Smart Mapping: Continuous Timeline and Age
Visualize your date/time attributes with color or size to emphasize new and old patterns
This guide introduces two methods of visualizing your date/time attributes within your maps: Age and Continuous Timeline. These methods can be shown in your maps with either color or size to highlight distinct patterns in your temporal data.
Smart mapping helps you create beautiful and informative maps, quickly. It sets the cartography of your map based on the significant values within your data. If your data contains attributes defined as the date field type, you can map them with the styles defined in this guide. When working with your temporal data in ArcGIS Online and ArcGIS Enterprise, choose the Styles option to work with smart mapping drawing styles that work with date/time attributes.
Mapping Time
With smart mapping, a date/time attribute, and your knowledge about the data, you can answer questions like: When did something happen? How long ago did something happen? Did something happen before or after a certain date? Which features are the oldest?
To help answer these questions by mapping them, you can visualize our date/time attributes in two ways:
- Continuous Timeline
- Age
Let's explore each method and learn how they can be applied to our own maps to help us answer questions about our temporal data.
Continuous Timeline
If you need to show when something happened, continuous timeline allows us to do so. This method uses either color or size to represent the dates associated with each feature on the map.
For example, if I need to map the buildings in Rotterdam by the year they were built, I can visualize the year by showing each building with a color to represent the newest and oldest buildings by their date. This helps us see the dates along a continuous timeline.
Showing time with continuous timeline helps us see when something happened, but you can easily transform the map with the smart mapping options to tell more specific stories. Let's walk through an example of how to explore different methods of mapping continuous time:
Use color to show when something happened
Use color to emphasize a point in time
Use size to emphasize patterns of the newest/oldest features
Continuous timeline (color)
When working with your data in ArcGIS Online and ArcGIS Enterprise, go to the Styles pane from the right toolbar to start mapping your date/time attributes.
It is best practice to start with a basemap that helps you tell the strongest narrative about your data. In this example, you can see the map uses the Human Geography Basemap from Living Atlas to create a neutral backdrop for our building footprints in Rotterdam, Netherlands.
To start mapping our data, go to Styles on the right toolbar and select the attribute you want to visualize. Here we want to map the year each building was built.
Smart mapping recognized that a date/time attribute was chosen, so it recommended drawing styles that appropriately represent this type of data.
By default, the map shows us the pattern of when each building was built over a continuous timeline. You can see that dark blue buildings were built more recently and lighter blue buildings were built much earlier.
While this is already a useful map, you can create even stronger narratives about this "Year Built" attribute by going into the style options.
Within the options, you can see the breakdown of the data within a histogram. You can also control settings such as the color ramp, the theme, and the transparency.
Themes allow us to emphasize important parts of our data. By default you can see the pattern from new to old, but there are many options to choose from.
For example, the Before and after theme allows us to show dates that fall before or after a specific date.
Using the Before and after theme, you can focus this map around an event that happened: the Rotterdam Blitz.
Center the map around an important date such as May 14, 1940 (the date of the blitz) and change the color ramp to alter the story.
Now, the map shows which buildings were built (or rebuilt) after the blitz in red and shows which buildings withstood the war in grey.
Continuous timeline (size)
You can also choose to display our dates over a continuous timeline by using size instead of color. Let's explore how to tell a similar story about these buildings using a different technique.
As we did before, it is recommended to go into the style options to customize the map beyond the defaults.
Using size, you can highlight the newest or oldest features in the map. By default this map is emphasizing the newest features within the data with the Above theme.
Adjust the date as we did before to highlight buildings newer than the Rotterdam Blitz. The symbology can be changed to different colors and symbols to help draw the reader's eye to the largest features.
As you did with the color options, you can transform the story by trying different themes.
If you adjust the theme to highlight features before May 14, 1940, now the map emphasizes the areas where buildings still stood after the war. This is similar to the map created earlier, but uses size instead of color to communicate the story.
Showing time over a continuous timeline helps us show the newest and oldest features on our maps. By going into the options and changing the settings and theme, you can start telling more directed narratives about the dates within our data.
Age
When you want to refer to the age of certain features on our map, you can use the Age drawing styles. Like you saw with continuous timeline, you can show age with color or size.
For example, the map below is an example of emergency response calls in Johns Creek, Georgia. The lightest orange colors represent the calls that took over 8 minutes for a response, while the darkest oranges represent the calls answered under 4 minutes. In life or death situations, these minutes can make an incredibly important impact.
Age of Response time for EMS calls in John's Creek, GA
This map uses the Age (color) drawing style within smart mapping by comparing two date attributes from the dataset: the time of the alarm and the time of arrival to the call. This is just one example where color can be used to visualize the age of spatial features on a map.
There are many ways to use age to tell informative stories about our date attributes. A few are:
Compare the age difference between two date attributes
Visualize the age between a date attribute and a specific date
Let's explore the Age drawing styles:
Age (color)
As you saw previously with the Continuous timeline example, start by selecting a date/time attribute within the Styles pane.
Here, you are seeing emergency response calls visualized by the time of the alarm. This map is using the Age (color) drawing style. By default, the style will show the age of each feature as the difference between the feature date attribute and the map creation date. This map uses the Human Geography Dark basemap from Living Atlas in order to use a dark neutral backdrop to draw attention to the features on the map.
As before, you can go into the Style options to show something more meaningful than the default settings.
The age can be the difference between a custom date or the difference between two date attributes.
This map makes more sense to compare two date attributes. You can see how long it took between the time an alarm was set and the time the emergency response team arrived.
This map adjust the units to show the age by minutes, since it makes the most sense for the map, but there are also options for seconds, hours, days, months, and years.
Based on the topic you're mapping, you can change the color ramp and symbol shape to better tell your map's story.
Age (size)
You can also use size to represent the age of our features.
Like you saw with the example with color, size can help us emphasize patterns in our data. This map uses the threshold of 6 minutes to emphasize the calls which took the longest to get a response.
If you want to see all calls that occurred before a certain time, you can instead use a custom date. To emphasize patterns, ask which features you want to highlight. This map now answers the question "where are the calls which happened over ten years ago from June 2021?"
Small changes to the symbol color and shape can help the patterns pop on the map.
Mapping Time & More
In this story, you've seen many different ways to represent our date/time attributes:
- Continuous timeline (color)
- Continuous timeline (size)
- Age (color)
- Age (size)
You can also combine these techniques with each other or with other attributes from your data to tell more complex stories. For example:
Color (age) and Size
In this example, age is used for the color on the map. Areas in darker shades of red had traffic accidents that were the more recent. The largest circles had more units involved in the accident. this example combines a numerical attribute and a temporal attribute to help answer the question "where were the most recent accidents which involved multiple vehicles?"
Open the legend at the bottom left to explore the map
Color and Size (age)
In this example showing building permits, the color of the map shows us how large the building is by the square footage. The size helps us see how old the permits are in months. The older they get, the larger they get.
Building Permits by Property Size and Age of Permit
Types and Size (age)
Combine your categorical data with your date attributes to explore the temporal aspect of your data. Categorical data is defined as an attribute that classifies your data into more than one category, such as different types of piping used for sewers. The map below uses color to show the different pipe types of sewer lines, while the size highlights the oldest ones using the age style. Right away you can see that many of the oldest sewer lines in Little Rock were made with VCP piping. This map helps us answer the question "Which types of sewer line pipes are the oldest?"
Open the legend at the bottom left to explore the map
With smart mapping doing the heavy lifting by taking the guesswork out of setting your map properties, you can freely explore new patterns and stories you did not know were present in the data.
Try it out today, and when ready share your maps with the hashtag #smartmapping and #ArcGISOnline.
