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4 Comments
Visualization of the population within 100 km of Berlin, New York City and Cairo
PLEASE NOTE: If you can’t read it then blame the mobile app. On desktop you can zoom in several times.
This is a follow-up to my previous post: [https://www.reddit.com/r/dataisbeautiful/comments/1f2rtu4/visualizations_of_city_populations_chicago_la_ny/](https://www.reddit.com/r/dataisbeautiful/comments/1f2rtu4/visualizations_of_city_populations_chicago_la_ny/)
You will find more such visualizations on my YouTube-Playlist [https://www.youtube.com/playlist?list=PLW6n55tz6jkXZa82BDIBern0zB9fgNaQl](https://www.youtube.com/playlist?list=PLW6n55tz6jkXZa82BDIBern0zB9fgNaQl)
The visualizations intuitively illustrate the distribution and density of inhabitants in a region and facilitate comparisons between cities.
The focus is on a radius of 100 km around the city center.
The visualization is done by illustrating the number of inhabitants and density of the area of concentric rings that extend in one-kilometer increments from the city center. This non-cumulative method thus records the population in one-kilometer intervals and illustrates how the number of inhabitants and thus the population density changes with increasing distance from the center.
When depicting cities that border directly on coasts or larger bodies of water, the deserted body of water inevitably has an influence on the population density in the surrounding area, but this is also the case in reality.
As cities and agglomerations do not usually spread out in a circular pattern, this naturally also has an influence on the representation, so that cities and areas that spread out in an extremely elongated manner would be shown here at greater distances with a lower density than cities that spread out in a circular pattern. In general, however, the representation is intended to provide the quickest possible overview of how many people can be reached at what distance from the city centers, how interwoven the commuter belt is and how strong the competition is with other populated areas in the vicinity. In this respect, this is still in the spirit of the illustration, even if in such cases the significance of information about urbanity in the inner circle of the urban area suffers.
As the area of each ring increases significantly with each additional kilometer, the number of inhabitants in this area does not provide a sufficient indication of its density; the population density of the rings is therefore shown in color. A distinction is made between 4 types of areas:
1. rural areas, areas with a population density of less than 300/km2 – these are colored black to blue
2. areas with intermediate population density such as low-density areas of cities and suburbs with a population density of more than 300/km2 but less than 1500/km2 – these are colored blue to green
3. urban centers such as areas of cities with a population density of more than 1500/km2 but less than 15,000/km2 – these are colored green to red
4. extreme urban densities such as city centers or CBDs of really dense cities, everything above 15,000/km is colored red
Below the graph the population of the city within its political boundaries is shown, as well as the radius in which the population density is at least equal to that of urban centers and the cumulative population of this area, and the radius of the area with a population density equal to that of suburbs and the cumulative population at this distance. In addition, the cumulative population figures are given for various radii from 5 km to 100 km from the center.
I’m on app and zoom working
cairo is super overpopulated
The color scaling helps, but it’s weird to just exclude the factor of 2*pi*r to account for the area being accounted for. It makes it unclear where the population density actually peaks. Cool graphic though!