Category Archives: London

OpenStreetMap: London Building Coverage

osm_londondetail

OpenStreetMap is still surprisingly incomplete when it comes to showing buildings for the London area, this is a real contrast to other places (e.g. Birmingham, New York City, Paris) when it comes to completeness of buildings, this is despite some good datasets (e.g Ordnance Survey OpenMap Local) including building outlines. It’s one reason why I used Ordnance Survey data (the Vector Map District product) rather than OpenStreetMap data for my North/South print.

The map below (click to view a larger version with readable labels and crisper detail, you may need to click it twice if your browser resizes it), and the extract above, show OpenStreetMap buildings in white, overlaid on OS OpenMap Local buildings, from the recent (March 2015) release, in red. The Greater London boundary is in blue. I’ve included the Multipolygon buildings (stored as relations in the OSM database), extracting them direct from OpenStreetMap using Overpass Turbo. The rest of the OSM buildings come via the QGIS OpenStreetMap plugin. The labels also come from OS OpenMap Local, which slightly concerningly for our National Mapping Agency, misspells Hampstead.

The spotty nature of the OSM coverage reveals individual contributions. For example, Swanley in the far south east of the map is comprehensively mapped, thanks presumably due to an enthusiastic local. West Clapham is also well mapped (it looks like a small-area bulk import here from OpenMap) but east Clapham is looking sparse. Sometimes, OpenStreetMap is better – often, the detail of the buildings that are mapped exceeds OpenMap’s. There are also a few cases where OSM correctly doesn’t map buildings which have been recently knocked down but the destruction hasn’t made it through to OpenMap yet, which typically can have a lag of a year. For example, the Heygate Estate in Elephant & Castle is now gone.

The relative lack of completeness of building data in OpenStreetMap, for London, where the project began in 2004, is – in fact – likely due to it being where the project began. London has always an active community, and it drew many of the capital’s roads and quite a few key buildings, long before most other cities were nearly as complete. As a result, when the Bing aerial imagery and official open datasets of building outlines became more recently available, mainly around 2010, there was a reluctance to use these newer tools to go over areas that had already been mapped. Bulk importing such data is a no-no if it means disturbing someone’s prior manual work, and updating and correcting an already mapped area (where the roads, at least, are drawn) is a lot less glamorous than adding in features to a blank canvas. As a result, London is only slowly gaining its buildings on OSM while other cities jumped ahead. Its size doesn’t help either – the city is a low density city and it has huge expanses of low, not particularly glamorous buildings.

An couple of OpenStreetMap indoor tracing parties might be all that’s needed to fix this and get London into shape. Then the OpenStreetMap jigsaw will look even more awesome.

osm_london_2mb

Click for a larger version. Data Copyright OpenStreetMap contributors (ODbL) and Crown Copyright and Database Right Ordnance Survey (OGL).

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High quality lithographic prints of London data, designed by Oliver O'Brien

The City of London Commute

Here’s a graphic I’ve made by taking a number of screenshots of DataShine Commute graphics, showing the different methods of travelling to work in the City of London, that is, the Square Mile area at the heart of London where hundreds of thousands and financial and other employees work.

All the maps are to the same scale and the thickness of the commuting blue lines, which represent the volume of commuters travelling between each home area and the City, are directly comparable across the maps (allowing for the fact that the translucent lines are superimposed on each other in many areas). I have superimposed the outline of the Greater London Authority area, of which the City of London is just a small part at the centre.

ttwf_cityoflondon

There’s lots of interesting patterns. Commuter rail dominates, followed by driving. Car passenger commutes are negligible. The biggest single flow in by train is not from another area of London, but from part of Brentwood in Essex. Taxi flows into the City mainly come from the west of Zone 1 (Mayfair, etc). Cyclists come from all directions, but particularly from the north/north-east. Motorbikes and mopeds, however, mainly come from the south-west (Fulham). The tube flow is from North London mainly, but that’s because that’s where the tubes are. Finally, the bus/coach graphic shows both good use throughout inner-city London (Zones 1-3) but also special commuter coaches that serve the Medway towns in Kent, as well as in Harlow and Oxford. “Other” shows a strong flow from the east – likely commuters getting into work by using the Thames Clipper services from Greenwich and the Isle of Dogs.

Try it out for your own area – click on a dot to see the flows. There is also a Scotland version although only for between local authorities, for now.

Click on the graphic above for a larger version. DataShine is part of the ESRC-funded BODMAS project at UCL. I’ll be talking about this map at the UKDS Census Applications conference tomorrow in Manchester.

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High quality lithographic prints of London data, designed by Oliver O'Brien

Tube Line Closure Map

anim

[Updated] The Tube Line Closure Map accesses Transport for London’s REST API for line disruption information (both live and planned) and uses the information there to animate a geographical vector map of the network, showing closed sections as lines flashing dots, with solid lines for unaffected parts. The idea is similar to TfL’s official disruption map, however the official one just colours in the disrupted links while greying out the working lines (or vice versa) which I think is less intuitive. My solution preserves the familiar line colours for both working and closed sections.

My inspiration was the New York City MTA’s Weekender disruptions map, because this also blinks things to alert the viewer to problems – in this case it blinks stations which are specially closed. Conversely the MTA’s Weekender maps is actually a Beck-style (or actually Vignelli) schematic whereas the regular MTA map is pseudo-geographical. I’ve gone the other way, my idea being that using a geographical map rather than an abstract schematic allows people to see walking routes and other alternatives, if their regular line is closed.

Technical details: I extended my OpenStreetMap-based network map, breaking it up so that every link between stations is treated separately, this allows the links to be referenced using the official station codes. Sequences of codes are supplied by the TfL API to indicate closed sections, and by comparing these sequences with the link codes, I can create a map that dynamically changes its look with the supplied data. The distruption data is pulled in via JQuery AJAX, and OpenLayers 3 is used to restyle the lines appropriately.

Unfortunately TfL’s feed doesn’t include station closure information – or rather, it does, but is not granular enough (i.e. it’s not on a line-by-line basis) or incorrect (Tufnell Park is shown only as “Part Closed” in the API, whereas it is properly closed for the next few months) – so I’m only showing line closures, not station closures. (I am now showing these, by doing free-text search in the description field for “is closed” and “be closed”.) One other interesting benefit of the map is it allows me to see that there are quite a lot of mistakes in TfL’s own feed – generally the map shows sections open that they are reporting as closed. There’s also a few quirks, e.g. the Waterloo & City Line is always shown as disrupted on Sundays (it has no Sunday service anyway) whereas the “Rominster” Line in the far eastern part of the network, which also has no Sunday service, is always shown as available. [Update – another quirk is the Goblin Line closure is not included, so I’ve had to add that in manually.]

Try it out

Street Trees of Southwark

southwarktrees_rotherhithe
Above is an excerpt of a large, coloured-dot based graphic showing the locations of street trees in Rotherhithe, part of the London Borough of Southwark in London, as released by them to the OpenStreetMap database back in 2010. You can download the full version (12MB PDF). Street trees are trees on public land managed by LB Southwark, and generally include lines of trees on the pavements of residential streets, as well as in council housing estates and public parks. By mapping just the trees, the street network and park locations are revealed, due to their linear pattern or clumping of many types of trees in a small area, respectively. Trees of the same genus have the same colour, on this graphic.

southwarktrees_thinWhy did I choose Southwark for this graphic? Well, it was at the time (and still is) the only London borough that had donated its street tree data in this way. It is also quite a green borough, with a high density of street trees, second only to Islington (which ironically has the smallest proportion of green space of any London borough). There are street tree databases for all the boroughs, but the data generally has some commercial value, and can also be quite sensitive (tree location data can useful for building planning and design, and the exact locations of trees can also be important for neighbourly disputes and other damage claims. It would of course be lovely to have a map of the whole of London – one exists, although it is not freely available. There are street tree maps of other cities, including this very pretty one of New York City by Jill Hubley. There’s also a not-so-nice but still worthy one for Washington DC.

Also well as a PDF version, you can download a zip-file containing a three files: a GeoJSON-format file of the 56000-odd street trees with their species and some other metadata, a QGIS style file for linking the species to the colours, and a QGIS project file if you just want to load it up straight away. You may alternatively prefer to get the data directly from OpenStreetMap itself, using a mechanism like Overpass Turbo.

A version of this map appears in London: The Information Capital, by James Cheshire and Oliver Urberti (who added an attractive colour key using the leaf shapes of each tree genus). You can see most of it below. I previously talked about another contribution I made to the same book, OpenStreetMappers of London, where I also detailed the process and released the data, so think of this post as a continuation of a very small series where I make available the data from my contributions to the book.

The data is Copyright OpenStreetMap contributors, 2015, under the Open Database Licence, and the origin of most of the data is a bulk-import supplied by Southwark Council. This data is dated from 2010. There are also some trees that were added manually before, and have been added manually since, by other OpenStreetMap contributors. These likely include some private trees (i.e. ones which are not “street” trees or otherwise appear on private land.) Many of these, and some of the council-data trees, don’t have information their genus/species, so appear as “Other” on the map – orange in the above extract.

southwarktrees_book

Out of Station Interchanges (OSIs)

osi_nlondon
Stations on the tube map with multiple lines are normally shown with a white circle (except where obscured by a disabled access blob) indicating connections where you can change lines there, while continuing on a single journey (and so not have to pay for two). However, there are a number of connections not shown on the map. These are Out of Station Interchanges (OSIs) and generally involve a walk out through ticket barriers, along a road or two, and back through more barriers. However, TfL will do the maths to ensure that you still only get charged for a single journey altogether – so long as you don’t spend too long a time between the two sets of barriers. TfL is quite secretive about these “hidden” free interchanges, likely because marking/highlighting the links and limit times would be tedious* so the current list is maintained by frequent Freedom of Information Requests. I’ve taken the current list, excluded interchanges with National Rail, and added the remaining (TfL to TfL) OSIs to my Tube Data Map. The OSIs are shown by white circles, connected together with white lines and black borders. There are a few more, where I’ve already joined OSI-linked stations as being actually in the same place. Sometimes you can leave and then reenter barriers within a single barriered area – for instance, you can leave the barriers at Bank and go back in them at Monument, without paying for two journeys (so long as you take less than 15 minutes to do so). However you can also get between the two stations while staying behind the barriers. N.B. If you change the date to 2019 then it shows the OSIs that will likely be added for Crossrail, when the central section starts running then.

Many of the OSIs are for links between the Underground and Overground, as the latter network is not otherwise particularly well connected. The longest Tfl-TfL OSI is from West Ruislip to Ickenham, in outer west London – it’s over a kilometre to walk between the two, but the link helps Central Line uses get easily to and from the transport hub at Uxbridge.

* They do however highlight a few at stations, e.g. Clapham High-Street to Clapham north. Some others have some street-signs pointing the way, e.g. Seven Sisters to South Tottenham.

Map background from HERE maps.

Taking the Scenic Route – Quantitatively?

A friend forwarded me this article which discusses this paper by researchers at the Yahoo Labs offices in Barcelona and the University of Turin. The basic idea is that they crowdsourced prettiness of places in central London, via either/or pairs photographs, to build up a field of attractiveness, then adjusted a router based on this map, to divert people along prettier, happier or quieter routes from A to B, comparing them with the shortest pedestrian routes. The data was augmented with Flickr photographs with associated locations and appropriate locations. and The article that featured this paper walked the routes and gives some commentary on the success.

Quantitatively building attractive routes is a great idea and one which is only possible with large amounts of user-submitted data – hence the photos. It reminds me of CycleStreets, whose journey planner, for cyclists, not only picks the quickest route, but adds in a quieter (and “best of both worlds”) alternative. Judging locations by their attractiveness also made me think of the (soon to be retired) ScenicOrNot project from MySociety which covered the whole of the UK, but at a much less fine-grained scale – and without the either/or normalisation.

In the particular example that the paper uses, the routes are calculated from Euston Square Station, which happens to be just around the corner from work here, to the Tate Modern gallery. It’s a little over 2 miles by the fastest route, and the alternatives calculated are only a little longer:
quercia_beauty
Above: Figure from http://dx.doi.org/10.1145/2631775.2631799

I really like the concept and hope it gets taken further – for more places and more cities. However, I would contend that local knowledge, for now, still wins the day. The scenic route misses out the Millennium Bridge which is surely one of the most scenic spots in all of London with its framed views to St Paul’s Cathedral and the Tate Modern itself. The quiet route does go this way, but the route is far from quiet when you consider the hordes of tourists normally near the cathedral and on the bridge. The pretty route goes down Kingsway which is a pretty ugly, heavily trafficked route, ignoring the nearby Lincoln Inns Fields, which is lovely. I think that the following, manually curated 3.0 mile route wins out as a much more beautiful route than the algorithmically calculated one:

beauty

Highlights include:

  • Walking through UCL’s Front Quad, through the university campus
  • Down Malet Street, past the imposing Senate House
  • Walking through the Great Hall of the British Museum
  • Bloomsbury Square garden and Lincoln’s Inn Fields
  • Chancery Lane
  • New Street Square (modern but attractive)
  • The statue of Hodge, Dr Johnson’s Cat
  • Wine Office Court, with the Ye Olde Cheshire Cheese Pub
  • Fleet Street and Ludgate Hill, with the famous view to St Pauls
  • The vista from St Paul’s Cathedral, across the Millennium Bridge to the Tate Modern.

Maps in this article are © Google Maps.

Seeing Red: 15 Ways the Boris Bikes of London Could be Better

santabikes

A big announcement for the “Boris Bikes” today, aka Barclays Cycle Hire. London’s bikeshare system, the second largest in the western world after Paris’s Velib and nearly five years old, will be rebranded as Santander Cycles, and the bikes with have a new, bright red branding – Santander’s corporate colour, and conveniently also London’s most famous colour. As well as the Santander logo, it looks like the “Santa Bikes” will have outlines of London’s icons – the above publicity photo showing the Tower of London and the Orbit, while another includes the Shard and Tower Bridge. A nice touch to remind people these are London’s bikes.

velibIt’s great that London’s system can attract “big” sponsors – £7m a year with the new deal – but another document that I spotted today reveals (on the last page) that, despite the sponsorship, London’s system runs at a large operating loss – this is all the more puzzling because other big bikeshare systems can (almost) cover their operating costs – including Washington DC’s which is both similar to London’s in some ways (a good core density, same bike/dock equipment) and different (coverage into the suburbs, rider incentives); and Paris’s (right), which has a very different funding model, and its own set of advantages (coverage throughout the city) and disadvantages (little incentive to expand/intensify). What are they doing right that London is not?

In financial year 2013/4, London’s bikeshare had operating costs of £24.3m. Over this time period, the maximum number of bikes that were available to hire, according to TfL’s Open Data Portal was 9471, on 26 March 2014. This represents a cost of just over £2500 per bike, for that year alone. If you look at it another way, each bike is typically used three times a day or ~1000 times a year, so that’s about £2.50 a journey, of which, very roughly, the sponsor pays about £0.50, the taxpayer £1 and the user about £1. In those terms it does sound better value but it’s still a surprisingly expensive system.

As operating costs, these don’t include the costs of buying the bikes or building the docking stations. Much of the cost therefore is likely ocurring in two places:

  1. Repairing the bikes – London’s system is wildly* successful, so each bike sees a lot of use every day, and the wear and tear is likely to be considerable. This is not helped by the manufacturers of the bikes going bust a couple of years ago – so there are no “new” ones out there to replace the older ones – New York City, which uses the same bikes, is suffering similar problems. (* Update: To clarify, based on a comment from BorisWatch, this assertion is a qualitative one, based on seeing huge numbers of the bikes in use, in certain places at certain times of the day. Doubtless, some do remain dormant for days.)
  2. Rebalancing/redistribution activity, operating a fleet of vehicles that move bikes around.

I have no great issues with the costs of the bikes – they are a public service and the costs are likely a fraction of the costs of maintaining the other public assets of roads, buses, railway lines – but it is frustrating to see, in the document I referred to earlier, that the main beneficiaries are in fact tourists (the Hyde Park docking stations consistently being the most popular), commuters (the docking stations around Waterloo are always popular on weekdays), and those Londoners lucky enough to live in Zone 1 and certain targeted parts of Zone 2 (south-west and east). Wouldn’t be great if all Londoners benefited from the system?

Here’s 15 ways that London’s bikeshare could be made better for Londoners (and indeed for all) – and maybe cheaper to operate too:

  1. Scrap almost all rebalancing activity. It’s very expensive (trucks, drivers, petrol), and I’m not convinced it is actually helping the system – in fact it might be making it worse. Most cycling flows in London are uni-directional – in to the centre in the morning, back out in the evening – or random (tourist activity). Both of these kinds of flows will, across a day, balance out on their own. Rebalancing disrupts these flows, removing the bikes from where they are needed later in the day (or the following morning) to address a short-term perceived imbalance that might not be real on-the-ground. An empty docking station is not a problem if no one wants to start a journey there. Plus, when the bikes are in sitting in vans, inevitably clogged in traffic, they are of no use to anyone. Revealingly, the distribution drivers went on strike in London a few months ago and basically everything carried on as normal. Some “lightweight” rebalancing, using cycle couriers and trailer, could help with some specific small-scale “pinch points”, or responding to special events such as heavy rainfall or a sporting/music event. New York uses cyclists/trailers to help with the rebalancing.
  2. Have a “guaranteed valet” service instead, like in New York. This operates for a certain number of key docking stations at certain times of the day, and guarantees that someone can start or finish their journey there. London already has this, to a certain extent, at some stations near Waterloo, but it would be good to highlight this more and have it at other key destinations. This “static” supply/demand management would be a much better use of the time of redistribution drivers.
  3. rrrHave “rider rewards“, like in Washington DC. Incentivise users to redistribute the bikes themselves, by allowing a free subsequent day’s credit (or free 60-minute journey extension) for journeys that start at a full docking station and end at an empty one. This would need to be designed with care to ensure “over-rebalancing”, or malicious marking of bikes as broken, was minimised. Everyone values the system in different ways, so some people benefit from a more naturally balanced system and others benefit from lower costs using it.
  4. Have more flexible user rules. Paris’s Velib has an enhanced membership “Passion” that allows free single journeys of up to 45 minutes rather than every 30 minutes. London, like Paris, is a large city, and the current 30 minute cutoff seems short and arbitrary, when considering most bikes are used around three times a day. Increasing the window would therefore have little impact on the overall distribution of the system and might in fact benefit it – because the journeys from the terminal stations to the City or the West End, which are the most distinctive flows seen, are acheived comfortably in under half an hour. In London, you have to wait 5 minutes between hires, but most systems (Paris, Boston, New York) don’t have this “timeout” period. To stop people “guarding” recently returned bikes for additional use, an alternative could be make it a 10 minute timeout but tie it to the specific docking station (or indeed a specific bike) rather than system-wide. Then, if people are prepared to switch bikes or docking stations, they can continue on longer journeys for free.
  5. Adjust performance metrics. TfL (and the sponsors) measure performance of the system in certain ways, such as the time a docking station remains empty at certain times of the day. I’m not sure that these are helpful – surely the principle metric of value (along with customer service resolution) is the number of journeys per time period and/or number of distinct users per time period. If these numbers go down, over a long period, something’s wrong. The performance metrics, as they stand, are perhaps encouraging the unnecessary and possibly harmful rebalancing activity, increasing costs with no actual benefit to the system.
  6. lyonRemove the density rule (one docking station every ~300 metres) except in Zone 1. Having high density in the centre and low density in the suburbs works well for many systems – e.g. Bordeaux, Lyon (above) and Washington DC, because it allows the system to be accessible to a much larger population, without flooding huge areas with expensive stations/bikes. An extreme example, this docking station is several miles from its nearest neighbour, in a US city.
  7. Build a docking station outside EVERY tube station, train station and bus station inside the North/South Circular (roughly, Zones 1-3). Yes, no matter how hilly* the area is, or how little existing cycling culture it has – stop assuming how people use bikes or who uses them! Bikeshare is a “last mile” transport option and it should be thought of as part of someone’s journey across London, and as a life benefit, not as a tourist attraction. The system should also look expand into these areas iteratively rather than having a “big bang” expansion by phases. It’s crazy that most of Hackney and Islington doesn’t have the bikeshare, despite having a very high cycling population. Wouldn’t be great if people without their own bikes could be part of the “cycling cafe culture” strong in these places? For other places that have never had a cycling culture, the addition of a docking station in a prominent space might encourage some there to try cycling for the first time. (*This version of the bikes could be useful.)
  8. Annual membership (currently £90) should be split into peak and off-peak (no journey starts from 6am-10am) memberships, the former increased to £120 and the latter decreased back to £45. Unlike the buses and trains, which are always full peak and pretty busy off-peak too, there is a big peak/offpeak split in demand for the bikes. Commuters get a really good deal, as it stands. Sure, it costs more than buying a very cheap bike, but actually you aren’t buying the use of a bike – you are buying the free servicing of the bike for a year, and free distribution of “your” bike to another part of central London, if you are going out in the evening. Commuters that use the bikes day-in-day-out should pay more. Utility users who use the bike to get to the shops, are the sorts that should be targetted more, with off-peak membership.
  9. officialmapA better online map *cough* of availability. The official map still doesn’t have at-a-glance availability. “Rainbow-board” type indications of availability in certain key areas of London would also be very useful. Weekday use, in particular, follows distinct and regular patterns in places.
  10. Better indication of where the nearest bikes/docks are, if you are at a full/empty docking station, i.e. a map with route indication to several docking stations nearby with availability.
  11. Better static signage of your nearest docking station. I see very few street signs pointing to the local docking station, even though they are hard-built into the ground and so generally are pretty permanent features.
  12. Move more services online, have a smaller help centre. A better view of journeys done (a personal map of journeys would be nice) and the ability to question overpayments/charges online.
  13. hubwayEncourage innovative use of the bikeshare data, via online competitions – e.g. Boston’s Hubway data visualisation competitions have had lots of great entries. These get further groups interested in the system and ways to improve it, and can produce great visuals to allow the operator/owner to demonstrate the reach and power of the system.
  14. Allow use of the system with contactless payment cards, and so integration with travelcards, daily TfL transport price caps etc. The system can’t use Oyster cards because of the need to have an ability to take a “block payment” charge for non-return of the bikes. But with contactless payment, this could be achieved. The cost of upgrading the docking points to take cards would be high, but such docking points are available and in use in many of the newer US systems that use the same technology.
  15. Requirement that all new housing developments above a certain size, in say Zone 1-3 London, including a docking station with at least one docking point per 20 residents and one new bike per 40 residents, either on their site or within 300m of their development boundary. (Update: Euan Mills mentions this is already is the case, within the current area. To clarify, I would like to see this beyond the current area, allowing an organic growth outwards and linking with the sparser tube station sites of point 7.)

London has got much right – it “went big” which is expensive but the only way to have a genuinely successful system that sees tens of thousands of journeys on most days. It also used a high-quality, rugged system that can (now) cope with the usage – again, an expensive option but absolutely necessary for it to work in the long term. It has also made much data available on the system, allowing for interesting research and increasing transparency. But it could be so much better still.

15094632681_a184a8a065_b
Washington DC’s systems – same technology as London’s, not that much smaller, but profitable.

London Boroughs and Tube Lines

piccadilly

How many of London’s 32 boroughs (& the City of London) would you pass through on a single end-to-end journey on the tube?

It turns out that if you travel the length of the Piccadilly Line (Uxbridge branch), then, in a single journey, you’ll pass through 14 boroughs (and stop at least once in all of them but Barnet). That’s more of London than if you travel on any single Crossrail journey, once it opens in 2018.

Line Branch # Boroughs
with Stops
# Boroughs
(Total)
Piccadilly to Uxbridge 13 14
Crossrail to Shenfield 10 13
Central to West Ruislip 11 12
Piccadilly to Heathrow 11 12
Central to Ealing Broadway 10 11
Northern High Barnet to Morden 10 10
District Upminster to Richmond/Ealing Broadway 10 10
Overground Richmond to Stratford 8 10
District Wimbledon to Barking 9 9
Hammersmith & City 9 9
Jubilee 9 9
Northern Edgware to Morden via Bank 9 9
Overground Clapham Junction to Stratford 8 9
Northern Edgware to Morden via Charing Cross 8 8
Bakerloo 5 8
Overground West Croydon to Highbury & Islington 7 7
Metropolitan 7 7
Circle 7 7
Victoria 6 7
Overground Clapham Junction to Highbury & Islington 6 7
Overground Gospel Oak to Barking 6 6
Overground Watford Junction to Euston 3 6
District Wimbledon to Edgware Road 5 5
DLR Bank to Lewisham/Woolwich Arsenal 4 4
Tramlink Wimbledon to New Addington 3 3
Waterloo & City 2 3
Cable Car 2 2

See for yourself at http://vis.oobrien.com/tube/#map.

Of course, if you are aiming to see a cross-section of London’s boroughs, in a rush, then the tube probably isn’t the best way, as you’ll be underground for quite a lot of the journey…

North/South – The Interactive Version.

northsouth_large

As a weekend project, I’ve made an interactive version of my London North/South artwork.

As well as the blue and red house silhouettes, assembled in QGIS, I’ve added in GeoJSON files of the River Thames (from Ordnance Survey Vector Map District, like the buildings) and of tube/DLR/Overground stations – the location/name/network data is from this GitHub file and I’ve applied a custom styling in OpenLayers 2, with station name styling inspired by the NYC Subway signs. The positional information comes from an OpenLayers control – I’m using a utility function to modify the output to use degrees, minutes and seconds. Finally, the naming popup is a set of UTFGrid JSON files (with 2-pixel resolution) based on OpenStreetMap data for polygons. Where the polygon has a building, leisure or waterway tag, I’m extracting a name, if available, and showing it. The coverage here is therefore only as good as building naming is in OpenStreetMap. I could potentially add in street names in the future.

Try it out here.

All the Tweets

Cross-posted from Mapping London, edited slightly.

This is a map of geolocated Tweets for the whole world – I’ve zoomed into London here. The map was created by Eric Fischer of Mapbox, who collected the tweets over several years. The place where each tweet is posted from is shown by a green dot. There are millions and millions of tweets on the global map – in fact, over 6.3 billion. The map is zoomable and the volume of tweets means that popular locations stand out even at a high zoom level. The dots are in fact vectors, so retain their clarity when you zoom right in. The map is interactive – pan around to explore it.

If you think this looks familiar, you’d be right. Mapping London has featured this kind of social media ‘dot-density mapping’ a few times before, including with Foursquare and Flickr (also Eric’s work), as well as colouring by language. The key difference with this latest map is the sheer volume of data. By collecting data on geolocated tweets over the course of several years, globally, Eric has assembled the most comprehensive map yet. He has also taken time to ensure the map looks good at multiple zoom levels, by varying the dot size and dot density. He’s also eliminated multiple tweets that happen at the exact same location, and reduced some of the artefacts and data quality issues (e.g. straight lines of constant latitude or longitude) to produce perhaps the cleanest Twitter dot-density map yet. Zooming out makes the map appear somewhat similar to the classic night-time satellite photos of the world, with the cities glowing brightly – here, London, Paris and Madrid are prominent:

activity_westeurope

However it should still be borne in mind that while maps of tweets bear some relationship to a regular population density map at small scales, at large scales they will show a bias towards places where Twitter users (who may be more likely to be affluent and younger than the general population) live, work and socialise. The popularity of the social network also varies considerably on a country-by-country basis. Some countries will block Twitter usage altogether. And in other countries, the use of geolocated tweets is much less popular, either due to popularity of applications that do not record location by default or a greater cultural awareness of privacy issues relating to revealing your location when you tweet.

activity_edinburgh

Above: Twitter activity in central Edinburgh, proving once and for all that the East End is a cooler place than the West End.

From the Mapbox blog. Found via Twitter, appropriately. Some of the background data is © OpenStreetMap contributors, and the map design and technology is © Mapbox.