Background Information
The BRIC countries comprise of Brazil, Russia, India, and China; distinguished by their promising
developing economies and projections to become leading global powers. Together, these four countries
makeup 40 percent of the world’s population, cover approximately a quarter of
the Earth’s land area, and account for 25 percent of the global GDP. The BRIC countries were
selected for this study due to their current economic projections, contribution
to the global GDP, and the significant portion of the global population they contain.
For this study three data sets were analyzed to
measure how efficient a country uses it available resources for production of
goods; gross domestic product (GDP), human appropriated net primary production (HANPP), and gross primary productivity (GPP).
A county's gross domestic product (GDP) is defined at the monetary
value of finished goods produced. To
evaluate the usage of each country’s resources, data was pulled in to measure
the available resources within that country and the amount utilized by
humans. Gross primary productivity (GPP)
measure the total amount of solar energy converted to organic plant matter
through photosynthesis. Conversely, human appropriated net primary
production (HANPP) measures the human usage of organic plant based material in
grams of carbon.
Data Sets
- Global Patterns of NPP: NASA SEDAC
- Global Patterns of HANPP: NASA SEDAC
- Country Data: The World Fact Book (CIA)
Methodology
All data sets were loaded into ArcGIS 10.1 for
manipulation, calculation, and mapping.
The methodology used in this study followed two papers written by Imhoff
et al. This first step was to derive the net GDP per country
from the data included in the country shapefiles. The Spatial Analyst tool, Zonal Statistics,
was used to sum GDP values to calculate the net GDP per country. The country level total GPP and HANPP values
from the acquired continuous rasterized datasets needed to be derived. The Raster to Polygon conversion tool was
used in ArcGIS 10.1 to convert continuous rasterized data to discrete datasets
with country level data. Using a common
naming convention, the converted HANPP and GPP files were joined to the GDP
shapefile. In order to compare each
country’s usage of resources for production purposes NPP and HANPP values were
normalized by each country’s GDP, dividing grams of carbon per dollar. Because the original data set includes all
global countries, the data set was clipped down to the BRIC countries.
Conclusions
This study found Brazil and Russia to use its resources for production
of goods the most efficiently. However,
using solely GDP, HANPP, and GPP is an over simplification of each country’s
production efficiency since many other factors contribute the datasets. Population size and density contributes to
both the land available to vegetation, and the demand for resources to sustain a
population. The
level of develop a country is at also influences the way resources are utilized, the
efficiency of extracting and processing them, and the level of demand. The type of industry a country is dominated
by also influences the need and type of material used. More developed economies like India and China
have less natural resource availability, and a need to use more materials. Climate affects the level of vegetation and
habitability of land. Brazil has a
significantly higher NPP value its tropical climate indicative rainforests do
to the high biomass contained within its rainforest. Also, Russia has a large land area part of
which has a harsh climate inhabitable in some locations. To accurately evaluate a country’s production
efficiency, many other factors have to be considered. The portion focused on in this study
highlights differences in each country’s economic development; out of the BRIC
countries, Brazil has uses the least amount of available carbon resources for
production.
Map Links
ESRI Story Map: http://www.arcgis.com/apps/Compare/storytelling_compare/index.html?appid=5ea05e9ef4ff476fa3353b529e064fe0
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