Thursday, July 24, 2014
[image credit: Batista e Silva et al, 2013]
The map shows a fine-scale spatial population distribution in selected European capitals. The high resolution map is here, and it comes from this paper:
Batista e Silva, F., Gallego, J., Lavalle C. (2013). A high-resolution population grid map for Europe. Journal of Maps 9(1):16-28.
Population figures are usually collected by national statistical institutes at small enumeration units (e.g. census tracts or building units). However, still for many countries in Europe, data are distributed at coarser geographical units like municipalities. This level of resolution is insufficient for analysis in many fields. In addition, the heterogeneity of the size of the geographical units causes great distortions in analysis, i.e. the Modifiable Areal Unit Problem (MAUP). Dasymetric mapping techniques have long been applied world-wide to derive finer (and MAUP-free) depictions of the population distribution. These techniques disaggregate population figures reported at coarse source zones into a finer set of zones using ancillary geographical data. ... In this article, we test new geographical datasets to produce an updated and improved European population grid map. ... As final outcome of this cartographic exercise, a European population grid map for the reference year of 2006, with a spatial resolution of 100 × 100 meters, is presented and validated against reference data. Resident population reported at commune level, a refined version of CLC and information on the soil sealing degree are used as the main inputs to produce the final map.
Related Paper and data:
Tuesday, July 22, 2014
Image Credit: ISS Expedition 30, NASA
"Constellations of lights connecting the densely populated cities along the Atlantic east coast of the United States are framed by two Russian spacecraft docked at the space station. Easy to recognize cities include New York City and Long Island at the right. From there, track toward the left for Philadelphia, Baltimore, and then Washington DC near picture center."
Sunday, July 20, 2014
The Max Planck Institute for Demographic Research (MPIDR) is receiving applications for the upcoming International Advanced Studies in Demography (IDEM) program, next winter semester 2014/15 in Rostock (Germany).
The program includes courses on Agent-based Modeling and Simulation, Integral Projection Models, Bayesian Forecasting, Spatial Demography, and other topics. Highly recommended! Thanks Rob Salguero-Gomez for the tip.
Saturday, July 19, 2014
Friday, July 18, 2014
Erik Stokstad writes about a new study recently published in PLOS ONE:
The authors have analyzed the Elsevier’s Scopus database, looking at at papers published between 1996 and 2011 by 15 million scientists worldwide in many disciplines.
Wednesday, July 16, 2014
Apparently, this is one of the oldest isochrone maps, circa 1920. It shows the “minimum” travel time into the city of Melbourne via suburban railways and tram lines (via Daniel Bowen and Transit Maps).
Transit Maps also points out to this isochrone map of Manchester in 1914. Finally, the Atlas of the Historical Geography of the US of 1932 showed also published a few isochrone maps of American railways in the 1800s. These maps comprise only a small sample of our old obsession with time.
Train and Tram Travel Times in Melbourne, Australia, c. 1920
More recently, some people/projects have been applying new technologies to this old obsession with travel times, and the results include some pretty amazing maps. Among many of these new projects, I would highlight two: The great Mapnificent (by Stefan Wehrmeyer).
Ant the amazing work Xiaoji Chen and her maps of Singapore and the isogreenic (!) map of Paris
Monday, July 14, 2014
- The daily routines of creative people
- 15 Super Thin Buildings
- Data-driven insights to optimize the use of public transport, by Urban Engines
- Heterogeneity in Expected Longevities
- Why are teen births down in the US? Answer: Postponement
- Tokyo's massive flood prevention system
- Things I would rather be doing
- 10 things statistics taught us about big data analysis
[image credit: Simply Statistics]