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A population density map to help provide context for the nuclear power plant proximity analysis

Following on from the population analysis which I published yesterday estimating quantitatively how many people live within certain distances of each of the world’s nuclear power plants, some people have asked me for more information on population distribution itself, and whether it might provide more spatial context for the results of the analysis – for example is the plant close to urban sprawl from a major city? Or why is it that nuclear power plants in France, for example – which with 58 nuclear reactors, is second only to the United States (which has 104) in terms of numbers of nuclear reactors – nonetheless tend to have fewer people living near to them, compared with, for example, those in much smaller nuclear power nations such as Germany – which have a comparable population? – answer; in centralized France most people live in the capital Paris, with much of the rest also being largely in a few big urban centres.

So to try to provide some more visual geographical context, today I’ve mashed together the results of the analysis I published yesterday in Nature — see here my 3D map of the results of that analysis — with a new very high-resolution global population density Google Earth map for 2010 created by the NASA Socioeconomic Data and Applications Center operated by Columbia University’s Center for International Earth Science Information Network (CIESIN). The underlying population data is the same as we used in our previous analysis to estimate the size of population in the proximity of nuclear plants.

Mashing the two maps together certainly does provide this sort of greater context, but the result of combining them is also a bit visually overwhelming, and may be confusing at first. — so beware.

Here’s a screenshot — you can find the full 3-D interactive mashup of the two maps below the fold

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Warning: the overlay of the population density map on my nuclear plant map is very much a beta. The original population density image file was itself 3 GB in size CIESIN’s scientists tell me (it had a global resolution of 1km); and they have worked to reduce it’s size, using several tricks, and also by only loading particular regions as you zoom in Google Earth — this also means that depending on server speed some panels may not load (you will see a large red “X” when this happens in an area, but they will eventually load as you browse). Using the browser plugin version below may also be CPU-intensive with a complex map like this, so you can always download the combined map file for the Google Earth desktop version — click here to download file.

For the base nuclear plant map, also remember that the size of circles – nuclear power plants — indicates the number of people living within 75 kms — circles are also coloured using the scale to the right. Move your mouse over a circle to see its label and its population within 75 kms. Click on any circle to open up an information panel showing data for population estimates at 30, 75, 150 and 300 kms, as well as the plant’s total power output.

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    Dario said:

    Cmplimenti! Veramente interessante!

    Dario

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    population said:

    A population density map to help provide context to my nuclear power plant proximity analysis – April 22, 2011

    Following on from the population analysis which I published yesterday estimating quantitatively how many people live within certain distances of each of the world’s nuclear power plants, some people have asked me for more information on population distribution itself, and whether it might provide more spatial context for the results of the analysis — for example is the plant close to urban sprawl from a major city? Or why is it that nuclear power plants in France, for example – which with 58 nuclear reactors, is second only to the United States (which has 104) in terms of numbers of nuclear reactors — nonetheless tend to have fewer people living near to them, compared with, for example, those in much smaller nuclear power nations such as Germany –

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    sweety

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