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:
This year’s New Teacher Subject Day organised by the Prince’s Teaching Institute took place at Altrincham Grammar School for Girls near Manchester. For the geography teachers the focus was on the topic of Geopolitics and Borders to which I contributed a talk about ‘The Power of Maps: A Cartographic Journey along the World’s Borders’ (see slides at the end of this page) and also organised a practical session where the participants learned to create their own cartogram. Related to the theme and linking to the content of my talk, this cartogram was an update of the Refugee arrivals map from 2015 using the latest data by UNHCR. The following map shows the number of refugee arrivals by sea in the Mediterranean in the first months of 2016 (as of March, 3):
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:
This is a German-language poster contribution looking at processes of change in the major urban agglomerations in Germany and novel ways of visualising these using cartogram visualisation techniques. Continue reading
The growing amount of remotely sensed data and the ongoing developments in the improvement of spatial and spectral resolutions lead to high expectations. These often inflated expectations are usually not fulfilled. I explored these expectations and aimed to make a contribution to bring them to a more accurate level in research in the field of hyperspectral image analysis of small scale and heterogeneous biotopes in the intertidal zones of coastal areas which I undertook back at my time at the University of Cologne and the Alfred Wegener Institute for Polar and Marine Research Bremerhaven. Here are some insights from my work.
Overview of the study area on the islands of Helgoland and Sylt, Germany
(click for larger version)