This feature was compiled in collaboration with Phil Baty of Times Higher Education and first appeared in the World University Rankings 2013-2014. In the following blog post we put the rankings results into a human and economic perspective (modified version from the original article). The two maps show the top 200 Universities from the Ranking displayed on two different kinds of gridded cartograms:
Wilderness and remote areas are a diverse element in the patchwork of spaces that form the land surface of our planet. Only very small amounts of people are living in sparsely populated areas, which is an expression of the strong organisation of human societies to maximise those living in close relative proximity. More than half of the world’s population now lives in areas categorised as cities, and although more than 95% of the world’s population live in approximately only 10% of the land area, the remaining 90% of space on land are far from being uniform remote or even wild areas.
There are very different ways of how the un-built area that still makes the largest share of land can be understood in terms of being under influence and in reach of human civilization. Only 15% of people in rich countries live more than an hour of travel time from a city (of at least 50,000 people), while the same applies to 65% of people living in the poor countries of the world. This paper demonstrates a different approach to visualising and understanding these loneliest places on the planet by using a technique called a gridded cartogram transformation. The following map shows a gridded cartogram visualising the relative distance of areas to the majority of people. The maps derived from the distorted grid show the physical space transformed according to the absolute travel time that is needed to reach the nearest major city by land transport averaged over the area of a grid cell, resulting in a map that gives the remotest places most space and provides a unique new perspective on the spatial dimension of remoteness:
The following map series is a comprehensive overview of the individual second vote shares of each of the parties represented in the new parliament after the 2013 general election (in order of their absolute vote share) and a look at the change in votes compared to the Bundestagswahl 2009 for the party who were in parliament during the last term. I also mapped a few of the smaller parties that are most relevant in the public debate. Please note that the following page may take a while loading due to the large number of maps and their respective filesize. Continue reading
The story of an election in a modern democracy has recently more and more turned into the story of a non-vote, as turnout at elections is on a general decline in many countries. That does not always reflect a certain libertarian strategy (otherwise the strive for anarchism would be stunningly on the rise), but can more likely be linked to an apolitical attitude. So how many Germans did choose to not cast a vote on this year’s general election (see the full results of the Bundestagswahl in this blog post)? 71.5% went to the polls last Sunday, so 29.5% of the electorate did not, which is slightly lower than the 29.2% non-voters at the 2009 election, though one can certainly not speak of an upward trend here. The following map gives an impression of this quite interesting geographical pattern that is far from evenly distributed across the country. The second map shows another group of voters who did not make their voice heard: The 1.3% of spoilt votes which again show a certain geographical distribution and are not completely evenly distributed. Even in the non-votes lie many spatial stories:
Germany’s vote at this year’s general election has implications that reach much further than its national borders. CDU, the party of chancellor Merkel, could secure a massive victory getting 34.1% of the second vote share, though it narrowly missed an absolute majority of seats with its sister party CSU who won 7.4% of the votes (they are only standing in the Federal state of Bavaria). The former coalition partner FDP however missed the 5% mark (4.8%) that is needed to enter parliament, so that CDU/CSU now have to find a new coalition partner. Second largest party became that of Merkel’s contender Steinbrueck. SPD could secure 25.7% of the second votes. The only two other parties in parliament are Die Linke (The Left) with 8.6% of votes, and Die Gruenen (the Green Party) with 8.4%.
As often the case with electoral maps, the problem with conventional map depictions (as shown in the little thumbnail maps below) is the distorted perspective of the less populated areas. The maps shown in most of the media give the impression of an almost landslide victory of CDU/CSU. But while their good results are undisputable, the conservative CDU is traditionally strong in the rural regions, while SPD is stronger in urban areas. The following two maps show the largest shares of votes from each of the two votes. The first vote directly elects the local candidate into parliament, while the second vote determine’s each party’s total vote share in the Bundestag (Erststimme / Zweitstimme, read more about the electoral system in Germany at Wikipedia). When it comes to showing the real distribution of voting patterns in Germany, these two main maps give the more honest result of this year’s election:
Time again to talk about the weather: Britain is suffering under heatwave conditions (also known as summer in other parts of the world), with the ongoing high temperatures and developing clouds going along with an increased humidity slowly increasing the risk for thunderstorms. Thunderstorms are not an uncommon phenomenon on the British Isles, but they are much less common and much less severe compared to other regions experiencing similar conditions much more frequently and more intensively. The Met Office explains that “Owing to the fact thunderstorms are created by intense heating of the earth’s surface, they are most common in areas of the globe where the weather is hot and humid. Land masses therefore experience more storms than the oceans and they are also more frequent in tropical areas than the higher latitudes. In the UK thunderstorms are most common over the East Midlands and the south-east.”
As it happens to be, the part most prone to thunderstorms in Britain is also the most densely populated region. Comparing this to other parts of the world, it can be seen that some of the most risky regions are also some of the very densely populated places. In Europe, which is overall densely populated in many parts, the most affected areas are the people living in the Mediterranean countries, although the European population in general is amongst the least affected by thunderstorms when comparing this to areas such as the southern edge of the Himalayas in India – densely populated and experiencing very intensive thunderstorms. These details only emerge when changing the projection of data collected on lightning flashes from a conventional land area map (where this part of India for instance remains comparably small) to a gridded population cartogram. The following map shows the intensity of lightning flashes displayed as the number of flashes per square kilometre per year in each of the grid cells, while the distortion of the grid cells reflects the global population distribution, so that the most and least exposed populations are highlighted in this visualisation: