The Challenge

The London Underground is one of the most extensive metro systems in the world, and the complex nature of the network led to the creation of one of the most well-known topological maps in the world. But… what if we wanted to not only see the network as it lies in London today, but also how it has evolved over time? This is the task I set myself when creating ‘A mapped history of the London Underground’ web app.

Given the extent of this task, I created a workflow to streamline the labour intensive parts, to keep track of progress and identify areas requiring intervention. The example we are stepping through in this blog uses ArcGIS Pro, but the workflow can be applied to a number of other ArcGIS applications.

The Project Foundations

Each segment and station of the Underground has a unique history which we need to link to the geography of the network.

The project started out looking like this, 11 lines and 269 stations.

If we were to segment a line and assign an opening year to it, we would be about 1/500th of the way through the project. Remembering which parts are complete would become quickly impossible. We can vastly simplify this process through the use of symbology and field calculations.

Data Processing

I will firstly focus on the stations. The stations and line layers both have two date fields, Open and Close. Most stations will only have an open year, as they are still operational. In the attribute table of the layer, we can add a text field called ‘IsComplete’ (you may choose to name yours differently). We then use the Calculate Field tool to choose what this column displays for each station. In this instance I used Python, but Arcade and VBScript would work just as well. The function checks if the Open column has a value and returns Complete. If Open is Null, Incomplete will be returned.

Our column will now appear as below. Any station with a value will return complete.

Symbolising Completeness

After repeating this process for our lines following the same steps, we can also go one further by symbolising the layers by their completeness. I used a neutral grey for incomplete parts of the network, and green for complete. At a glance we can now see how much of our network is complete.

Charting Progress

The final tool in the arsenal of this approach is the ability to chart progress. Keeping to a deadline can be tricky with a task like this, especially if like me, you have the tendency to fixate on smaller details. By right-clicking the layer and selecting Create Chart, we can make a pie chart using the IsComplete field as our category.

The only drawback to this approach is that the Calculate Field will not automatically update. So after a period of progress, we have to remember to calculate field again. Thankfully, unless your dataset is exceptionally large, this is a quick process. At the end of the workflow your data should be a sea of green, making missing areas easy to spot.

You could even use a bright red to make them even more noticeable, although your pie chart will let you know if there are any incomplete spots remaining. What’s more, you can select them directly from the chart.

Next steps

Once your pie chart is complete, you can then continue to the next (hopefully more exciting) part of your project!

Using a field calculation to check the completeness of other attributes can be taken far beyond the application we have just explored, and can be a very simple way to keep track of extensive projects.

This workflow helped to streamline and organise the formatting of the 160 year old history of the London Underground. Learn more about the other workings and techniques that went into A mapped history of the London Underground over on our Map Gallery.