Smart Mapping with ArcGIS Online

What it is, and how and why to use it in higher education

Goals

  1. What is smart mapping?
  2. How can you teach and learn effectively with smart mapping?

What is smart mapping?

Smart mapping looks at the geometry and attribute information in the layer you want to map and suggests symbology that works best with your type of data: text fields, integers, floats, date fields, and combinations of these types. As a result, you can quickly start analyzing patterns and trends. This is why we call it "smart"!

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.

Smart mapping can be broken down into 3 simple steps:

  1. Choose attribute(s) to map.
  2. Examine your data that are now symbolized by the smart mapping capabilities.
  3. Optional: Explore more symbol options.

Examples of smart mapping:

Predominance:

See which field has the largest value by using predominance. Compare up to 10 attributes.

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Dot Density:

See where there are concentrations by visualizing the patterns as dots on the map.

Compare A to B:

Compare two fields as a ratio or percent.

Relationship:

Also known as bivariate mapping, this style shows two color patterns alongside each other to let you compare them.

Note: The activities in this story require an ArcGIS Named User account (a free public account will not work).


Activity 1: Applying smart mapping to a table of data

In this activity we will add a set of data collected in the field and use Smart Mapping techniques to uncover patterns and relationships in the data.

Here, we've mapped data about litter found around the streets of San Diego. This feature service was generated from a spreadsheet that could have been manually collected in the field, or via Survey123 or Field Maps.

Because this feature service was just published and added to the map, it has default symbology applied, showing the location only.

1) Use smart mapping

Open the Layers pane and make sure the Community litter survey layer is selected.

The Properties pane opens.

On the right toolbar, click Styles.

For Choose attributes, click the + Field button and choose Fast Food wrappers, then click Add.

Notice what smart mapping does with the data- instantly, the layer is redrawn using the Counts and Amounts (size) style. The more fast food wrappers were found at each location, the larger the symbol is.

2) Map multiple attributes

Fast food wrappers were just one of the types of litter collected at each location. Now, you'll map all the kinds of litter to see what kinds of patterns there might be.

For Choose attributes, click + Field and choose Cans, Glass bottles, Other plastic waste, Paper waste, and Plastic bottles. Click Add.

Now, the map redraws using the Predominant category style. The color of each point corresponds to the type of litter that was most frequently found at each location.

Scroll down until you see Charts and Size. Click Charts and Size, then click Style options.

For Charts (color), click Style options.

Click Symbol style. For Outline color, click the Edit button.

In the Select color window, choose a shade of black or type 000000 in the Hex # box. Close the Select color window.

For Outline transparency, drag the slider down to about 40% and for Outline width, drag the slider up to 2 px.

Close the Symbol style window.

In the Style options pane, scroll down until you see the Shape slider.

Drag the Shape slider about 3/4 of the way to the Donut shape.

Click Done three times.

Each symbol now shows the types of litter collected as a donut chart.

3) Apply Effects

On the right toolbar, click Effects.

In the Effects pane, click Drop shadow.

Close the Drop shadow window and close the Effects pane.

Now each symbol has a dark highlight around it to make it stand out off the map.

For example of a finished map,  look here. 


Activity 2: Examining Internet Access by Census Tract

In this activity we will map some social variables and use Smart Mapping techniques to uncover patterns and relationships in the data.

1) Explore the map

This map shows Internet Access data from the American Community Survey.

Note the bivariate smart mapping symbology:  we see 2 variables: color (%) and size (# of Households).

Click the Layers pane and expand the ACS Internet Access by Income Variables group.

Note patterns at different levels- zoom in and out to see different layers.

Zoom in to the census tract level for an area you are interested in.

On the left toolbar, click Legend.

2) Experiment with symbol color

In the Layers pane, click Tract. On the right toolbar, click Styles.

For Choose attributes, delete the Households without an Internet subscription field so you're just mapping the percent field. For Counts and Amounts (color), click Style Options and choose a different color ramp.

For Theme, click High to Low and choose Above and Below.

Observe what Above and Below shows you.

3) Experiment with symbol size

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

Change the size range to 3 to 33.

Observe how making the symbols smaller help you better visualize the patterns.

For an example of the finished map,  click here. 


Activity 3: Mapping the Relationship Between Drinking and Smoking

In this activity we will use Smart Mapping's relationship mapping techniques to uncover patterns and relationships in the data.

1) Explore the map

This map shows community health data from the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute. This data measures the health of nearly all counties using indicators such as child poverty, physical inactivity, access to primary care physicians, and more.

On the left toolbar, click Legend.

Currently, the map is showing the % Poor or fair health indicator. In this example, we are going to compare adults who smoke cigarettes and adults who are excessive drinkers.

2) Map multiple attributes

In the Layers pane, click the County Health Rankings 2022 layer to select it.

On the right toolbar, click Styles.

For Choose attributes, delete the % Poor or fair health field.

Click + Field and choose % Adult smoking. Click Add.

Click + Field again, and choose % Excessive Drinking. Click Add.

Now, the map shows the Color and size style. This shows some patterns in the data, but doesn't really allow comparisons.

Scroll down until you see the Relationship style.

Click Relationship, then click Style options.

The map redraws using the Relationship style. Counties in orange have high percentages of adults who reported excessive drinking, and counties in blue have high percentages of adults who reported smoking.

Counties in brown have a high amount of smokers and drinkers, while Utah stands out as a state in beige with few smokers or drinkers, as well as some sections of Idaho, Colorado, Kansas, Washington, and New Mexico.

3) Customize the relationship map

Click Symbol style, then click Fill color and explore the color blocks available.

Ramps can be filtered based on appropriateness for light or dark backgrounds or color-blind friendly. Note that you can also choose to Rotate the ramp colors.

You can also choose the size of the grid.

By default, this is set to a 3x3 grid which spreads the data values over 3 categories (low, middle, high). The corners show where the patterns are the strongest, so this helps differentiate the corners as areas that draw attention.

A 2x2 grid shows what is above or below average, and a 4x4 grid spreads the values over more colors. 

For Focus, choose whether to emphasize high values, or other combinations. The default is to show where both values are high (High - High), but you can change to one of the options from the Focus dropdown:

  • High values / Low Values
  • Low values / High Values
  • Low Values
  • None

For Labels, click High - High to make the text editable. Type High % Drinking - High % Smoking and press Enter.

Rename the other labels to better describe the legend.

See an example relationship map of these variables,  here .



Activity 4: Comparing Types of Power Plants

In this activity we will add a layer showing global power plants and compare where countries are using predominantly renewable energy versus fossil fuels.

1) Explore the map

This map shows global power plants by fuel.

On the left toolbar, click Legend.

Power plants are shown by type of fuel- renewables are shown with circles, and fossil fuel plants are shown with diamonds.

And we can see that the size of the symbol represents the number of features- this is based on a smart-mapping-adjacent functionality called clustering.

2) Explore clustering settings

Clustering is a kind of on-the-fly predominance mapping.

In the Layers pane, click Global Power Plants to select the layer.

On the right toolbar, click Clustering.

For Cluster radius, drag the slider to High.

Drag the Size range to Max.

Uncheck Enable clustering.

3) Compare fuel to generation

On the right toolbar, click Styles.

Click + Field and choose Estimated Annual Generation (GWh). Click Add.


Keep Learning!

  1. Some of these smart mapping hands-on activities are included in a new 10-activity "introduction to GIS" short course, here:  https://community.esri.com/t5/education-blog/an-introduction-to-gis-as-a-course-with-10-hands/ba-p/1204626 
  2. Smart mapping  lesson in the Learn ArcGIS Lesson Library .
  3.  How to smart map: Relationships . Essay with examples.
  4. Article: Smart Mapping Can Make Compelling Thematic Maps in Minutes | from ArcNews | Summer 2022.  https://www.esri.com/about/newsroom/arcnews/smart-mapping-can-make-compelling-thematic-maps-in-minutes/ 

 


Credits

All

Kathy Cappelli Breier, Kylie Donia, Jason Sawle, Joseph Kerski, Esri for instructional purposes