In the months since lockdown restrictions around Great Britain began to be relaxed in response to the Covid-19 pandemic, Britons valued the chance to GetOutside. During that time, subscribers to OS Maps have logged almost 700,000 routes in the app, showing whereabouts in the country they’ve been outdoors.
Do you know what an AONB is? Or an NSA? Most of us have heard of Britain’s National Parks (see all 15 here), but did you know that England and Wales also have 38 Areas of Outstanding Natural Beauty (AONB) and Scotland has 40 National Scenic Areas (NSAs)?
These scenic areas cover over 34,000 km2 of Great Britain (larger than the 23,000 km2 covered by our National Parks) and cover a huge variety of mountain, coastal and countryside landscapes. Our GeoDataViz team have been virtually exploring and comparing the landscapes with OS data and created a poster to showcase the AONB and NSAs.
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!
First off, thank you to everyone for your interest in the OS blog over 2019. At the end of each year, we like to find out the content you’ve enjoyed the most. Of course we always aim to publish content that you’ll find interesting, but crunching the numbers and working out the top 10 helps us understand what we should do more of. So, what has grabbed your attention the most throughout 2019? Let’s find out…
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
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.