Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Historical chart and dataset showing World population growth rate by year from 1961 to 2023.

This dataset contains estimates of the number of persons per square kilometer consistent with national censuses and population registers. There is one image for each modeled year. General Documentation The Gridded Population of World Version 4 (GPWv4), Revision 11 models the distribution of global human population for the years 2000, 2005, 2010, 2015, and 2020 on 30 arc-second (approximately 1 km) grid cells. Population is distributed to cells using proportional allocation of population from census and administrative units. Population input data are collected at the most detailed spatial resolution available from the results of the 2010 round of censuses, which occurred between 2005 and 2014. The input data are extrapolated to produce population estimates for each modeled year.

The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the years 2000, 2005, 2010, 2015, and 2020.�A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative Units, was used to assign population counts to 30 arc-second grid cells. The population density rasters were created by dividing the population count raster for a given target year by the land area raster. The data files were produced as global rasters at 30 arc-second (~1 km at the equator) resolution. To enable faster global processing, and in support of research commUnities, the 30 arc-second count data were aggregated to 2.5 arc-minute, 15 arc-minute, 30 arc-minute and 1 degree resolutions to produce density rasters at these resolutions.

The statistic shows the development of the world population from 1950 to 2050. The world population was around 7.38 billion people in 2015.

The global population

As shown above, the total number of people living on Earth has more than doubled since the 1950s, and continues to increase. A look at the development of the world population since the beginning of the Common Era shows that such a surge in numbers is unprecedented. The first significant rise in population occurred during the 14th century, after the Black Death had killed approximately 25 million people worldwide. Subsequently, the global population increased slowly but steadily until it reached record numbers between 1950 and 2000.

The majority of the global population lives on the Asian continent, as a statistic of the world population by continent shows. In around 100 years, it is estimated that population levels on the African continent will have reached similar levels to those we see in Asia today. As for a forecast of the development of the world population, the figures are estimated to have reached more than 10 billion by the 22nd century.

Growing population numbers pose an increasing risk to the planet, since rocketing numbers equal increased consumption of food and resources. Scientists worry that natural resources, such as oil, and food resources will become scarce, endangering the human race and, even more so, the world’s ecosystem. Nowadays, the number of undernourished / starving people worldwide has decreased slightly, but forecasts paint a darker picture.

Explore the patterns of world population in terms of total population, arithmetic density, total fertility rate, natural increase rate, life expectancy, and infant mortality rate. The GeoInquiry activity is available here.Educational standards addressed:APHG: II.A. Analyze the distribution patterns of human populations.APHG: II.B. Understand that populations grow and decline over time and space.This map is part of a Human Geography GeoInquiry activity. Learn more about GeoInquiries.

Students will explore the patterns of world population in terms of total population, arithmetic density, total fertility rate, natural increase rate, and infant mortality rate. The activity uses a web-based map and is tied to the AP Human Geography benchmarks. Learning outcomes:Students will be able to identify and explain the spatial patterns and distribution of world population based on total population, density, total fertility rate, natural increase rate, and infant mortality rate.Find more advanced human geography geoinquiries and explore all geoinquiries at http://www.esri.com/geoinquiries Latest version: Q2 2016

Human population data from UN

FAOSTAT Population module contains time series data on population, by sex and urban/rural.

The series consist of both estimates and projections for different periods as available from the original sources,

Total, female, male, urban and rural Population in 1,000 persons

Estimated density of people per grid-cell, approximately 1km (0.008333 degrees) resolution. The units are number of people per Km² per pixel, expressed as unit: "ppl/Km²". The mapping approach is Random Forest-based dasymetric redistribution. The WorldPop project was initiated in October 2013 to combine the AfriPop, AsiaPop and AmeriPop population mapping projects. It aims to provide an open access archive of spatial demographic datasets for Central and South America, Africa and Asia to support development, disaster response and health applications. The methods used are designed with full open access and operational application in mind, using transparent, fully documented and peer-reviewed methods to produce easily updatable maps with accompanying metadata and measures of uncertainty. Acknowledgements information at https://www.worldpop.org/acknowledgements

The Global Human Settlement Layer: Population and Built-Up Estimates, and Degree of Urbanization Settlement Model Grid data set provides gridded data on human population (GHS-POP), built-up area (GHS-BUILT), and degree of urbanization (GHS-SMOD) across four time periods: 1975, 1990, 2000, and 2014 (BUILT) or 2015 (POP, SMOD). GHS-BUILT describes the percent built-up area for each 30 arc-second grid cell (approximately 1 km at the equator) based on Landsat imagery from each of the four time periods. GHS-POP consists of census data from the 2010 round of global census from Gridded Population of the World, Version 4, Revision 10 (GPWv4.10) spatially-allocated within census Units based on the percent built-up areas from GHS-BUILT. GHS-SMOD uses GHS-BUILT and GHS-POP in order to develop a standardized classification of degree of urbanization grid. The original data from the Joint Research Centre of the European Commission (JRC-EC) has been combined into a single data package in GeoTIFF format and reprojected from Mollweide Equal Area into WGS84 at 9 arc-second and 30 arc-second horizontal resolutions in order to support integration with a variety of global raster data sets.

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

Data Usage Notice

This version is not recommended for download. Please check the newest version.

We would like to inform you that the updated GlobPOP dataset (2021-2022) have been available in version 2.0. The GlobPOP dataset (2021-2022) in the current version is not recommended for your work. The GlobPOP dataset (1990-2020) in the current version is the same as version 1.0.

Thank you for your continued support of the GlobPOP.

If you encounter any issues, please contact us via email at lulingliu@mail.bnu.edu.cn.

Introduction

Continuously monitoring global population spatial dynamics is essential for implementing effective policies related to sustainable development, such as epidemiology, urban planning, and global inequality.

Here, we present GlobPOP, a new continuous global gridded population product with a high-precision spatial resolution of 30 arcseconds from 1990 to 2020. Our data-fusion framework is based on cluster analysis and statistical learning approaches, which intends to fuse the existing five products(Global Human Settlements Layer Population (GHS-POP), Global Rural Urban Mapping Project (GRUMP), Gridded Population of the World Version 4 (GPWv4), LandScan Population datasets and WorldPop datasets to a new continuous global gridded population (GlobPOP). The spatial validation results demonstrate that the GlobPOP dataset is highly accurate. To validate the temporal accuracy of GlobPOP at the country level, we have developed an interactive web application, accessible at https://globpop.shinyapps.io/GlobPOP/, where data users can explore the country-level population time-series curves of interest and compare them with census data.

With the availability of GlobPOP dataset in both population count and population density formats, researchers and policymakers can leverage our dataset to conduct time-series analysis of population and explore the spatial patterns of population development at various scales, ranging from national to city level.

Data description

The product is produced in 30 arc-seconds resolution(approximately 1km in equator) and is made available in GeoTIFF format. There are two population formats, one is the 'Count'(Population count per grid) and another is the 'Density'(Population count per square kilometer each grid)

Each GeoTIFF filename has 5 fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below with the example filename:

GlobPOP_Count_30arc_1990_I32

Field 1: GlobPOP(Global gridded population)
Field 2: Pixel unit is population "Count" or population "Density"
Field 3: Spatial resolution is 30 arc seconds
Field 4: Year "1990"
Field 5: Data type is I32(Int 32) or F32(Float32)

More information

Please refer to the paper for detailed information:

Liu, L., Cao, X., Li, S. et al. A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning. Sci Data 11, 124 (2024). https://doi.org/10.1038/s41597-024-02913-0.

The fully reproducible codes are publicly available at GitHub: https://github.com/lulingliu/GlobPOP.

Population databases are forming the backbone of many important studies modelling the complex interactions between population growth and environmental degradation, predicting the effects of global climate change on humans, and assessing the risks of various hazards such as floods, air pollution and radiation. Detailed information on population size, growth and distribution (along with many other environmental parameters) is of fundamental importance to such efforts. This database includes rural population distributions, population distrbution for cities and gridded global population distributions.

 This project has provided a population database depicting the
 worldwide distribution of population in a 1X1 latitude/longitude grid
 system. The database is unique, firstly, in that it makes use of the
 most recent data available (1990). Secondly, it offers true
 apportionment for each grid cell that is, if a cell contains
 populations from two different countries, each is assigned a
 percentage of the grid cell area, rather than artificially assigning
 the whole cell to one or the other country (this is especially
 important for European countries). Thirdly, the database gives the
 percentage of a country's total population accounted for in each
 cell. So if a country's total in a given year around 1990 (1989 or
 1991, for example) is known, then population in each cell can be
 calculated by using the percentage given in the database with the
 assumption that the growth rate in each cell of the country is the
 same. And lastly, this dataset is easy to be updated for each country
 as new national population figures become available.

Human population densities retrieved from UN open data resources in 1000 units.

The geographic distribution of human population is key to understanding the effects of humans on the natural world and how natural events such as storms, earthquakes, and other natural phenomenon affect humans. Dataset SummaryThis layer was created with a model that combines imagery, road intersection density, populated places, and urban foot prints to create a likelihood surface. The likelihood surface is then used to create a raster of population with a cell size of 0.00221 degrees (approximately 250 meters).The population raster is created usingDasymetriccartographic methods to allocate the population values in over 1.6 million census polygons covering the world.The population of each polygon was normalized to the 2013 United Nations population estimates by country.Each cell in this layer has an integer value depicting the number of people that are likely to reside in that cell. Tabulations based on these values should result in population totals that more accurately reflect the population of areas of several square kilometers.This layer has global coverage and was published by Esri in 2014.More information about this layer is available:Building the Most Detailed Population Map in the World

The average for 2023 based on 196 countries was 0.51 percent. The highest value was in India: 17.91 percent and the lowest value was in Andorra: 0 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

This dataset categorizes pixels with estimated zero population based on information provided in the census documents. General Documentation The Gridded Population of World Version 4 (GPWv4), Revision 11 models the distribution of global human population for the years 2000, 2005, 2010, 2015, and 2020 on 30 arc-second (approximately 1 km) …

LANDSCAN GLOBAL 2022

Contact: Human Dynamics Section, Geospatial Science and Human Security Division, Oak Ridge National Laboratory

Address: landscan@ornl.gov

Online Resource: https://landscan.ornl.gov

Standard Name: ISO 19139 Geographic Information - Metadata - Implementation Specification

Standard Version: 2007

Title: LandScan Global 2022

Publication Date: 2023-07-01

Creation Date: Human Dynamics Section, Geospatial Science and Human Security Division, Oak Ridge National Laboratory

Other Citation Details: https://doi.org/10.48690/1529167

Abstract: Using an innovative approach that combines Geographic Information Science, remote sensing technology, and machine learning algorithms, ORNL’s LandScan is the community standard for global population distribution. At 30 arc-second (approximately 1 km) resolution, LandScan is the finest resolution global population distribution data available representing an “ambient population” (average over 24 hours). The LandScan algorithm, an R&D 100 Award Winner, uses spatial data, high-resolution imagery exploitation, and a multi-variable dasymetric modeling approach to disaggregate census counts within an administrative boundary. LandScan population data are spatially explicit - unlike tabular Census data. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution models are tailored to match the data conditions and geographical nature of each individual country and region. By modeling an ambient population, LandScan Global captures the full potential activity space of people throughout the course of the day and night rather than just a residential location.

Purpose: LandScan Global was developed on behalf of the U.S. federal government and is used for rapid consequence and risk assessment as well as emergency planning and management.

Credit: Human Dynamics, Geospatial Science and Human Security Division, Oak Ridge National Laboratory; US DOD

Creative Commons Attribution 4.0 International License

https://landscan.ornl.gov/licensing

Oak Ridge National Laboratory