Takeaway Hotspots

About the map

One of the toughest decisions in life usually occurs on a Saturday night, deciding which takeaway option is going to make or break your evening. Moreso if you live in a major city like London, the number of options can be overwhelming. So we asked ourselves, where is the worst place to live if you’re a little indecisive when choosing dinner options? This map has analysed a 15 minute ‘delivery time’ from each takeaway restaurant in London, then calculated how many different options each area will have access to. For certain areas, having over 500 takeaway options could lead to a few disagreements around the increasingly hungry dinner table.

Why it works

The map has an eye catching red-orange-yellow colour ramp to mark the ‘hotspot’ areas, reflecting the hottest part of a fire being yellow. The underlying analysis counts how many takeaway drivetimes overlap on any given point, then churns out the figure.

Requirements

  • Data and software

    Esri UK created the map using ArcGIS Pro 2.9, with data provided from Local Data Company.

  • Analysis

    The takeaway restaurants were plotted on the map and then using the network analysis tools in Pro, a 15 minute drivetime was calculated for each area. We felt this was an average time for takeaway deliveries based on several reports. Once we had created the drivetime areas, we then ran the ‘count overlapping features’ tool, to analyse how many takeaways are accessible for each area. Due to the large volume of data, we used a grid to iterate through the data, as otherwise the number of vertices was too high.

  • Time

    The process to create the output was fairly simple, but because we created thousands of overlapping polygons this increased the demand on our machine due to the sheer number of vertices.

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Tips and tricks

  • Grids

    To simplify our analysis and alleviate the CPU, we created a grid and iterated through areas of London to reduce the number of vertices per polygon.

  • Network

    We explored several network analysis methods, settling on using the Esri network, which costs credits but was more cost efficient when compared with a premium network.

  • Keep it simple!

    We stripped the map back to keep the cartography simple, but left in the roads layer (at a medium transparency) as this allows the user to navigate round and locate themselves quicker. This was the Human Geography Detail layer.

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Links & Resources

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Ahmad Raja, Graduate Consultant

Map Author

Ahmad Raja

Ahmad is a Graduate Consultant at Esri UK with a background in engineering and environmental economics. Although relatively new to the field, his fascination and commitment to GIS is constantly growing. In his free time, he enjoys playing chess and creative writing.

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