Iceland and maps have a long tradition in the history of cartography. From the first maps of the country in the 16th century (including works from cartographers such as Ortelius and Mercator, also featuring some nice sea monsters) to today’s advanced digital mappings of Iceland’s diverse natural environment (such as this innovative mapping of water in Iceland or this quite beautiful representation of contour lines), Iceland never really had a lack of quite good cartographic works. Much less covered than the natural environment are the social landscapes of the country, such as this just recently updated version of a gridded population cartogram of the country where each grid cell is proportional to the number of people living in that area:
The effects of humans on the global environment are perceived to be so significant by some scientists that they argue the onset of industrialisation (in the eighteenth century) has been a major driving force in environmental change on a par with the forces of nature. It is this rapid impact that has led some geologists to unofficially name (but not, as yet, officially recognise) this recent period of the earth’s history (from around 1760-onwards) as the Anthropocene (roughly translating as the era – or epoch – shaped considerably through the actions of humanity).
Gridded population cartogram displaying the topography of the world in relation to the population distribution (click here for larger version)
“There is no planet B”. This slogan has become widely mentioned recently in relation to COP21, the United Nations conference on climate change in Paris. The slogan highlights that the debate about climate change relates to much more than simply a changing climate. The underlying processes have a lot to do with our lifestyles and the related patterns of consumption and waste which cause severe damages to the environment (including the global climate). Carbon emissions are therefore one major trigger of climate change, but are also an effect of our unsustainable ways of life. The ecological footprint shown in the following map is a measure that looks at the impact that humanity has on our planet:
Innovative maps that illustrate the most recent socio-demographic urban changes in the major city urban agglomerations in Germany have very recently been produced in a joint project of the School of Geography and the Environment at the University of Oxford and the Research Institute for Regional and Urban Development Dortmund (Germany).
The Research Institute for Regional and Urban Development (Institut für Landes und Stadtentwicklungsforschung, ILS) investigates new social processes, especially those involving urbanisation in Germany and Europe. This includes economic, social and structural processes that are compared and monitored over time to gain a better understanding of the underlying developments. Testing state-of-the-art visualisation techniques are a significant part of this effort. This was the focus of a collaboration between researchers of the University of Oxford and the ILS Dortmund which resulted in the development of a series of highly effective maps called “cartograms” that provide new insights in the changing geographies of city regions in Germany.
Big data, big challenge? Together with Harald Sterly of the University of Cologne I presented a little piece of research in the Extended Spatial Analytics session of the German Geography Congress (Deutscher Kongress für Geographie) in Berlin. The project “Calling Abidjan” that we worked on with Kouassi Dongo of Université de Cocody-Abidjan was started after we successfully applied for participation of the D4D Challenge. According to the initiator Orange telecommunications ‘Data for Development’ is “an innovation challenge open on ICT Big Data for the purposes of societal development”. The project allowed us to work with anonymised mobile phone data from individual call records by Orange in the country of Côte d’Ivoire (Ivory Coast).
We were interested in investigating, what non-computer scientists with a social science and urban planning background can do with such data in a more contextual rather that technically driven way and therefore explored how mobile phone call records can be used to better estimate population distribution.
For our analysis we used anonymised call data records consisting of information about the base station, timestamp, and caller ID produced by the approximately 500.000 Orange Télecom users in the country. There were 1079 base stations at the time the data was generated and we were able to work with data covering 183 days. The dataset consisted of 13GB of raw data which some would perhaps call ‘Big Data’ (though I personally do not like this term for many reasons).
The following two (draft) maps give an insight into the results. The purple circles show the distribution and density of population estimates that we derived using only mobile phone call records dataset. To better see the correlation with what other population data tells us about where people live, we did not only produce a normal land area map (on the left, also displaying some basic idea of the topography in the country) but also showed the data on a gridded population cartogram which we generated from the LandScan population grid, the perhaps most detailed population dataset currently available on a globally consistent high-resolution basis: