Visualizing global democracy, redux
Previously, I’ve attempted to construct voting districts for the whole world, with an equal number of people in each one. This all stems from a proposal in George Monbiot’s book calling for a global parliament, as a compliment to or replacement for the United Nations and its one-nation-one-vote paradigm. Monbiot points out that this proposal is repulsive to many in the developed world, simply because of the overwhelming dominance in the system of the developing countries, due to their large populations. As a landscape ecologist and a geographer, I was interested in how this would look on a map. My previous algorithm for mapping this was very crude, and came up with very square-looking voting districts. My current algorithm allows the boundaries of districts to follow gradients in population density, and is a great improvement.
Below is a map of 400 voting blocks of approximately equal population, based on the excellent global grid of population in 1995 available from the Columbia Earth Institute. First of all, let me say what this map is NOT: It is not an attempt to put forth a reasonable set of voting districts (which would be rather arrogant of me, as such things are always the outcome of a political process), nor is it an endorsement necessarily of Monbiot’s scheme for a world parliament. The idea is to get people thinking about how political power would be distributed if every person on earth had equal voting power. While national boundaries are shown on the map to help orient the reader, they were not used at all in the creation of these voting districts, and so the districts freely span national boundaries when population densities require that. Note the high density of small regions in southeastern Asia, particularly India and China- this is simply due to the high population density in these places.
Click on the thumbnails below to view a global map and close up maps of a variety of areas. Each color is a region with around 15 million people. Note that these are high-resolution JPEGs (600 DPI) that don't always display well in a browser, but if you download them they look and print great in something like Photoshop.
Now, technical details on how this was made: Population data were taken from the Center for International Earth Science Information Network (CIESIN), Columbia University; International Food Policy Research Institute (IFPRI); and World Resources Institute (WRI). 2000. Gridded Population of the World (GPW), Version 2. Palisades, NY: CIESIN, Columbia University. Available at http://sedac.ciesin.columbia.edu/plue/gpw. This gives population estimates in latitude/longitude for cells that are about 5km on a side near the equator. To perform my calculations in a projection system that is more equal-area than geographic, the grid was projected into a Robinson projection, which is reasonably equal-area between 45 and -45 latitude, and doesn’t have the high distortion of shape and distance at high latitudes that a true equal-area projection (e.g., sinusoidal projection) would. The algorithm starts with the densest cell, and begins joining it with its neighbors, starting with its most dense neighbor. This process continues until the target population is reached. This district is then considered finished, and taken out of consideration, and the algorithm then goes to the next highest cell. This algorithm works quite well except in places where there’s little or no population (like northern Canada), where there are no gradients in population density to guide the placement of boundaries. The other place it occasionally fails is when there is a large city (5-10 million people) surrounded by an area of almost no population. In this case, the final district created will tend to be over my target of 15 million, as this city will get lumped in with another big one a fair distance away.
The philosophy behind this algorithm is that people who live near one another should be in same voting district, whenever possible, regardless of which country they are in. This leads to an urban-centric definition of boundaries. Take a good look at New York City, for example- the core of the city gets one voting district, while the suburbs get another. This may upset the people from the suburbs (folks from northern New Jersey often want to claim allegiance to NYC), but it is a necessary consequence of having the many millions of people in the NYC core voting together. In any event, one could argue that the suburbs of New Jersey are more like the suburbs of the lower Hudson Valley than the core of NYC, so it may be appropriate that they vote together.
