The organisation has a colour guide to ensure that, when referencing the tube lines, the correct colour is used. Somewhat surprisingly, the guide includes hexadecimal (i.e. web) colours for only a “safe” palette – i.e. colours which would definitely work in very old web browsers. They don’t list the “true” hexadecimal for the colours, even though, confusingly, the colour shown is the true one. I couldn’t find anywhere on the web that did this either, all in one place, so here below is a summary. I’ve also included the safe colours so you can see the difference – but don’t use these unless you have to.

The Mappiness project is run by one of CASA’s technology superstars Dr George MacKerron – it was his Ph.D project at LSE. The project, which is still going, aims to quantify happiness based on environmental factors, such as location, views and sound, as well as who people are with and what they are doing. Data is collected by volunteers downloading an iPhone app, which then pings them at random moments twice a day between 8am and 11pm (configurable) to ask them the questions and collect the data. Volunteer incentive is driven by having access to a personal webpage which contains all their collected data, visualised in a wealth of attractive graphs and maps.

I’ve been using the app since late October, it has been steadily pinging me twice a day since then, and most of the time I hear the familiar ‘ding ding’ and get around to recording the information. With around 160 responses, some interesting insights are now appearing, some(!) of which are non-personal enough to share here. The map above shows the locations where I was pinged, for the London area – yellow stars indicate where a photo was taken.

Here’s one, based on the general environment:

Perhaps more interesting is that I spend much less time outdoors than I thought. The app (by default) only asks for a picture if you are outdoors, so by counting the number of pictures that appear on my personal webpage – just 14 out of 161 – this in theory means that I spend only 8-9% of my waking life outside. This percentage will hopefully grow as summer approaches and things start to warm up again.

Because I don’t get to choose when to post the images, the photos are a good snapshot of my “everyday” outdoor view, rather than a nice or interesting place that I would specifically stop to photograph. Here’s a couple of my most recent ones:

One of Dr MacKerron’s current projects involves using Microsoft Kinect sensors for visualisation – this is my very tenuous link to allow me to post the image below, which is a 3D grid “photograph” of me at my desk, constructed from Kinect data.

Mappiness managed to choose to ping me this morning precisely at the moment that my bike chain snapped, on the way to work. Needless to say, a low score for happiness was recorded.

Map background Copyright Google.

Taking together all these data sets, I’ve used Routino and OpenStreetMap data to suggest likely routes taken for each recorded journey. This same set of data was used for Martin Zaltz Austwick’s excellent animation of bikes going around London streets. I’ve then built another set of data, an node/edge list, showing how many bike sharing bikes have probably travelled along each section of road. Finally, I’ve used node/edge visualiser Gephi and its Geo Layout plugin to visualise the sets of edges. The resulting maps here are presented below without embellishment, contextual information, scale or legend (for which I apologise – unfortunately this isn’t my current primary work focus so my time on it is restricted.)

For the two American schemes featured here, I have set the Routino profiler to not use trunk roads. Unlike most UK trunk roads, American trunk roads (“freeways”?) appear to be almost as big as our motorways, and I expect you wouldn’t find bikes on them. Unfortunately there are some gaps in the Washington DC data, which does show some cycle-lane bridges alongside such freeways, but these aren’t always connected to roads at either end or to other parts of the cycle network, so my router doesn’t discover them. This means that only a few crossings between Virginia and Washington DC are shown, whereas actually more direct ones are likely to be also in use. The profile also over-rewards cycleways – yes these are popular but probably not quite as popular as the distinctive one in the centre of Washington DC (15th Street North West) showing up as a very fat red line, suggests. The highlighting of other errors in the comments on this post is welcomed, I may optimise the profiler (or even edit OpenStreetMap a bit, if appropriate) and have another shot.

London:

Washington DC:

Boston:

…it sounds like one heck of a lot of running. But Murray Strain, one of Scotland’s top terrain runners, is counting on it for his basic training. He’s logging the whole venture, which is based on his trusty Edinburgh A-Z. If two adjacent streets with very similar names are nonetheless separated in the A-Z index by one on the far side of the city, it means a couple of legs right across the city.

Since he started the exercise last year Murray’s got through all the As, and is currently midway through the Bs. I’ve produce a couple of GEMMA maps, one showing the A-Bs (above, As are red and Bs are orange) and one showing the A-Gs (below, in rainbow order). That’s a lot of streets. N.B. The maps in fact show all linear features in the area in OpenStreetMap, so the odd named cycleway and waterway has crept in there too. But the ~95% of the coloured lines will be the streets that Murray will be run.

In order to produce the map, I’ve added a new feature to GEMMA – it now allows you specify only one desired geometry type, i.e. points, lines OR polygons, when adding an OpenStreetMap layer to your map. Previously, you got all three types, although you could reduce each to a dot if desired. This example also highlights the need for legends on the PDF maps that GEMMA produces – a larger coding change, so one that would make it into a future version 2 of GEMMA.

It shows the “footprint” of the docking stations making up 49 bike share systems around the world. The colours represent the empty/full state of each docking station at the particular moment in time when the image was made. The numbers show the total number of docking points – each docking station being made up of one or more docking points, each of which may or may not have a bike currently parked in it.

The geographies and topographies of the cities themselves inform the shape of the systems – particularly coastal cities (e.g. Nice, Rio, Barcelona, Miami Beach) and ones with large lakes mountains near their centres (e.g. Montreal).

A subtle but important point on the scaling: The scales of the systems (i.e. each system footprint and the spacing between docking stations) are roughly comparable – they actually vary by the cosine of the latitude – these means that the more tropical systems, e.g. Mexico City’s, appear to be up to ~20% smaller than they actually are, relative to the majority which are generally at temperate latitudes. However, the sizes of the circles themselves are directly comparable across all the systems, i.e each pixel on the graphic represents an equal number of docking points, regardless of which system it is in.

Christmas Day this year recorded far and away the highest ever simultaneous usage of the Barclays Cycle Hire bikes, aka the Boris Bikes, probably meaning it was the biggest number of hires in a single day too. The lack of any Christmas Day tube or bus service in the capital is the obvious reason for the huge usage spike. Previous popular days for the were the four tube strikes in late 2010. Both these events can be seen in the graph above. There is a diamond for each day, showing the difference between the maximum number of bikes available at a point in the day (typically at around 3am), and the minimum available (typically around 4pm for weekends or 9am/6pm for weekdays). Christmas Day was the big jump on the far right of the graph. The jump is much bigger than for Christmas Day 2010, as that day was pretty cold and snowy and only especially hardened tourists would be using the bikes then.

The top days are (measured by maximum closed-system simultaneous usage, i.e. maximum number of Boris Bikes out of the docks and rolling around the streets in a single moment, assuming no removal or addition by the operator that day):

• Sunday 25 December 2011 – 2065 (Christmas Day – no tubes or buses)
• Sunday 2 October 2011 – 1795 (Late summer heatwave)
• Thursday 3 February 2011 – 1791 (?)
• Tuesday 15 March 2011 – 1649 (Likely false result – mass removal)
• Saturday 1 October 2011 – 1627 (Late summer heatwave)

Actual total usage on each day is likely to be roughly proportional, and typically ~20 times the above numbers.

Note – please don’t read too much into the lowest usage days that appear on the graph. We’ve had quite a few power problems with our server room this year, and such low days may simply be when we were able to record little if any data. Large-scale bike removals and additions by the operator can also distort the results quite a bit, by perhaps up to 500 bikes a day. Mass additions to the system will depress the true result for that day, while mass removals can falsely inflate the numbers. It’s difficult to spot these, except by looking at the graph for the previous and following days, and comparing the max/min numbers.

Now available on the Bike Share Map are five extra French cities: Montpellier, St Etienne, Calais, Valence and Vannes, as well as Kunshan in China. I’m also now showing the relaunched bike share in Rio de Janeiro – yes, you can #bikeshare beside Copacabana Beach. This brings the total currently being visualised to 45 – not including several that have shut down for the winter and will be back, and some others where I’ve been asked not to collect the data. Thanks to Russell from the Bike-sharing Blog for the tip-offs for all of these.

So far, Montpellier, Rio and Kunshan are looking potentially very interesting, while there’s nothing much going on in Calais, St Etienne, Valence or Vannes.

I’ve also added some extra stats on each bike share, showing the number of docks and how many are completely empty and completely full – often surprisingly many after rush-hour for certain cities.

Finally and perhaps most importantly I’m now showing current weather conditions for most of the cities. The data is the METAR information for the major airport nearest each city, supplied and decoded by the NOAA Internet Weather Source. I’m picking up the reports every hour or so (some report less frequently) and caching them. Hopefully they will prove accurate. Currently it’s reporting 0°C in Toronto and 27°C in Rio de Janeiro.

[Updated with new connections.] Ever thought what the tube network would look like if you took out the expensive Zone 1? Me neither, until this morning, when I was wondering if it was possible to utilise my current “Boris Bike” bikeshare 24-hour membership to save a bit of money on commuting in to work.

Transport for London would really rather you didn’t take the tube into Zone 1. It’s often at capacity during the rush hour. The fares are priced accordingly – for example, to get a tube from Zone 3 to Zone 1, it costs £2.90 during the Peak Fare periods, compared with £1.40 if you only go from Zone 3 to Zone 2. Do that commute twice, and it’s a £3 saving missing out Zone 1, which more than makes up for the £1 Boris Bike 24-hour membership charge. So, I was wondering if it is viable to get off the tube a few stops early and Boris Bike the final mile or so.

Superimposing my London bike share map reveals directions from where such money-saving journeys may be possible. Plenty of opportunities from the north-west or the west, with St John’s Wood, Notting Hill and Earls Court having easy Boris Bike accessibility. Access from the south-west and south is also good, thanks to Vauxhall and Elephant & Castle. Things get a little trickier – as usual – in the south-east, where a 1km walk from Bermondsey, or a much longer walk from South Bermondsey are your only options – the region won’t even stand to benefit from the forthcoming scheme expansion. The east is also an option, with Whitechapel being very well stocked with Boris Bikes, and Wapping not being too far either. The east is set to benefit too from the imminent expansion of the Barclays Cycle Hire scheme, to use its full name, to cover all of Tower Hamlets. The north-east is OK, with Hoxton an option, although it’s a shame the docks don’t extend up to Highbury & Islington station, a major interchange. The north is also good, thanks to the legendary Mornington Crescent station.

Four of the Best Zone 2 & Bike Opportunities

• Mornington Crescent (Northern Line) – right beside a big docking station. Don’t go to Euston (Zone 1). It’s also easy to get to Mornington Crescent from the Overground, thanks to an unmarked but official Out of Station Interchange.
• Notting Hill Gate (Central Line) – the tube takes you to the top of the hill, then go east by Boris Bike.
• Earl’s Court (District/Piccadilly) – it’s a long way to Charing Cross, but if you don’t need to go that far, the bike is a good way to travel.
• Whitechapel (District/Hammersmith & City) – two big stands very close to the station, and an easy cycle along CS2 into the City.

So, all in all, not too bad. Whether it’s worth the extra time walking to a convenient docking station, and the worry of finding it all out of bikes, to save a pound or two, is another thing…

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See my Mapping London article for more detail about the No Zone 1 map. You can click on the map above for a larger version. An SVG version (i.e. editable) without the bike docking stations, is downloadable here although there is lots of missing detail beyond Zone 2.

The map was based on a Wikimedia/Wikipedia file, which I then augmented (to show the Overground and some selected regular railway lines) with OpenStreetMap data, by producing a map in GEMMA of railway=rail features. I also added some unmarked Out of Station Interchanges, thanks to this FOI request. Photos by Gnatallica, Clotheyes and Wwarby on Flickr.

[Update: An earlier version of the article and map made reference to Shoreditch High Street station which I incorrectly thought was in Zone 2 for "old East London Line" journeys - it appears this is not actually the case - the anomaly that I was misremembering is that for short journeys from the station, the Peak Fare increases do not apply. I've also updated the map a few times since posting this article, to add in a few missing stations and also the locations of the big terminus stations in London. I've also added some "Out of Station Interchanges" on the Overground - many of these aren't marked on official TfL maps, but are valid interchanges, i.e. you don't get charged for two journeys.]

One use of the OpenStreetMap feature highlighter in GEMMA, that was suggested by one of the participants at the JISCgeo Meeting earlier this week where we launched the web application, and augmented by a friend who was trying it out, was mapping the occurrences of the “High Street” road name – and a few regional variations, namely Main Street, Front Street, Market Street, Fore Street and The Street. Using GEMMA, and the high level of completion of OpenStreetMap in the UK and Ireland, allows us to visually show the spatial patterns of such street names.

Here’s a stitched-together screenshot of the GEMMA webpage showing the pattern throughout the UK and part of Ireland:

It turns out that Main Street is popular in the Midlands and in Scotland and Ireland, and Front Street is popular in the North-East of England (around Newcastle) while High Street is used nearly everywhere in the UK – but only sparingly in Ireland. Market Street is popular in the Manchester and Devon areas. Fore Street is popular in Cornwall and The Street very popular in Essex and Kent.

Note that many parts of Northern Ireland and the Republic of Ireland, are not yet well mapped in OpenStreetMap, so the street names will be missing in some parts here. The base-map is copyright Google and the street data is CC-By-SA OpenStreetMap.

You can see the live version of the map here.

I was intrigued by this tweet that appeared in my Twitter client this morning:

It’s one of those tweets that makes you go “That doesn’t sound right?”

Is Tokyo really a third of the size of England? It generally takes just under four hours by highish-speed train from London to the edge of England (Berwick) and a similar amount of time to get down to Cornwall. Even Wales is a good couple of hours away. I know they have ultra-fast trains in Japan but can Tokyo really be that big?

The link offers up the following map as proof, which appears to be based on Google Earth (very likely Copyright Google and its aerial imagery partners):

Some of the comments on the source article mention the key point that the Toyko metropolitan area, an administrative area, contains a large amount of rural land. The same is somewhat true of London – parts of the south-eastern fringe of the Greater London Authority (GLA) area are very definitely rural, and conversely built-up areas (Loughton) are outside of the GLA but part of the London continuous urban area and very much feel part of London – e.g. it’s on the tube network and in Zone 6.

Another example of administrative areas not coinciding with urban areas is that the City of Edinburgh council area extends well away from the city – but only to the west (i.e. to the Forth Bridge). In all other directions, the boundary is not far from the city bypass which is itself not far from the urban area, or there’s water in the way.

So a better comparison would be to visually compare the built-up areas of the two cities, first of all making sure that the scales are exactly the same and that the projections are appropriate for each city – I’m not saying this is not the case for the Google Earth example, although you do have to be careful with how Google Earth displays scales for, and projects, very large areas, as they are not always 100% rigorous.

I asked James of Spatial Analysis to have a quick look, as he had the data to hand, and he’s produced the rather lovely map which is at the top of this article. Thanks James! The dark grey areas are built-up areas and railways and the land and sea are also shown for context. A rough visual comparison of the map shows the urban area of Tokyo is maybe 3 times the size of London. This kind of equates to the population difference (8.5 million vs 31 million, using very rough numbers) and shows that Tokyo would fit quite snugly into Kent, rather than taking up much of southern England as the original statement implied – its own map, while exaggerating the urban area, also doesn’t quite cover a third of the nation.

(As an aside – it’s tricky to define exactly what a metropolitan area is – Wikipedia’s article for instance has very different numbers.)

So Tokyo is big – yes – but not nation-eating gigantic. I could probably just about cope with it.