As 2011 draws to a close it is worth reflecting on what, I think, has been a defining year for mapping and spatial analysis. Geographic data have become open, big, and widely available, leading to the production of new and interesting maps on an almost daily basis. The increasing utilisation of technology such as Google Fusion Tables has made it easier than ever to map data. Sadly the number of bad maps is on the increase as a result (largely thanks to the web’s preference for the Mercator projection and push-pins) and I hope things will improve (over to you Google!) next year. To inspire another year of mapping, and in no particular order, here is the spatialanalysis “Best of 2011″. The maps here have been popular, engaged users, innovated, and raised the bar for cartographic standards. I bet I have missed some so feel free to link to your best map in the comments section.

Paul Butler’s Facebook Connections Map

This just sneaks in as it was produced in December 2010. The map is important for what it doesn’t show (most of Africa for example) rather than what it does. It has served as an inspiration for many others, and raised the bar in terms of the detail and extent of social media mapping.

National Geographic Surnames Map

I think the National Geographic Surnames Map is one of an increasing number of brilliant typographic maps that have been produced in the past year.  Typographic maps can show many variables (using colour, font size etc) and are often instantly engaging. This one was especially popular alongside its “sister” map of London Surnames.

Galaxy Survey Fly Through 

I really like this video as it serves to demonstrate just how vast the universe is. I spend my life mapping a few things over relatively small geographic areas and there is plenty for me to do. We have barely even started mapping the universe and I think this video captures the immensity of the undertaking.

iPhone Tracker

This map is not featured for its cartographic brilliance but for its unveiling of the volume of data our electronic devices, in this case iPhones, are capable of collecting. It served as a wake up call for many that data about our locations are collected all the time and it is easy to track where you have been.

Fedex Cartograms

Cartograms are becoming an increasingly popular way of mapping population data. I don’t have a problem with advertising so long as it is informative as well. I think these maps tick the box as they provide the best animations I have seen of cartograms morphing from one dataset to the other so I’m happy to give fedex a plug for this one.

Naming Rivers

The “Naming Rivers” map shows how different cultural and linguistic factors have influenced the naming of geographic features in the US. We talk about how we live in a “world without borders” but this plainly isn’t true as things we encounter on a daily basis are still influenced by the uneven movements of various populations over time.

Scientific Collaboration

This map, inspired by the Facebook connections map (above), demonstrates the dominance of a few countries within the scientific literature and the limited collaborations between a few countries. This pattern is seen in many datasets and is another illustration that  “global” is often only a minority of countries.

Eric Fischer’s Twitter Language Map

I really liked these maps both for their cartography but also for their demonstration that linguistic and national borders can be seen online as well. There has also been a tendency for fine scale mapping of Twitter data so it is nice to get a global perspective.

ITO 10 Years of Road Casualties UK (and US)

As I was writing this, the BBC have launched their own visualisations with this depressing data. It is often said that in the context of modern health and safety standards the car would never have been allowed. With maps such as the above it is easy to see why. ITO World have tried to be more intelligent with their use of icons- they have moved beyond the simple “pins on maps” we often see. It doesn’t work so well at the regional level, but as you zoom in clear accident hotspots unfortunately emerge.

NOAA Japanese Tsunami Wave Height

This year saw a devastating earthquake and subsequent tsunami hit Japan. NOAA produced a series of excellent maps and visualisations to help chart and explain the events. The map shows likely tsunami wave heights. I found it interesting as it shows both the extent of the waves and the way in which they appear as tentacles circling Earth.

BBC Brief History of Time Zones

Good maps help to educate and I found the above interactive globe from the BBC a really great way to learn about time zones. The BBC are becoming increasingly ambitious with their maps and I think they have excelled themselves with this one.

xkcd’s What Your Favourite Map Projection Says About You

This captures the different opinions on some of the many map projections perfectly. You may have gathered from the opening lines of this post that projections are really important and often considered too complicated to bother with. I’m all for the Winkel-Tripel although I can’t claim to have been a fan before the National Geographic adopted it, as I would have been too young to care at the time.

For Carto-Nerds: This map has not been adjusted for the underlying population density of Great Britain, which is why it closely resembles a map of urban areas. The underlying spatial units for the density analysis are Output Area centroids which have been roughly standardised for population. Taking the relative frequency of the name therefore makes little difference (I have tried it). There are some more involved ways of accounting for underlying population in density analysis (this forms part of my PhD research) but I haven’t bothered to use them in a map as tongue in cheek as this…

To create this map I used ArcGIS 10 and the Cartogram Geoprocessing Tool. The nice thing about the tool is that it is not dependent on VBA and therefore worked straight off in ArcGIS 10. There are over 220,000 spatial units in this map and the tool had no problems processing them. I have not found any alternatives that work for this volume of data.

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.

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.

Family Names as indicators of Britain’s Changing Regional Geography

James Cheshire, Pablo Mateos, and Paul A. Longley

In recent years the geography of surnames has become increasingly researched in genetics, epidemiology, linguistics and geography.  Surnames provide a useful data source for the analysis of population structure, migrations, genetic relationships and levels of cultural diffusion and interaction between communities. The Worldnames database (www.publicprofiler.org/worldnames) of 300 million people from 26 countries georeferenced in many cases to the equivalent of UK Postcode level provides a rich source of surname data. This work has focused on the UK component of this dataset, that is the 2001 Enhanced Electoral Role, georeferenced to Output Area level.

Exploratory analysis of the distribution of surnames across the UK shows that clear regions exist, such as Cornwall, Central Wales and Scotland, in agreement with anecdotal evidence. This study is concerned with applying a wide range of methods to the UK dataset to test their sensitivity and consistency to surname regions. Methods used thus far are hierarchical and non-hierarchical clustering, barrier algorithms, such as the Monmonier Algorithm, and Multidimensional Scaling. These, to varying degrees, have highlighted the regionality of UK surnames and provide strong foundations to future work and refinement in the UK context. Establishing a firm methodology has enabled comparisons to be made with data from the Great British 1881 census, developing insights into population movements from within and outside Great Britain.

This is a cartogram representing the relative frequency of the surname “Cheshire” in the UK. You can see it is an English name with very few, if any, occurrences in Scotland, Wales and Ireland. West Central England has become the most bloated suggesting the highest proportion of  “Cheshires” in this region. I have mapped a silhouette of a correctly proportioned (British National Grid) UK behind the cartogram representation.

The above cartogram shows the surname “Lewis”. Lewis is a common name throughout the UK but the cartogram shows its Welsh (particularly South Wales)  dominance as the country has greatly expanded beyond its normal proportions.

This is my favorite cartogram. It shows how concentrated many Cornish names, in this case “Laity”, are in the UK and how they rarely exist beyond Bristol.

The above cartogram is for the surname “Saltmarsh”. I have included this as it nicely represents the influence of landscape features on UK naming conventions. The sheltered South Eastern and Eastern coast of the UK is where you will find the majority of UK saltmarshes. The cartogram shows an expansion of districts on the South Eastern/ Eastern side of the UK and a reduction in district size along more exposed coasts (where there are fewer, if any, saltmarshes), therefore suggesting a close correspondence between the number of people with the name and their proximity to the landscape feature!