The dataset of terrain ruggedness and other geographical characteristics of countries was created by Nathan Nunn and Diego Puga for their article `Ruggedness: The blessing of bad geography in Africa', published in the Review of Economics and Statistics 94(1), February 2012: 20-36.
Last updated by source: 2010-11-12
| Dataset type: | Cross-section |
| Dataset level: | Country |
(Nunn & Puga,
2012)
The percentage of the land surface area of each country covered by sandy desert, dunes, rocky or lava flows, was calculated on the basis of the desert layer of the Collins Bartholomew World Premium digital map data (Collins Bartholomew, 2005) and the country boundaries described above. This was initially computed as a cruder measure of soil (in)fertility for an early draft of the paper and is no longer used in the final version. Nunn and Puga have left it in the dataset in case it is of use to other researchers.
More about this variableAverage distance the to nearest ice-free coast (1000 km). To calculate the average distance to the closest ice-free coast in each country, Nunn and Puga first compute the distance to the nearest ice-free coast for every point in the country in equi-rectangular projection with standard parallels at 30 degrees, on the basis of sea and sea ice area features contained in the fifth edition of the Digital Chart of the World (US National Imagery and Mapping Agency, 2000) and the country boundaries described above. Then Nunn and Puga average this distance across all land in each country not covered by inland water features. Units are thousands of kilometres.
More about this variableWithin 100 km of ice-free coast. On the basis of the same data used to calculate the average distance to the nearest ice-free coast, Nunn and Puga calculate the percentage of the land surface area of each country that is within 100 km of the nearest ice-free coast.
More about this variableThis is the Terrain Ruggedness Index originally devised by Riley, DeGloria, and Elliot (1999) to quantify topographic heterogeneity in wildlife habitats providing concealment for prey and lookout posts. The source of elevation data is GTOPO30 (US Geological Survey, 1996), a global elevation data set developed through a collaborative international effort led by staff at the US Geological Survey's Center for Earth Resources Observation and Science (EROS). Elevations in GTOPO30 are regularly spaced at 30 arc-seconds across the entire surface of the Earth on a map using a geographic projection, so the sea-level surface distance betNunn and Pugaen two adjacent grid points on a meridian is half a nautical mile or, equivalently, 926 metres. After calculating the Terrain Ruggedness Index for each point on the grid, Nunn and Puga average across all grid cells in the country not covered by water to obtain the average terrain ruggedness of the country's land area. Since the sea-level surface that corresponds to a 30 by 30 arcsecond cell varies in proportion to the cosine of its latitude, when calculating the average terrain ruggedness - or the average of any other variable - for each country, Nunn and Puga Nunn and Pugaigh each cell by its latitude-varying sea-level surface. Nunn and Puga assign land to countries - for this and other variables - using digital boundary data based on the fifth edition of the Digital Chart of the World (US National Imagery and Mapping Agency, 2000), which Nunn and Puga have updated to reflect 2000 country boundaries using information from the International Organization for Standardization ISO 3166 Maintenance Agency and other sources. Nunn and Puga exclude areas covered by permanent inland water area features contained in the same edition of the Digital Chart of the World. The units for the terrain ruggedness index correspond to the units used to measure elevation differences. In our calculation, ruggedness is measured in hundreds of metres of elevation difference for grid points 30 arc-seconds (926 metres on the equator or any meridian) apart.
More about this variableTropical climate. Using detailed temperature and precipitation data from the Climatic Research Unit of the University of East Anglia and the Global Precipitation Climatology Centre of the German Nunn and Pugaather Service, Kottek, Grieser, Beck, Rudolf, and Rubel (2006) classify each cell on a 30 arc-minute grid covering the entire land area of the Earth into one of 31 climates in the widely-used Köppen-Geiger climate classification. Based on these data and the country boundaries described above, Nunn and Puga calculate the percentage of the land surface area of each country that has any of the four Köppen-Geiger tropical climates.
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