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Gridded Population of the World (GPW), v3

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  • Collection Overview
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Documentation

Methodological documentation for the Gridded Population of the World, Version 3 (GPWv3), and GPWv3: Future Estimates data products is available in the following papers:

  • The Global Distribution of Population: Evaluating the Gains in Resolution Refinement
  • Construction of Gridded Population and Poverty Data Sets from Different Data Sources

For a more in-depth description of GPW methodologies, please see the GPWv2 working paper below:

  • Transforming Population Data for Interdisciplinary Usages: From Census to Grid

To understand the units and spatial resolution of the census data inputs for GPWv3 by country, please download (Microsoft Excel file) the GPWv3 and Global Rural-Urban Mapping Project (GRUMPv1) country, continent, and global summary spreadsheet. (Note that GRUMPv1 is based on the same census inputs as GPWv3.)

National Population Estimate Differences: GPWv3 and UN

GPWv3 relies on national statistical office estimates of population. Therefore, GPWv3 and UN national population estimates may differ because of disparate methodologies and source data.  The list below summarizes the countries for which the population difference was greater than 5% in 1990, 2000, and 2015:

1990  Armenia, Bangladesh, Bolivia, Cambodia, Cameroon, Chad, Colombia, Comoros, Croatia, Djibouti, Ecuador, Egypt, French Guiana, Guatemala, Guinea, Holy See, Honduras, India, Iran, Ivory Coast, Kenya, Lebanon, Macao, Madagascar, Malawi, Mali, Mongolia, Mozambique, Nicaragua, Occupied Palestinian Territory, Panama, Paraguay, Peru, Qatar, Sierra Leone, Slovakia, Sri Lanka, Turkmenistan, Uganda, United Arab Emirates, United Republic of Tanzania, United States Virgin Islands, Vanuatu, Venezuela

2000  American Samoa, Andorra, Armenia, Bangladesh, British Virgin Islands, Cambodia, Cameroon, Chad, Colombia, Comoros, Congo, Cook Islands, Costa Rica, Croatia, Ecuador, Federated States of Micronesia, French Guiana, Gambia, Georgia, Guatemala, Haiti, Holy See, Honduras, India, Indonesia, Iran, Malawi, Maldives, Mali, Mongolia, Montserrat, Mozambique, Netherlands Antilles, Niger, Niue, Northern Mariana Islands, Oman, Paraguay, Russia, Solomon Islands, Somalia, Saint Pierre and Miquelon, Trinidad and Tobago, Turkmenistan, Uganda, United Republic of Tanzania, United States Virgin Islands, Vanuatu, Venezuela

2015  American Samoa, Andorra, Armenia, Bangladesh, Bosnia-Herzegovina, British Virgin Islands, Cameroon, Chad, Colombia, Comoros, Congo, Cook Islands, Federated States of Micronesia, French Guiana, Georgia, Haiti, Kuwait, Latvia, Lithuania, Malawi, Maldives, Morocco (includes Western Sahara), Nauru, Netherlands Antilles, Niger, Niue, Oman, Paraguay, Romania, Russia, Saint Lucia, San Marino, Sierra Leone, Solomon Islands, Somalia, Saint Pierre and Miquelon, Tokelau, Trinidad and Tobago, Turkmenistan, Uganda, Vanuatu, Yemen, Zimbabwe

Countries in GPWv3 Given a Growth Rate Cap

When interpolating between population estimates from two data years, it is not uncommon to experience high growth rates for small administrative units—even when the vast majority of units in that country experience much lower rates of growth.  The list below summarizes the countries for which one or more administrative units experienced an unusually high growth rate (±5%). For these units we applied a growth rate cap of 5%.

Belgium, Botwana, Brazil, Cambodia, China, Chile, Ecuador, Guatemala, Guinea, Honduras, Italy, Mali, Mexico, Morocco, Mozambique, Namibia, Niger, Oman, Panama. Paraguay, Russia, Sierra Leone, Slovakia, South Africa, Uganda, United Republic of Tanzania, Venezuela, Zambia

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