The Global Poverty Mapping Project

I recently tackled uploading some relatively complicated, yet highly informative data from The Global Poverty Mapping Project(GPMP).  The creators (Columbia University Ivy Leaguers) mission is to “enhance current understanding of the global distribution of poverty and the geographic and biophysical conditions where the poor live.”   I like that their mapping efforts are to engage policy makers, development agencies, and the poor themselves in a geographical sense to reduce poverty—a similar aim we have at FortiusOne with GeoCommons by delivering visual analytics and geospatial intelligence to the public.

One of the problems I faced while combing through the GPMP, aside from the very technical terminology (a lot of the data the Columbia students created uses complex formulas:), was that the maps themselves were only viewable in .pdf format without any real mapping interface.  I wanted to click on different areas of their maps to get a better idea of the poverty level for each nation, provincial, and municipal level areas.  This was easily made possible after a couple clicks in Finder! and Maker!.

Below are two of the maps I created in Maker!. The first being a fairly basic global-level map showing the prevalence of global child malnutrition:

Click here to view map in Maker! and here to view dataset in Finder!

Darkest green countries with a negative value didn’t have child malnutrition data; likely not created by different national government data sources. By also clicking different countries you can get an idea of the percent of the population under 5 years of age.

A second map I’ve created from the GPMP is a bit more complicated as I mentioned above because it uses a complex formula called the Poverty Gap Index. It measures the severity of poverty by taking the per capita cost of eliminating poverty (relative to the poverty line). Below I’ve showed the Poverty Gap Index of Bangladesh in each municipality.  The areas with darker color red are the poorest municipalities and the lighter shades of red are the non poor because they  represent a zero poverty gap.  In other words, the darker the shade of red the greater the poverty gap the poorer the municipality.

Click here to view the map Maker! and click here to view in Finder!