December Visualisation Blog: Crow Flies Vs. OD Paths  

December Visualisation Blog: Crow Flies Vs. OD Paths  

Crow Flies Vs. OD Paths  

In 2017, the UK Data Service published a report on commutes or more specifically “Location of usual residence and Place of work by Method of travel to work”. This utilised 2011 census data, and used people’s home and workplace, drew a straight line between the two and calculated the distance.  This is called “as the crow flies”, but if you are a regular reader of these blogs you, will know, we do not crow fly around here. 

Basemap regularly get asked about visualising this journey data, as it provides an insight into commuting locations which is important when looking at new housing developments.

The term as the ‘Crow Flies’ goes as far back as the 19th Century when it was first mentioned in the novel Oliver Twist. Since then, it has been regularly used to represent travel times between two points. And whilst it has been ever so popular within the transport industry, the ‘Crow Flies’ method is quickly becoming obsolete due to its inability to measure real travel times and distances. The reason for this is simply because… well, we aren’t crows. We can’t fly! Instead, we must factor in buildings, junctions, and road speeds, just to name a few. Which we all know play a large part in how we travel.   

So, we thought we would show you just how different a crow flies journey compares to an actual everyday commute using some cool maps! 

To do this, we firstly downloaded the Middle Layer Super Output Area (MSOA) shapefile from the UK Data Service. This was loaded into QGIS where the centroids for each MSOA was extracted, which became our origins/residences. Out of this layer a single point was selected as the destination/workplace, Bury St. Edmunds. Straight lines were generated for each origin point to create journeys imitating a ‘Crow Flies’ approach. The map below shows the resulting output for this.  

Here we can see the shortest distances travelled from residences to Bury St. Edmunds, and at a glance, the destination seems easily accessible with what looks like relatively short trips. As you and I both know, things are never this simple! As these are ‘Crow Flies’ results, we can expect that it isn’t showing actual distances travelled nor the time taken. See Tables 1 and 2 to find out more. 

We decided to take this one step further and find out what the true routes would look like for some of the journeys. For this, the MSOA points were exported from QGIS and loaded into TRACC, along with OS Highways and public transport data so that accessibility calculations could be run. Within TRACC there is a feature which produces OD Path Reports whilst running simultaneously calculations to show the exact breakdown of journeys. This was completed for both public transport and car rides. These reports are saved as .csv files which contain co-ordinate information, making them easy to convert into shapefiles when adding into GIS. With the help of the ‘Points to Path’ feature in QGIS we were able to produce the routes for every trip to Bury St. Edmunds from the path reports.  

A sample of the ‘Crow Flies’ journeys were compared against the results that had been generated in TRACC. See the comparison maps below to find out just how much the journeys differ! 

As already mentioned, the ‘Crow Flies’ distances seemed very short as would be inevitable when you’re excluding the road network from your commute. So, it is expected that both maps would show an immediate difference in their outputs, which shows just how much travel can be affected by factoring in roads.  

Office for National Statistics provides a ‘Method of travel to work’ dataset containing information about residents aged 16 to 74 as defined by their method of travel to work from Census 2011. It is summarized by the number of usual journeys between two points.  

The table below outlines the number of trips taken using the journey examples shown in the comparison maps. We also added in the various distances travelled and time taken for each as given by Crow Flies and TRACC so these can be compared in more detail.  

Table 1 

Table 2 

Combining these datasets can be very useful in providing additional context to how we travel between places. It also creates a clearer picture of the actual difference between ‘Crow Flies’ and the outputs generated in TRACC. Simply adding to the conclusion that ‘Crow Flies’ should no longer be used. We all know the frustration of a job hunt website that uses the crow flies method to calculate commutes, with large discrepancies of journey times within your set radius. 

Conclusion 

I think we can see why ‘Crow Flies’ has become outdated, as an inaccurate method of journey time calculation it was a necessary evil – but now we have technology on our side, doing all the hard work for us and even providing more accurate results. 

I mean, yes, being able to get up and fly to exotic destinations like Barbados would be the dream and certainly would do less damage to my pockets. Alas evolution has not gifted us this power and we must contend with rivers and roads on our journeys.