is one of the most commonly used blend modes. In this situation, it allows both the provinces and the basemap layers underneath to be equally visible.

The green ocean complements the pink provinces nicely. However, the most common forms of color blindness make it difficult for many people to distinguish between reds and greens. While this map may look attractive, it may also be hard for some people to read. You'll change the ocean color to blue.

The map updates with the new basemap color.

Next, you'll test if your new color choice is acceptable for different forms of color blindness.

The colors of the map change to simulate how it might appear to a person with green-blind vision. The map is still legible—for example, the difference between land and water is still clear.

Basemaps are helpful resources for thematic maps, since you do not have to spend time building and symbolizing background geography. But just like every other map element, you don't need to use them in their default state. Choose a gray basemap to better present your thematic data. Try adding, removing, and reordering basemap layers, adjusting their transparency and layer blending, and even changing their color with a blended layer on top.

An effective basemap elevates your thematic data, rather than distracting from it.

This A4-sized layout has already been set up for you. However, you'll tidy the legend before you export it.

Many of the layers in your map are basemap layers that don't need to be presented in the legend.

The legend on the map is smaller, but it still contains redundant information that can be removed. For example, the layer name Cities: Population totals is followed by the heading Population. A cluttered legend takes longer to read and understand.

The headings for all three layers are removed from the legend.

You're almost ready to export your map. Before you do, you'll take one more look to see if your symbols are working as well as they can. The road layer appears jumbled and crowded at the scale used by the layout.

You'll adjust the line width to better suit this scale. You can make this change from the Layout view.

You are now ready to export the map. You will use an export preset that already has common properties set for a .pdf format.

The Export Layout pane appears with many properties already entered. You will modify a couple of properties for your export.

• Verify that Output as image is unchecked (it should be as part of the preset).
• For Image compression, verify that Adaptive is chosen (it should be as part of the preset).
• Confirm Quality is set to approximately 80%.