Create a map

You'll begin your map by signing into your ArcGIS account and opening a blank map. Then, you'll search ArcGIS Living Atlas of the World, Esri's authoritative collection of GIS data, for county health data related to adult obesity. Finally, you'll add this data to your map and use symbols to show demographic patterns.

Add Living Atlas data to a new map

You'll start by opening Map Viewer and finding the data you want to show on your map.

  1. Sign in to your ArcGIS Enterprise using a named user account.
  2. On the ribbon, click the Content tab and click New item.

    New item

  3. In the New item window, choose URL and for URL copy and paste the following link:

    https://services.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/2021_County_Health_Rankings/FeatureServer

    Add the feature layer

    The data comes from the 2022 County Health Rankings Key Findings Report, a trustworthy source. You know that adult obesity data is included in this county health data, so you'll add this layer to your map.

  4. Click Next, for Title type County Health Rankings 2021. Click Save.
  5. On the ribbon, click the Map tab.
    Note:

    Depending on your organizational and user settings, you may have opened Map Viewer Classic. ArcGIS Online offers two map viewers for viewing, using, and creating maps. For more information on the map viewers available and which to use, please see this FAQ.

    This tutorial uses Map Viewer.

  6. If necessary, on the ribbon, click Open in Map Viewer.

    Map Viewer opens.

    Map opens in Map Viewer

    Map Viewer includes two vertical toolbars-the Contents (dark) toolbar and the Settings (light) toolbar. Use the Contents toolbar to manage and view the map contents and work with the map. Use the Settings toolbar to access options for configuring and interacting with map layers and other map components.

    Tip:

    You can click the Expand or Collapse button at the bottom of each toolbar to expand or collapse them.

  7. In the Layers pane, click the Add button.

    Add button in the Layers pane

  8. In the Add layer pane, in the search box, type county health data and press Enter.

    The County Health Rankings 2022 feature layer appears in the list.

  9. Click Add. Click the Back button to hide the Add layer pane.

    Add to map button on the item details pane and the back button at the top of the Add layer pane

    The County Health Rankings feature layer is added to the map.

    County health rankings layer on the map

    The Layers pane shows that the layer is comprised of three scale-dependent feature layers: a nation layer, a state layer, and a county layer. The nation layer is visible at the current map scale, but you want to examine the county layer.

    Note:

    The extent you see may differ depending on the settings of your organization.

    Before exploring the map further, you'll make more space for the map by collapsing one of the toolbars.

  10. If necessary, at the bottom of the Settings toolbar, click Collapse. Click the Collapse button on the Contents toolbar.

    Collapse the Settings toolbar.

  11. On the map, zoom in until the county boundaries are visible. Pan the map until the contiguous United States (the states except Alaska and Hawaii) are visible and centered on the map.

    Map of county-level data

Explore data using dot density styling

Before you look specifically at adult obesity, you'll explore some of the other attribute fields in the layer using dot density styling. Applying different smart mapping styles such as dot density helps you see the data in different ways.

First, you'll change the basemap to better emphasize your data. Dark Gray Canvas is a good option to help your data stand out because it has fewer topographic features than the default Topographic basemap.

  1. On the Contents toolbar, click Basemap and choose Dark Gray Canvas.
    Note:

    You may see different basemaps depending on the configuration of your organization.

    Change the basemap to Dark Gray Canvas.

    The basemap changes.

  2. On the Contents toolbar, click Layers. Click the expand arrow for the County Health Rankings 2022 group layer and click the County layer to select it.

    Select the County layer in the Layers pane.

    A blue bar appears next to the layer to indicate that it is selected.

  3. On the Settings toolbar, click the Styles button.

    Styles button on the Settings toolbar.

    The Styles pane appears.

    The layer has been preconfigured with useful symbology to highlight one of the attributes in the data—poor or fair health self-reported rating. You can easily explore and display other attributes from the Styles pane.

  4. Under Choose attributes, click the remove button for the % Poor or fair health field.

    Remove the Poor or fair health attribute.

    The map is updated to show all counties in a single color.

  5. Click the Field button.

    Field button under Choose attributes in the Styles pane

    The Add fields window appears. You'll choose several population fields to explore the distribution of specific populations in the United States.

  6. In the Add fields window, click the sort button and select Display name.

    Select Display name from the sort drop-down menu.

  7. In the search bar, type population and press Enter.

    A filtered list shows fields related to population.

  8. In the attribute list, scroll down and click to select the following fields:

    • Asian population
    • Count of American Indian & Alaska Native population
    • Count of Hispanic population
    • Count of Non-Hispanic Black population
    • Native Hawaiian/Other Pacific Islander population
    • Non-Hispanic White population

    Choose race and ethnicity related attribute fields to symbolize.

  9. Click Add.

    The map updates to show the population attribute fields you selected.

    Map showing the predominant variable for each county

    You'll choose a different smart mapping style to view the populations in a different way.

  10. In the Styles pane, under Pick a style, scroll down and click the Information button of the Dot Density style.

    Dot density explanation

    A pop-up appears with more information about the Dot Density style and when to use it. Dot Density visualizes the distribution of one attribute or visually compare multiple attributes on a map.

  11. Close the When to use Dot Density pop-up and click the Dot Density drawing style thumbnail.

    The map updates to show the five population attributes represented with different-colored dots. Your map and legend may look slightly different depending on the current map zoom level.

    Dot density layer legend

    You'll change the dot colors by selecting a different color ramp.

  12. In the Styles pane, for Dot Density, click Style options.

    Dot Density style options

  13. For Symbol style, click the color ramp. In the Symbol style window that appears, click Dot color. In the Ramp window, choose the Fruit Basket ramp. (To see the name of a color ramp, point to it.)

    Choose the fruit basket color ramp.
    Tip:

    You can also change the dot colors by clicking the colored dots under Legend in the Style options pane.

    The map updates to reflect the new ramp you selected. Next, you'll specify what each dot represents on the map. Because your data is population data, the dots represent people.

  14. In the Ramp window, click Done and close the Symbol style window.
  15. On the Style options pane, for Dots represent, type people and press Enter.

    Dots on the map represent people.

    The legend updates to indicate the number of people represented by 1 dot. This value will be different depending on your current map zoom level.

  16. Adjust the dot value using the slider to explore different levels of representation on the map.

    Adjust the dot value to show more or less people per dot.

    The map and legend update dynamically.

    Tip:

    To make your map easier to interpret, you can also click the dot value and type a new value to input a rounded number.

  17. In the Style options pane, click Done twice.
  18. Zoom and pan the map to examine the distribution and density patterns across the United States.

Interpret the data

Now that you've explored some of the population attributes in the data, you'll turn your attention to adult obesity. Before focusing on Alabama, you'll explore national patterns to better understand the adult obesity situation in the United States. To do this, you will change the style of your data layer to show counties with higher and lower adult obesity rates using different colors.

Use smart mapping to discover national obesity patterns

Now you'll choose population and obesity data to map. These attributes are also inside the County Health Rankings 2022 layer. Unlike when you mapped the demographic data, for obesity data you'll use a single color ramp. Then, you'll symbolize the data so that counties with percentages above the national average stand out.

  1. If necessary, on the Contents toolbar, click Layers. In the Layers pane, expand the group layer and click the County layer to select it.
  2. In the Styles pane, under Choose attributes, remove all the population fields you selected previously except Non-Hispanic White population.

    Non-Hispanic white population attribute remaining under Choose attributes in the Styles pane

    You'll replace the remaining field with a field containing adult obesity rates.

  3. Click the Non-Hispanic White population field. In the Replace field window, in the Search fields box, type obesity.

    A filtered list of fields shows fields related to obesity.

  4. Next to % Adult obesity, click the More information button.

    More information button for the % Adult obesity field in the Replace field window

    Information about the % Adult obesity field is displayed.

  5. Read the field information. When finished, click the Back button.

    You'll explore this field in your map.

  6. Click % Adult obesity to select it and click Replace.

    The counties are automatically styled with a high to low color ramp.

    Map updates to show the % Adult obesity data by Counts and Amounts (color)

    Note:

    The colors on your map may look different.

    The legend explains the distribution of the colors. In the lightest colored counties, adult obesity rates are higher than 40. In the darkest ones, rates are lower than 31.5. Obesity rates are highest in many of the counties in the southeast.

  7. Click the Layers button to close the Layers pane and get a better view of the map.

    You can view a histogram to better understand the distribution of values.

  8. In the Styles pane, for Counts and Amounts (color), click Style options.

    Style options for Counts and Amounts (color under Pick a style

    The Counts and Amounts (color) pane appears. It contains a histogram.

    Histogram of obesity rates

    The histogram shows a maximum value of 51 and a minimum value of 16.4. The average value is 35.7, as denoted by the x̅ symbol. This is different from the national average of 41.9 percent in a 2019-2020 report by the Centers for Disease Control and Prevention (CDC). The average of your data treats all counties as equal, meaning it does not account for population differences between counties. The CDC's average does account for population differences, which is why the averages are different.

    The values of 40.01 and 31.39 on the side of the histogram represent one standard deviation above and below the average. They were assigned as the cutoffs for the darkest and lightest colors. This default statistical classification is fine, but you can also change the settings to uncover more patterns.

  9. For Theme, choose Above and below.

    Above and below color ramp

    Your map changes to reflect the new style. Now two distinct colors are used to represent values above and below the average. The cutoffs for the darkest and lightest colors remain the same, but a new handle has been added to the histogram with a value of 35.7, an approximation of the average.

    You'll adjust the histogram to use the national average instead of the data average.

  10. On the histogram, click the value of the top handle, type 45 and press Enter. Click the middle handle and type 41.9. Press Enter.

    The top break adjusted to 45 and the middle break on histogram adjusted to 41.9

    The values of the handles on the histogram change and the colors of the counties adjust on the map. Now the values above the national average are drawn in one color while the values below the national average are drawn in another color.

    Note:

    Click the center handle of the histogram and drag the handles up and down to dynamically adjust the map display.

    Next, you'll apply a different color ramp to make the data stand out better against the dark basemap.

  11. For Symbol style, click the color ramp.
  12. In the Symbol style window, click Fill color.
  13. In the Ramp window, click All color ramps and choose Best for dark backgrounds. Click the Blue and Yellow 9 color ramp.

    Best color ramps for dark backgrounds.

    The map and histogram update with the new style. You'll make a couple more style changes to fine-tune the story you want the map to tell.

  14. In the Ramp window, click Done.
  15. In the Symbol style window, for Outline color, click the no color button.

    Turn off the

    The county boundaries are now invisible on the map.

  16. Close the Symbol style window. In the Style options pane, under the color ramp, click the Flip ramp colors button.

    Flip the color ramp to show values above average in yellow.

    Counties with obesity rates higher than the national average now stand out clearly in yellow.

  17. At the bottom of the Style options pane, click Done and click Done again.

    Now that you've styled your map, you'll save it.

  18. On the Contents (dark) toolbar, click Save and open and click Save as. In the Save map window, enter the following information:

    • For Title, type Adult obesity rates by county, 2020.
    • For Tags, type obesity rate, adults, counties, and United States, pressing Enter after each word.
    • For Summary, type This map shows which United States counties have obesity rates that are above and below the national average in 2020.

    Note:

    The County Health Rankings 2022 layer represents data most recently available in 2022. At this time, the latest data available for national rates of adult obesity was data from 2020. It is important to verify the year data represents.

    Save the map

  19. Click Save.

    The map is saved.

Configure pop-ups

The County Health Rankings 2022 layer includes preconfigured pop-ups that provide general health and life expectancy information. However, the focus of your map is adult obesity rates per county, so you'll customize the pop-up to highlight this information.

  1. Click any county on the map to open its pop-up.

    The preconfigured pop-up shows health outcomes, health factors, and life expectancy information for the county.

  2. Close the pop-up. On the Layers pane, confirm that the County is selected.
  3. On the Settings toolbar, click the Pop-ups button.

    Pop-up on the Settings toolbar

    The Pop-ups pane appears. You can configure the pop-up's title and text and add more content. You'll keep the pre-configured title but create a new text content type with some explanatory text and fields, including the field for adult obesity percentage.

    First, you'll remove the existing Text content.

  4. For the Text content type, click the Options button and choose Delete.

    Delete the Text content in the Pop-ups pane

    The content is removed.

    You'll add new Text content.

  5. Click Add content.

    Add content to the pop-up

    You can add Attributes content, Image content, or Text content types. You can add as many of these content types as you want and change their order as needed by dragging them in the configuration window.

  6. Under Content, click Text.

    (text)Add text to the pop-up.

    A text configuration window appears.

  7. Type the following text: The adult obesity rate (body mass index of 30 or more) in

    Next, you'll add attribute fields to pull in the county and state names. Inserting an attribute field allows you to display feature-specific information in the pop-up. For example, a county field displays the name of the county you clicked on the map, as you can see in the preconfigured pop-up title.

    Attribute fields are surrounded by curly braces { }. Typing a curly brace in the text gives you a list of fields to select.

  8. Press the spacebar and type {name.

    The file list updates based on the text you entered.

  9. From the list that appears, choose Name {county}.

    County name variable in pop-up

  10. After {county}, type a comma, a space, and type {Stat. From the field list that appears, choose State {STATE}.

    The text box now contains the following text:

    The adult obesity rate (body mass index of 30 or more) in {county}, {STATE}

    Next, you'll add the field for adult obesity rate.

  11. After {STATE}, add a comma and a space and type the following text: was {Adult
  12. From the list that appears, choose % Adult obesity {v011_rawvalue}.

    The Adult obesity attribute field is added to the pop-up. The field notation {v011_rawvalue} is the field name that was assigned to this attribute in the data.

  13. Type in 2020.

    Finished pop-up message

    The final text that should be in the text box is as follows:

    The adult obesity rate (body mass index of 30 or more) in {county}, {STATE}, was {v011_rawvalue} in 2020.

  14. Click OK. On the map, click any county.

    Finished pop-up content.

    The pop-up has been updated.

  15. Close the pop-up. Click the Configure pop-ups button to close the pop-up configuration pane.

Filter data to inform policy intervention

The national map you created provides important context for the issue of adult obesity across the United States. Next, you'll use a filter to help you focus on the counties in your state (Alabama) that are most in need of policy intervention to reduce adult obesity.

  1. On the Layers pane, ensure the County layer is selected.
  2. On the Settings toolbar, click the Filter button.

    Filter the data

    A filter uses an expression to determine which features to show on the map. You can create expressions using specific attributes.

  3. In the Filter pane, click Add expression.
  4. Click the first expression field box.

    First box in the Expression

    The Replace field window appears.

  5. In the Search fields box, type state. Click the State field and click Replace.

    Replace the existing value with the State field.

  6. In the Filter pane, click the third drop-down menu. Search for and choose AL.

    Select AL as the state value.

    The map updates to highlight counties in Alabama. All other counties have been filtered out and are now shown in gray.

  7. At the bottom of the Filter pane, click Save.

    Save at the bottom of the Filter pane

  8. If necessary, zoom in to Alabama.

    The filter is fully applied, and the map only shows Alabama counties. Several counties are drawn in different shades of yellow, representing varying degrees of adult obesity rates that are higher than the national average.

    Zoom to the state of Alabama.

    Next, you'll add another expression to your filter to highlight counties that have more limited access to healthy foods. This is often a factor that affects obesity rates.

  9. On the Settings toolbar, click the Filter button.
  10. In the Filter pane, click Add expression.

    A new empty expression appears. The Filter results menu is displayed at the top of the pane.

  11. For Filter results, keep the default of Match all expressions.

    Match all expressions.

    Choosing this option ensures that only the features that match all the filter expressions will be displayed on the map.

  12. For the new expression, click the first expression field box.
  13. In the Replace field window, type grocery store and click % population who are low-income and do not live close to a grocery store. Click Replace.

    You want to identify counties in Alabama with a percentage that is the same or higher than the average.

  14. Confirm that is at least is chosen.

    Filter areas with limited access to healthy food

    The third box automatically displays a value of 8.5. This value is the average percentage calculated from the data. The map displays the filtered results.

    A histogram shows the breakdown of the data. Dragging the handle on the histogram will update the filter automatically. You'll leave the value unchanged.

    Note:

    You can click Add expression again to dynamically filter the data further. For example, you can add an expression that includes the Access to exercise opportunities attribute field to identify counties in Alabama that have lower than average access to adequate locations for physical activity.

  15. In the Filter pane, click Save.

    Your policy map displays only the features that match both filter expressions you created: counties in Alabama and lower than average access to healthy foods.

    Filtered view of Alabama

    The counties in yellow also have higher than average adult obesity rates, reflecting the styling options you applied earlier. These are the counties you want to consider for policy intervention.

  16. Save the map.

The map is saved. You can now share it with others in your organization or with the public. To do so, click Share map on the Contents toolbar and choose the sharing options you want. For more information about sharing content, see Share items.

Tip:

A good way to share your map is by publishing a web app. A web app provides a simple way to view and interact with your map and calls attention to its most important details. To create a web app from Map Viewer, click Create app and click Instant Apps. On the Instant Apps page, choose a suitable app, such as Media Map. Click Preview to test and publish with default settings or click Choose to create and configure the app to make changes.

In this tutorial, you used Map Viewer to create a policy map about adult obesity in the United States. You added a layer from ArcGIS Living Atlas of the World, styled it to show where adult obesity rates are higher and lower than the national average, and configured informative pop-ups. You then filtered the data to focus on priority counties in Alabama for policy intervention to share with members of your agency.

You can find more tutorials in the tutorial gallery.