Smart Mapping: Get Started

Make beautiful and informative maps FAST with ArcGIS Online Map Viewer

Smart mapping is here to help you create effective and impactful maps, quickly. This guide is here to explain what smart mapping is, and how to get started.

What is Smart mapping?

Smart mapping helps you symbolize your maps in ArcGIS Online and ArcGIS Enterprise. Smart mapping allows you to explore your data to help you understand what's worth calling attention to, and symbolizing what's important.

Not a cartographer? Don’t worry! Smart mapping's default settings take the guesswork out of your map-making process, and help you get to a clear map more quickly. It helps you showcase what’s most important in your data, de-emphasize or even filter out what’s not important.

Do you have a background in cartography? Awesome! Smart mapping provides a wide range of mapping techniques and options to help you create stunning customized maps.

What makes it smart?

As soon as you choose an attribute to symbolize, smart mapping looks at the attribute’s information to suggest map styles that work with that type of data: text fields, integers, floats, date fields, and combinations of these types. As a result, you can quickly try out different map styles to see how each might work with your data. This is why we call it "smart"!

Where is it?

To start using smart mapping within Map Viewer, select the layer you want to symbolize from your Layers on the left toolbar, and then choose Styles from the right toolbar:

Smart mapping can be broken down into 3 simple steps:

1) Choose attribute(s)

2) Try a drawing style

3) Explore the style options

1) Choose Attributes

1 Choose an attribute

To start mapping your data, click +Field to select an attribute from the drop down list of attributes from your layer.

Some things to help you choose an attribute to map:

  • You can quickly search for a field by its name or alias
  • Click the small i next to each field to learn more about it. See the field type, field description, a sample value, and more. If looking at a numeric field, you can see the statistics such as the minimum, maximum, average, etc.
  • Easily choose a different field by replacing it with another

Notice that the styling options change as you choose different fields

If you select a single attribute, you will automatically see a map that is appropriate for your data type. Below we see a Counts and Amounts (Color) map because the attribute selected was a Double/Float. Smart mapping suggested this style based on the characteristics of the attribute.

To go one step further, try choosing two fields to see the patterns of both attributes within the map at the same time. Below is an example where a percent (Double) and a count (Integer) are being mapped with the Color and Size style.

There are many different ways to visualize and compare attributes patterns alongside each other in a single map. Choose up to 10 attributes to find possible relationships between seemingly different topics. You may be surprised at what you find, and smart mapping makes it easy to try different styles.

Here are some examples:

  1. Compare A to B: Compare two fields as a ratio or percent
  2. Dot Density: See where there are concentrations by visualizing the patterns as dots on the map
  3. Relationship: Also known as bivariate mapping, this style shows two color patterns alongside each other to let you compare them.
  4. Predominance: See which field has the largest value by using predominance. Compare up to 10 attributes.

But how will you know which style to choose?

The answer is that you won't know until you try! Step #2 will show you how to navigate through these various styles to choose one suitable for the story you want to tell about your data. Let's see how some of the maps above were created.

2) Try a drawing style

2 Try a drawing style

Once you have selected an attribute (or multiple attributes), smart mapping will suggest drawing styles based on the attribute type. 

For example:

In this map, we start with the raw polygons for Census Tracts in the Chicago area. Smart mapping knows that no attribute is being mapped, so notice that it shows the current style as "Location (single symbol)".

We can choose +Field to select a field and start customizing our map.

If we select the field called "County" and choose the small i to the right, we can learn more about this field.

Here we can learn more about an attribute. We can see that this field is a string.

We can also learn more about the field by its description and statistics.

Let's choose this field to see what smart mapping offers us.

Smart mapping noticed that this attribute was a string/text field, so it only offered us a mapping style appropriate for this type of data.

The map automatically is set to "Types (unique symbols)". Notice again how the interface shows you the current drawing style being used in the map.

Click on the attribute currently being mapped (County) to replace it with another attribute.

Let's explore a field containing numeric values.

Here we chose the "Hispanic or Latino Population" attribute to see the count of population who replied to the US Census Bureau's American Community Survey as this ethnicity.

Click the i to learn more about this field.

This field is an Integer, meaning it contains numeric values that are whole numbers. Let's see what smart mapping offers us.

Smart mapping recognized that the attribute was an integer, and automatically offered us a map highlighting the areas with the largest number of Hispanic or Latino population by the mapping style Counts and Amounts (Size).

We can already learn new things about this topic by seeing the clustering of large circles in certain parts of the downtown Chicago area.

Hint: if you don't know when you would use a certain style, choose the small i to learn more.

Instead of visualizing the count of the Hispanic and Latino population, we can replace the field to see 'Percent of population that is Hispanic or Latino' the same way we replaced the field before.

If we were to investigate this field like the others, this field is type Double. This means that there is a decimal in the data values. This is also known as a float.

Because this field is a Double, smart mapping offers us a map that stratifies the data over various colors based on the statistics. This style is known as Counts and Amounts (Color) and is also referred to as a choropleth map.

If we wanted to combine the two previous maps, we can add the Hispanic or Latino Population field as a second field. Let's see what smart mapping gives us...

Smart mapping merged the two maps to show us both the percentage and count fields within a single map. This puts emphasis on the areas with both a high count and high percentage of people who are Hispanic or Latino.

This style is called Color and Size since it combines the two styles.

Next, let's quickly explore a few of the other styles that are available when mapping multiple attributes.

If we replace the percentage attribute with another count, we can start to compare patterns.

Here, we replaced the percent Hispanic attribute with the count of Black or African Americans (non-Hispanic) to learn more about the racial breakdown of population within Chicago. Let's see a few maps based on this combination of attributes.

The first style we explore is called Compare A to B which offers a ratio or percentage to compare the two attributes. We can see that there are overall more Hispanic or Latinos, but that there are pockets of blue showing areas with higher Black or African Americans.

Using the same two fields, we can change the drawing type to show Dot Density. This style helps us visualize distribution of the data.

We can see where there are areas with more or less of each race/ethnicity shown in the map. Each dot on this map represents 9 people, as you can see in the Legend on the bottom left.

Let's try another style with the same two fields. This style, Predominant Category, compares the values of each field and shows us which one is larger.

Areas in red have more Hispanic or Latinos than Black or African American. Areas in yellow have more Black or African Americans.

If we change the style to Predominant Category and Size, we see the same map as before, but the size component of the map adds the two fields together to show us the total sum of those categories.

This style adds one more level to the story being shown, but only took a single click to explore.

Finally, if we choose the Relationship style comparing these two attributes, it will provide a gridded Legend representing a combination of two distinct data patterns.

Areas in blue have higher Black or African American population. Areas in Orange have higher Hispanic or Latino population. Areas in brown have high counts of both, and areas in light beige have low counts of both.

As the map-maker are the key to a successful map. Smart mapping will offer you smart suggestions to start, but your knowledge of the data or subject matter is crucial to the smart mapping workflow.

Each mapping style can help different stories emerge from your data. This basic intro doesn't even begin cover them all, but smart mapping will always give you smart defaults to help you get started and explore. It is easy to swap between them and explore new patterns. Try spending 5 minutes with a new dataset and choose different attributes and styles and watch the stories unfold.

Once you have chosen a map style, it is best practice to go beyond the defaults and customize the map to your purpose. Step #3 shows us how to navigate the options and choose setting which will create more meaningful maps.

3) Explore the style options

3 Explore the options

Creating a map is more than just choosing the style. It's also about using your own knowledge and intuition to effectively communicate the story behind the data.

Each drawing style provides different options, allowing you to customize your maps beyond the smart defaults. This is a highly encouraged step that can often be overlooked, but is a crucial part of the map-making process. A few small changes within the options can make your map infinitely more clear to your audience.

Here are some pointers to familiarize you with some of the most common options:

Once you have selected a drawing style, click Style options to get into the detailed settings.

Let's explore the Counts and Amounts (size) options to get familiar.

When mapping size, the symbols on the map are proportionately sized based on the data value of each symbol.

To better understand your data, explore the spread of the data within the histogram (labeled 1). Here you can see the minimum, maximum, and average (x) values. Smart mapping spreads size over the full range of the data, but you can easily drag the bars or type custom values to add meaning to your map. If you wanted to highlight areas over a specific figure such as the national average, you can easily drag the lower bar or type the value you want to highlight.

You can also customize the sizes of your symbols using the size range options (labeled 2). To help your map look good at all scales, smart mapping adjusts the size automatically as you zoom in and out in the map.

Small adjustments to these size ranges can make a big difference in your map. In this example the areas with the highest percentages of Hispanic or Latino population are now emphasized with small changes to the size range.

Change the look of your symbols by going into the Symbol style options. Here, you can adjust the shape, color, outline, and more.

In this map, the circles were changed to squares, and a custom color was chosen from the color picker.

Another way to explore the patterns in your data is to use themes.

Here, the Above theme was used to emphasize the values above the average (which we can see in the histogram). This is an easy way to highlight the above-average features on the map.

Now let's take a look at the options within the Counts and Amounts (Color) style. Many of the options should look familiar.

Like we saw in the size options, the histogram is shown to help you better understand your data. However unlike the size options, you can see the two handles are not set at the minimum and max. Instead, smart mapping helps immediately reveal significant patterns on the map by spreading the data plus or minus one standard deviation from the average.

Within the symbol style options, there are many different color ramps to help you tell clear and meaningful stories about your data.

You can even narrow down the ramps by which basemaps they work best with and which colors they contain.

This helps you customize the colors of the map to the stories you want to tell.

Here we chose a ramp that is best for light backgrounds since we are using the Light Grey basemap.

To help you explore your data and tell new narratives, themes are a powerful way to emphasize different parts of your data. You saw the size themes earlier, and here we see the themes specific to mapping color.

If we change the theme to Above and Below, we can emphasize the highest and lowest values in our map. By default it will set the middle of the ramp to the average, but you can set this to any number that has meaning to you such as a threshold or goal.

Notice that the color ramp options for this theme all have a diverging pattern.

Each drawing style will have options specific to that style, so we highly encourage you to spend just a few minutes exploring them and trying different settings. You can always hit "Cancel" if you don't like the settings you chose.

Note that the examples in this story map use polygon features, but the concepts are fundamentally the same when mapping points or line features.

Let's recap the three steps for smart mapping:

1) Choose an attribute or multiple attributes to compare

2) Try a drawing style

3) Explore the style options

Now that you are familiar with the interface and these three steps, try smart mapping on your own data or try out the styles you saw in the maps above from  this Living Atlas layer .

Happy Mapping!

Want to learn more? Check out the following resources:

Notice that the styling options change as you choose different fields