Apply styles (Map Viewer)

Maps allow you to visualize data in a variety of ways. For example, you can visualize population data for countries as a sequence of colors, such as from light to dark, or as proportional circles, such as from small to large. This flexibility allows you to tell different stories and discover hidden patterns depending on how the data is presented. However, because mapmaking is so flexible, you must make decisions when there isn't always a single best answer.

With Map Viewer (formerly known as Map Viewer Beta), you can explore various styling options using smart mapping defaults. When you style map layers in Map Viewer, the nature of the data determines the styling options that appear by default in the Styles pane. You can then experiment with color ramps, line weights, transparency, symbols, and other graphic elements, and see your choices reflected immediately on the map.

To learn more about smart mapping in Map Viewer, see the How to Smart Map story.

Apply a style

The styling options provided for a layer are based on the type of data you are mapping. The available options depend on whether the feature layer is composed of point, line, or polygon features, or whether you are mapping imagery or raster data. For example, heat map styling options are available for a layer composed of points, but not for line or polygon layers. The options are also influenced by the type of attribute data associated with the layer. For example, a point feature may only have location information such as geographic coordinates but may also have categorical information such as tree species or numeric information such as air temperature. Styling options also vary depending on whether you want to show one or two attributes, such as revenue or population. Not every styling option can be used for every type of data. By analyzing these and other characteristics of the data, Map Viewer presents the best styling options.

Note:

Instead of styling a feature layer using explicit attributes in the layer, you can create a custom attribute expression written in ArcGIS Arcade to use for styling. This is available for most styles. For example, you can create an Arcade expression to derive a yearly sales figure for individual sales territories by summing the value of monthly sales fields. The yearly sales figures can then be represented as different-sized symbols on the map. You can also create an Arcade expression or edit an existing Arcade expression directly in Map Viewer. You can also use Arcade expressions when setting transparency for features or the rotation angle of symbols, as well as when configuring pop-ups and labels.

When you add a layer without any styling attached to it—for example, you add a hosted feature or imagery layer from its item page immediately after publishing—Map Viewer displays the layer with default styling applied. If you add a layer with existing styling applied, Map Viewer respects that styling. You can change the style of a supported layer at any time by clicking the Styles button on the Settings toolbar.

To apply a style or change the style of a feature layer, do the following:

Note:

For information about styling imagery layers, see Style imagery.

  1. Confirm that you are signed in and, if you want to save your changes, that you have privileges to create content.
  2. In Map Viewer, open the map containing the layer or add the layer directly.
  3. In the Layers pane, click the layer to select it.
  4. On the Settings (light) toolbar, click Styles Styles.
  5. In the Styles pane, do one of the following in the Choose attributes section:
    Note:

    You can skip this step if you want to show locations using a single symbol or map the locations of point features as a heat map.

    • Click Field, find and select the attribute, and click Add to style an attribute in the layer.
    • Click Expression and create a custom Arcade expression in the editor window, including providing a name, to style the layer.

      You can also use existing expressions to build new expressions; however, some variables may not work in all profiles—for example, an expression created for pop-ups may not work for styles. To use an existing expression, select it from the Existing tab in the editor window.

    Tip:

    If you need help with any of the Arcade functions, click Information Information next to the function in the editor window to see reference information about it.

  6. To style additional attributes or create more expressions, repeat the previous step.

    The style currently applied to the layer is selected in the Try a drawing style section.

  7. Optionally, select a different style. Choose a style based on what you want to show.

    For help choosing a style, see the Styles quick reference table.

    Note:

    Only the options that apply to the data appear. For example, if you only know the location of a feature, you can only use a single symbol or heat map, not size or color. However, if you have categorical or numeric information attached to those locations, smart mapping presents additional styling options.

    Some styles also include a Theme option. Themes allow you to experiment with various views of your data. The availability of themes depends on the smart mapping style you choose.

  8. Optionally, click Style options on the style card to customize the look of the layer.
    Tip:

    With Color and Size, Types and Size, Predominant Category and Size, Relationship and Size, Types and Size (age), and Color and Size (age), you apply styling options to each attribute. For example, if you choose the Types and Size style, choose options for Types (unique symbols) and Counts and Amounts (size).

  9. In the Style options pane, click Done when you finish customizing your style, or click Cancel to return to the Styles pane without saving your choices.
  10. In the Styles pane, click Done.
  11. On the Contents (dark) toolbar, click Save and open Save and open and click Save to save your styling changes to the map.

Styles quick reference

When you style a layer using smart mapping, the available styling options depend on the type of data you are mapping (point, line, polygon, or imagery) as well as the type of data attributes (numbers, categories, dates, and so on) and number of attributes you choose. Each style helps you tell a slightly different story and answer different questions with the data.

The following table provides a quick reference of the smart mapping styling options available for various types of data and some of the key questions you can answer using each style:

Data typeQuestions that smart mapping can answerAvailable smart mapping style

Location only

Examples: city service requests in Miami, white shark locations near New Zealand

  • Where are the features located?
  • How are the features distributed geographically?

One numeric attribute

Examples: above- and below-average childhood obesity rates, market value of parcels, annual average daily traffic

  • How do the features compare to each other based on numeric values?
  • Where are the highest and lowest values?
  • Which features are above and below a specific attribute value?

Two numeric attributes

Examples: number and rate of uninsured people, unemployment trend, richness and rarity of species

  • Where are the highest and lowest values?
  • How are the numeric attributes related?
  • What is the relationship between numeric totals and the rate or ratio?
  • Are there any outliers?
  • Which features have high values or low values for both attributes?
  • Which features have low values for one attribute and high values for the other attribute?
  • Where is the relationship pattern the strongest or weakest for each attribute?

Three numeric attributes

Example: funding for conservation and wetlands programs, farming programs, and total funding

  • How are the numeric attributes related?
  • Which features have high values or low values for both attributes?
  • Which features have low values for one attribute and high values for the other attribute?
  • Where is the relationship pattern the strongest or weakest for each attribute?

One or more numeric attributes (counts or amounts) with the same unit of measurement

Examples: distribution of various types of crime, distribution of unsheltered versus sheltered people who are homeless, distribution of population by race across the United States

  • How is the data distributed?
  • How does the distribution of one attribute compare to other attributes?

Two to ten related numeric attributes with the same unit of measurement

Examples: predominant ethnic population per census tract, predominant housing type by census tract and which tracts have the highest and lowest total housing units

  • Which attribute has the highest value compared to other related attributes for each feature? Which has the lowest value?
  • How much higher is the highest attribute value compared to other related attributes?
  • What is the sum of the attributes for each feature and how does it compare to the other features?

One category/type attribute

Example: wind turbines by manufacturer

  • How is the data distributed or summarized by category?

One category/type and one numeric attribute

Example: unemployed people by county

  • Where are the highest and lowest values?
  • How is the data distributed by category?

One date/time attribute

Examples: Rotterdam buildings built or rebuilt after the Rotterdam Blitz, oldest buildings in Rotterdam, emergency incident response times, age of code violation from complaint to compliance date, sewer lines by installation year

  • Where are older features and where are newer features?
  • Which features have dates that are before or after a key date?
  • Which features have a higher age (length of time between two dates) and which have a lower age?
  • What's the distribution of features by time period?

Two date/time attributes

Examples: relationship between the age of storm water structure inspections and inspection dates, relationship between age of code violation (how long between complaint and compliance) and how recently the violations occurred

  • Where are older features and where are newer features?
  • Which features have dates that are before or after a key date?
  • Which features have a higher age (length of time between two dates) and which have a lower age?
  • What is the relationship between the age of features and how old or new are they?

One date/time attribute and one numeric attribute

Example: most recent traffic accidents involving multiple cars, age of storm water structure inspections

  • Which features have a higher age (length of time between two dates) and which have a lower age?
  • What is the relationship between a feature's age and a numeric attribute value?

One date/time attribute and one category/type attribute

Example: sewer lines by type and number of years since installation

  • How is the data distributed by category?
  • Which features have a higher age (length of time between two dates) and which have a lower age?
  • What is the relationship between the age of a feature and its category?

Categorical raster

Example: land cover including forest, urban, and agriculture

  • How is the data distributed by category?

Multispectral imagery

Examples: multiband Landsat imagery, high to low elevation in Charlotte

  • What does the imaged landscape look like in real life?
  • Where are some specific features in the image?
  • Where are the highest and lowest values?

Continuous raster or imagery

Examples: United States temperatures, elevation in Iceland

  • What is the distribution of values?
  • Where are the highest and lowest values?
  • How might the values be grouped into ranges?
  • What does the shadow look like in elevation data?

Colormap

Example: Soil map with legend

  • What is the distribution of different soil types?
  • How are soil types associated with slope?
  • What is the distribution of landcover and landuse classes?
  • How do roads impact forest landcover over time?

Multidimensional Vector Field

Example: Classified ocean current direction and magnitude

  • What is the direction and magnitude of ocean currents?
  • What is the direction and magnitude of wind currents using the Beautfort Wind Scale?