Guest blog by Alasdair Rae, University of Sheffield
Thanks to the new Ordnance Survey Data Hub, it’s easier than ever for users to get their hands on the treasure trove of geographic data covering the length and breadth of Britain. In this article, I’ll explain how I used some of Ordnance Survey’s digital terrain model data to create a new map of the Scottish Highlands. I will also say a bit about the software and methods, and I’ve shared the data below so anyone who is interested can try it for themselves. But before that, let’s take a look back at the first ‘3D map’ of the Highlands.
The first ‘3D map’ of the Highlands
In a world where we have access to an abundance of information, good data visualisation is more important now than ever before. Our GeoDataViz team here at OS know this better than anyone. Here they talk us through their thematic mapping techniques and explain when and how these techniques should be used…
Mappy New Year! 2019 was a great year for cartography, especially geo data visualisation. We loved seeing such amazing maps and visuals being produced by some very talented people, and the standard just seems to be getting better and better. Inspired by all the brilliant work we’ve seen, we thought we’d pull together some of our favourites. There are too many to include so this list is by no means exhaustive, but we hope you enjoy our picks.
Surfing Saco Bay, Margot Carpenter
Created by independent cartographer Margot Carpenter, this stunning map depicts Maine’s Saco Bay. The detail is incredible, and we love how the map focuses on the bay’s underwater topography and wave dynamics and how they fuel the bays amazing surfing conditions. There is also a beautiful compass rose that illustrates wave height and a visualisation depicting how bathymetry and waves create surf!
As a self-proclaimed outdoor enthusiast, it’s no surprise our guest blogger Dan Harris is a Forward Planning Manager at the Cairngorms National Park Authority. In his spare time, he used our data to create a 3D LEGO map and in doing so, enthused many Twitter users. Here, he tells us about the project…
LEGO is an extremely engaging medium that can generate great enthusiasm in almost any subject, whether the audience is young or old. There are hundreds of examples of its use to promote subjects such as history, philosophy, economics, science and more, so I wanted to bring it to the world of cartography and use it to inspire engagement with mapping, landscape and place.
I’ve always really liked the way 3D relief maps can quickly and often dramatically convey the geography of an area. They’re popular and inspiring so to me, LEGO seemed like the ideal material from which to make my own; and where better to make one for than Scotland? With its mountains, islands and intricate coastline, it seemed to me to be the ideal subject. Plus, I live there and if it’s going to be displayed in my house, I want it to mean something to me.
One of my main objectives was to make the map using open data, so OS’s open datasets were an obvious solution. While I did consider other options, I decided that OS Terrain 50 DTM best suited my needs. To be fair, OS Terrain 50 is total excessive for a model of the resolution I had planned, but I wanted to use it so that in future I could create more detailed maps without having to process loads of new data. My map also includes a part of Northern Ireland, so I used the ALOS World 30m DSM to fill in that gap. Watercourses data came from the OS Open Zoomstack dataset, which is a great source of open data.
By Lucie Woellenstein, Graduate Data Scientist
Did you know that there are 50 motorways in Great Britain with over 8,300 km of roads and a whopping 666 junctions? How many junctions have you taken? Or will you be taking as you head off for the summer holidays? Ever tried to come off a motorway junction, only to find you’ve taken the wrong exit and are now heading in the wrong direction? Maybe you’ve driven through the famous ‘Spaghetti Junction’ in Birmingham, and wondered what it looks like from above? Or perhaps you’ve been perplexed at how the most complex of junctions somehow actually work?
Well here at Ordnance Survey, we’ve spent many hours over the years thinking about the interwoven laces of motorway junctions. Not from the perspective of a driver, but that of a cartographer. From data architects conceptually modelling how to capture data, to surveyors capturing the exact GPS locations of our roads, and to the cartographers that digitise the maps you use to travel along the motorways – a lot of thought goes into how to cartographically represent junctions in a way they make sense to the map reader.
Cartographically complex motorway junctions
Our OS Maps users created over 300,000 public routes across Great Britain in 2018 (covering some 2,950,000 miles…) and we were curious to see where you most (and least) enjoy exploring. Our Data Scientist Andrew Radburn set to work analysing the data before our Data Visualisation expert Charley Glynn set to work to showcase the results.
Analysing OS Maps route data
Tableau is a data visualisation software that is used for creating a wide range of different visualisation to interactively present data and obtain insights. It has a very intuitive user interface and you don’t need any coding knowledge to work with it. For this tutorial we will be using Tableau Public which can be downloaded here.
We will be creating a spider map or origin-destination map that shows paths between our origins (RNLI stations) and destinations (call-outs). All the data you will need for this tutorial can be found here.
On 28 February 1823, Sir William Hillary made an impassioned appeal to the nation, calling for a service dedicated to saving lives at sea. That service was to become the Royal National Lifeboat Institution (RNLI).
Did you know?
- There are 238 lifeboat stations around the coasts of Great Britain, Ireland, the Isle of Man and Channel Islands.
- Tower Lifeboat Station on the River Thames in London is the RNLI’s busiest.
- There are 349 lifeboats in the RNLI fleet.
- The RNLI have 4,966 volunteers.
- It cost £176.5m to run the RNLI in 2017.
Last week we looked at using QGIS to create some visualisations using data from the Royal National Lifeboat Institution (RNLI) and Ordnance Survey. This week we will be taking the same datasets and working with them within Kepler, Uber’s new open source geospatial analysis tool.
KEPLER (Pt 1)
Kepler is great for creating a range of different visualisations easily and quickly, and to begin with we are going to look at creating a visualisation depicting where in the UK most emergency call-outs are made. To do this we will need to download the RNLI Return of Service data.
In an emergency the importance of location is critical. Knowing the precise whereabouts of an incident can be the difference between life and death.
The Royal National Lifeboat Institution (RNLI) are the charity that saves lives at sea. Responsible for saving over 140,000 lives since their formation in 1824 they work with a dedicated team of volunteers, staff and community fundraisers. They allow us to enjoy our shorelines and water, safe in the knowledge that in an emergency they will be there to assist us.
There is a lot of data behind the lifesaving and in 2017 RNLI teamed up with ESRI to create an open data portal to help share some of this data.
Continuing our series to introduce some friendly faces from the people working at OS and showcase the wide variety of work we do, meet Joe Harrison. Joe joined OS on our graduate scheme in 2017 as a data scientist and has worked in a few areas of the business so far. If you’re a follower of the blog, you may recognise some of the project Joe’s worked on…
Hi, I’m Joe, one of the data science grads from the most recent graduate scheme. My first placement was an eight-month stay in the Consultancy & Technical Services team from September until the end of March. I then moved to the GeoDataViz team with Charley and Paul for a two-month placement.
Scottish Boundary Commission
During my first week in the team, Charley was contacted by the Scottish Boundary Commission who wanted advice on how to visualise the new Scottish constituency boundaries and the changes. I created a couple of examples using QGIS. I improved the clarity of the maps by reducing the number of colours, and by adding shadows to emphasise areas of interest.