Sound maps are nothing new but they are becoming increasingly popular as technology (such as Google Maps and Audioboo) are making their creation much easier. My interest in these stems from the Sounds Like Leigh-On-Sea project my brother is creating of our hometown (map below).
View Sounds Like Leigh-on-Sea in a larger map
There are several other larger-scale projects that have caught my eye recently. The London Sound Survey is one of the most mature projects with sounds from most of London, and recent plans to expand east along the Thames Estuary.
On a National Scale the Noise Futures Network and British Library have teamed up to create the UK Soundmap with the intention of creating a crowd-sourced soundscape of the UK. It has only recently been launched so there is space for many more contributions!
One of my favorite maps is from sonicwonders.org with its “travel guide to sonic wonders‘. Sounds can be rated as ‘worth a journey’, ‘worth a detour’ and ‘interesting’ and it can certainly add another dimension to holiday plans.
Worthy of a final mention is the BBC’s Audio Map of the World because it is the most extensive I have seen (it even has recordings from Antarctica!).
I think sound maps are yet to come of age. It would be nice to see the large scale creation of georeferenced sound recordings uploaded online in a similar way that photos are on Flickr. I think they could make for a really interesting data source and could produce some great maps and applications.
Much of the research we do in UCL Geography and CASA relates to London. One of the most interesting aspects of the city is its growth and development (you can see changes in London’s population density here). I was therefore excited to stumble on a scanned copy of “Maps of Old London” by Geraldine Milton (1908) (pdf or archive.org link). The book contains some great maps of London dating from as far back as the 16th Century. I have included several maps from the book below.
The 2010 UK election results have been visualised in hundreds of different ways. The map below is another contribution. We have used the RGB Colour Model to create the colours. The colour model works by mixing Red, Green and Blue to produce the final colour (more details below).We have given the Conservatives blue, Labour red and all other parties (incl. Liberal Democrats, Scottish National Party, Plaid Cymru, Green Party etc) green. How red, green or blue the constituency is depends on the proportion of the vote won by each of the three groups. So dark blue’s are very Conservative, purples are Conservative/ Labour, turquoise is Conservative/ Lib Dem (and others), yellows are others/ Labour and greys represent an even split between all three groups. It is a reasonably intuitive way of getting a general impression of the views of the people of the UK, and crucially includes all the votes that get ignored when a single colour is assigned to each constituency based on the party to win the seat. It is a shame that we have to group the Lib Dems. and smaller parties together so if you are interested in the exact break down of results you can see it here.
The Details
The proportion of each colour to go into the mix is controlled by a saturation value of between 0-255. To produce this value we re-scaled the percentage of the vote won by each of the groups to a value of between 0-255. So if Labour won 100% of the vote the red value would be 255 and the green and blue values would be assigned 0. If Labour (red) won approx 50% of the vote, the other parties (green) 10 % and conservatives (blue) 40% the rgb value would be (128, 25, 102) to produce apurple colour. A three way split (85, 85, 85) would be grey. To enhance the range of colours we have stretched them out a little to make the differences a little clearer. We know there are limitations of the RGB colour model but the UK elections is one of the few examples where there are generally three possible outcomes for each constituency, so the results lend themselves to this type of visualisation.
This post is a slight deviation from the major themes of this blog, but well worth it. I have embedded a couple of videos from Flat-e filmmakers. They specialize in what they call “architectural projection mapping” to project images onto buildings (the two examples below are castles) with stunning effects. The idea is a simple but its execution must be extremely complex to produce such impressive results. It is a great way utilize the exterior of buildings and a lot more exciting than fireworks! The first video is a projection onto Gorey Castle as part of the Branchage Festival.
I have just discovered the amazing visualisations produced for the BBC’s Britain from Above series. I have embedded some of my favourites- much of the data were collated and provided by CASA- see Digital Urban for details . The taxis in London (above) create a fantastic impression of the diurnal rhythms within the city. The air traffic over Britain animation (below) is just as impressive. I was especially taken by the amount of “stacking” that takes place over British airports.
The final is, for me, the most powerful as it illustrates just how important long distance communication has become:
As part of the research group that created the National Trust Surnames Profiler I have access to a comprehensive database of surnames in Great Britain. Most of my analysis on this database is spatial so I thought I would look at non-spatial way of illustrating the fact that in Britain the majority of people have a rare surname and that there are relatively few “popular”. This distribution is often referred to as having a long tail, as can be seen from the graph below. I find this graph lacks impact and novelty and it is hard to label a meaningful number of names along the x-axis. The surname clouds above have a greater impact by clearly demonstrating the popularity of a few surnames, such as Smith and Jones, in Britain and the large numbers of rarer surnames. I have only included the top 500 names for clarity. Comparisons between 1881 and 2001 are interesting. It would appear that the big names, such as Smith, dominate less now than they once did. The effects of migration also show in 2001 with names such as Patel, Kahn and Singh making an appearance. You can see how your name compares globally here. I am not sure if a word cloud would stand up to peer review for a journal but I think it would make a more interesting addition to presentations and posters than a simple line graph.
Using data from the excellent new London Data Store website I have produced a maps showing London’s population density for each decade between 1801 and 2001. An especially interesting pattern from the maps is that of increased population densities in central London until around 1951 and then a gradual decline until 2001. Outer London boroughs show a steady increase and then stabilise towards the end of the 20th Century. Below is an animated gif with the results. You may need to click on it to view the animation.
I recently had an interview with Radio Wales‘ “Good Evening Wales“. Following media interest in the migrations of some Welsh surnames such as “Jones”, BBC Wales wanted a little more information from our own World Names Profiler project. The project’s website allows visitors to type in their own surname and generate a map of it’s global distribution. You can also do an ethnicity search to simply map where Welsh names, for example, occur (see map below).
From the website you can find some interesting facts. For example, you are more likely to meet someone with a Welsh name in Chicago than London, and 6 out of the “top ten” regions with the most Welsh surnames (outside of Wales) occur beyond Europe. One of the most successful migrations (in terms of preserving the Welsh language and culture) was of course to Patagonia and this is shown by Argentina appearing in the top 10 most likely places to find many Welsh Surnames. So, although the main focus of yesterday’s interview was the movements of Welsh surnames within the UK, I think the global migrations we can track using Welsh surnames are far more interesting.
That said, to illustrate a little more the media interest in the Welsh surnames within the UK, I recommend people visit the National Trust Surname Profiler Website (link) that provides historical and contemporary maps of most surname distributions in the UK. The data behind this website have been the focus for much of my research and I have produced some maps related to Welsh names already. I have and included a couple with a little commentary below. If you would like to make your own you can visit the websites I mentioned above (Worldnames, National Trust).
The map above shows the % of the population with a Welsh surname (left) and an English surname (right). Darker brown means higher percentages and lighter colours represent lower percentages. You can see clearly how the more urban Southern Wales and the Welsh border have been infiltrated with English surnames.
I have featured the above map before on this blog. I have rescaled the UK so that the size of the area is proportional to the number of people with the Welsh surname “Lewis” that live there. As you can see from how much larger Wales has become you are still most likely to find the Lewis name in its country of origin.
Yesterday I presented the paper “Combining Historic Interpretations of the Great Britain Popualtion with Contemporary Spatial Analysis: the Case of Surnames” during the Geospatial Computing Workshop at the 5th IEEE International Conference on e-Science . You can download the extended abstract here and I have uploaded the complete presentation below. In later posts I will provide a summary of the other papers presented in what I thought was a very interesting session.
I read recently this article on the BBC News website. I thought the map they used (below) to show the areas of Britain with the largest domestic carbon footprints was a little uninspiring.
The colour scale was unclear with no explanation as to why the numbers jump around (the interval changes from 1 to 2) and appears to, for example, ignore the values that fall between 24 to 26 tonnes per household. Southern England is too red in the sense that it is hard to distinguish between areas with the highest emissions. I also feel that a more useful variable to plot is whether areas are increasing or decreasing their domestic carbon emissions. I understand why people are keen to highlight, for example, that David Cameron’s constituency is one of the top 40 most polluting, but it presents a static picture. It may be that he has heavily invested in household energy efficiency programs and dramatically reduced emissions compared to a few years ago- equally the constituency’s emissions could be increasing because he has avoided potentially unpopular environmental policies.
In response to my comments above I have logged on to the Guardian Data Blog to get hold of the UK Carbon Emissions by Local Authority Data they have published. In order to represent both total emissions and improvement between 2005 and 2007 I have opted to use cartograms. The first cartogram focusses on the Local Authority (LA) by rescaling their boundaries by the total domestic carbon emissions. The colours represent the % reduction or increase in emissions between 2005 and 2007. So areas that have been expanded a lot and coloured red are large domestic emitters and getting worse, whereas shrunken blue areas are already low domestic emitters that are reducing emissions. I have used Jenks’ Natural Breaks to decide the transitions from one colour to the next.
This second cartogram is subtly different because the boundaries are scaled by the average per captia emissions for each LA. An enlarged area is one where the people living there are relatively high emitters of carbon dioxide. Their total contribution from the entire LA population (as shown in the cartogram above) can still however be small compared to other areas in the country. Equally a large LA can appear as a large emitter in the above map simply because more people live there even though they may have very low per capita emissions as shown below. As before the colours represent the % increase or decrease in carbon emissions between 2005 and 2007. I don’t think these maps are perfect by any means but they present a more eye-catching interpretation of an important but heavily discussed issue.
