This layer was created by Duncan Smith and based on work by the European Commission JRC and CIESIN. A description from his website follows:--------------------A brilliant new dataset produced by the European Commission JRC and CIESIN Columbia University was recently released- the Global Human Settlement Layer (GHSL). This is the first time that detailed and comprehensive population density and built-up area for the world has been available as open data. As usual, my first thought was to make an interactive map, now online at- http://luminocity3d.org/WorldPopDen/The World Population Density map is exploratory, as the dataset is very rich and new, and I am also testing out new methods for navigating statistics at both national and city scales on this site. There are clearly many applications of this data in understanding urban geographies at different scales, urban development, sustainability and change over time.

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

Author: Joseph Kerski, post_secondary_educator, Esri and University of DenverGrade/Audience: high school, ap human geography, post secondary, professional developmentResource type: lessonSubject topic(s): population, maps, citiesRegion: africa, asia, australia oceania, europe, north america, south america, united states, worldStandards: All APHG population tenets. Geography for Life cultural and population geography standards. Objectives: 1. Understand how population change and demographic characteristics are evident at a variety of scales in a variety of places around the world. 2. Understand the whys of where through analysis of change over space and time. 3. Develop skills using spatial data and interactive maps. 4. Understand how population data is communicated using 2D and 3D maps, visualizations, and symbology. Summary: Teaching and learning about demographics and population change in an effective, engaging manner is enriched and enlivened through the use of web mapping tools and spatial data. These tools, enabled by the advent of cloud-based geographic information systems (GIS) technology, bring problem solving, critical thinking, and spatial analysis to every classroom instructor and student (Kerski 2003; Jo, Hong, and Verma 2016).

Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

Web Map Service that supports the IRENA Global Atlas for Renewable EnergyThe LandScan 2018 Global Population Database was developed by Oak Ridge National Laboratory (ORNL) for the United States Department of Defense (DoD).ORNL’s LandScan™ is a community standard for global population distribution data. At approximately 1 km (30″ X 30″) spatial resolution, it represents an ambient population (average over 24 hours) distribution. The database is refreshed annually and released to the broader user community around October. LandScan™ is now available at no cost to the educational community. The latest LandScan™ dataset available is LandScan Global 2018. Older LandScan Global data sets (LandScan 1998, 2000-2017) are available through site. These data set can be licensed for commercial and other applications through multiple third-party vendors. LandScan is developed using best available demographic (Census) and geographic data, remote sensing imagery analysis techniques within a multivariate dasymetric modeling framework to disaggregate census counts within an administrative boundary. 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 is essentially a combination of locally adoptive models that are tailored to match the data conditions and geographical nature of each individual country and region.

The Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) data set. The grids were created by using rates of population change between decades from the coarser resolution History Database of the Global Environment (HYDE) database to back-cast the GRUMPv1 population density grids. Mismatches between the spatial extent of the HYDE calculated rates and GRUMPv1 population data were resolved via infilling rate cells based on a focal mean of values. Finally, the grids were adjusted so that the population totals for each country equaled the UN World Population Prospects (2008 Revision) estimates for that country for the respective year (1970, 1980, 1990, and 2000). These data do not represent census observations for the years prior to 2000, and therefore can at best be thought of as estimations of the populations in given locations. The population grids are consistent internally within the time series, but are not recommended for use in creating longer time series with any other population grids, including GRUMPv1, Gridded Population of the World, Version 4 (GPWv4), or non-SEDAC developed population grids. These population grids served as an input to SEDAC's Global Estimated Net Migration Grids by Decade: 1970-2000 data set.

The Global Human Settlement Layer (GHSL) project is supported by European Commission, Joint Research Center and Directorate-General for Regional and Urban Policy. The GHSL produces new global spatial information, evidence-based analytics, and knowledge describing the human presence in the planet.

The GHSL relies on the design and implementation of new spatial data mining technologies allowing to process automatically and extract analytics and knowledge from large amount of heterogeneous data including: global, fine-scale satellite image data streams, census data, and crowd sources or volunteering geographic information sources. Spatial data reporting objectively and systematically about the presence of population and built-up infrastructures are necessary for any evidence-based modelling or assessing of i) human and physical exposure to threats as environmental contamination and degradation, natural disasters and conflicts, ii) impact of human activities on ecosystems, and iii) access to resources.

This spatial raster dataset depicts the distribution and density of population, expressed as the number of people per cell. Residential population estimates for target years 1975, 1990, 2000 and 2015 provided by CIESIN GPWv4 were disaggregated from census or administrative units to grid cells, informed by the distribution and density of built-up as mapped in the Global Human Settlement Layer (GHSL) global layer per corresponding epoch.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

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.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.Other New Zealand GeoInquiry instructional material freely available at https://arcg.is/1GPDXe

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.

Overview

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Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

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Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)

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Urban areas worldwide, from the Natural Earth project.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

Population data for a selection of countries, allocated to 1 arcsecond blocks and provided in a combination of CSV and Cloud-optimized GeoTIFF files. This refines CIESIN’s Gridded Population of the World using machine learning models on high-resolution worldwide Maxar satellite imagery. CIESIN population counts aggregated from worldwide census data are allocated to blocks where imagery appears to contain buildings.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

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 population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

Author: S Wicklund, educator, Minnesota Alliance for Geographic EducationGrade/Audience: high schoolResource type: lessonSubject topic(s): population, mapsRegion: worldStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.

Standard 3. Places have physical characteristics (such as climate, topography and vegetation) and human characteristics (such as culture, population, political and economic systems).

Standard 5. The characteristics, distribution and migration of human populations on the earth’s surface influence human systems (cultural, economic and political systems).Objectives: Students will be able to:

1. Use maps of population distribution to examine the history of world population growth.
2. Construct a dot map to show current world population distribution.
3. Describe the difference between arithmetic and physiological densities.
4. Craft a response to a prompt to evaluate the Negative Population Growth perspective. Summary: Students will use maps of population distribution to examine the history of world population growth. They will also examine current world population distribution. Students will role-play the difference between arithmetic and physiologic densities using Egypt as an example. They will then craft a response to a prompt where they evaluate the Negative Population Growth perspective.

The FGGD estimated 2015 global population density map is a global raster datalayer with a resolution of 2.5 arc-minutes. Each pixel contains an estimated value for persons per square kilometre in 2015, obtained by applying population growth trends to population counts for the lowest subnational administrative unit for which 2000 population data were available. The method used by FAO and CIESIN to generate this datalayer is described in FAO, 2005, Mapping global urban and rural population distributions, by M. Salvatore, et. al.

Populated places of the world.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.