WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Stevens et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020. These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map populations for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

Together with the Russian Academy of Sciences, IIASA's Forestry (FOR) project has released a CD-ROM titled Land Resources of Russia, Version 1.1, containing socioeconomic and biophysical data sets on important targets of international conventions — climate change, wetlands, desertification, and biodiversity. The CD-ROM, a country-scale integrated information system, supports sustainable use of land resources in line with Chapter 10 of Agenda 21 (UNCED) and makes a contribution to the Rio+10 Summit.

The Project's analysis of land resources are crucial for doing full greenhouse gas (or carbon) accounting. Integrated land analyses are also important for the introduction of sustainable forest management. FOR's land analyses concentrate on Russia, which is used as a case study for full carbon and greenhouse accounting.

Russia's area of forests, called here the forest zone, covers about 1180 million ha or 69% of the land of the country. The forested area (forests forming closed stands) occupies some 765 million ha constituting 65% of the forest zone. Forests are elements of a land-cover mosaic that direct the features of landscapes, ecosystems, vegetation and land uses. The FOR project attempts to overcome the traditional approach of just considering the direct utilities of forests. Instead, FOR operates with a holistic view of forests in a fully-fledged land concept. Integrated analysis of the land requires extended databases that includes various data for the total land operated in the form of GIS-based tools.

The land databases on Russia are the most comprehensive ever assembled, inside or outside of Russia. The databases have been enriched by remotely sensed data, biogeochemical functionality (carbon analysis), and institutional frameworks. The data included on the CD-ROM have been specially selected and filtered to meet the following criteria: (1) completeness: to meet a variety of the analysis tasks; (2) complexity: to describe a diversity of the task aspects; (3) consistency: to provide compatible results; to be ata compatible scale and, to provide a compatible time horizon; and (4) uniformity: to allow them to be standardized and formatted according to modern data handling routines.

The following databases and coverages are included on the CD-ROM and are available for download:

Socioeconomic Database -- Describes the social environment of each administrative region in Russia with close to 7000 parameters. The data cover the years 1987-1993. Coverages in this section include:

(1) Socioeconomic Statistical Database. This database provides the following statistical data sets: Population; Labor and Salary; Industry; Agriculture; Capital Construction; Communication and Transport; State Trade and Catering; Utilities and Services; Health Care and Sport; Education and Culture; Finance; Public Consumption; Industrial Production; Interregional Trade; Labor Resources; Supply of Materials; Environmental Protection; Foreign Trade; and Price Indices.

(2) Population Database. Adapted from Center for International Earth Science Information Network (CIESIN), Columbia University; International Food Policy Research Institute (IFPRI); and World Resources Institute (WRI). 2000. Gridded Population of the World (GPW), Version 2, this coverage contains population densities for 1995 on a 2.5 degree grid. Data were adjusted to match United Nations national population estimates for 1995.

(3) Administrative Oblasts, Cities & Towns Database. Oblasts coverage contains 92 polygons, 88 of which contain Oblast names, the other four represent waterbodies. The cities coverage contains 37 cities identified by name.

(4) Transportation Database. The statistical data sets and maps cover the transport routes of the railway, road, and river networks spanning the entire country. Railways and roads are classified by type and status, and major rivers are named. Map coverages (line data) were created from the Digital Chart of the World, using the 1993 version at the 1:1,000,000 scale.

Natural Conditions Database. This section of the CD-ROM contains the basic land characteristics. This database provides specialists and scientists in research institutes and international agencies with the capability to perform scientific analysis with a Geographic Information System. These data describe land characteristics that might be applied in various ways, such as individual items (e.g., temperature, elevation, vegetation community, etc.), in combination (e.g., forest-temperature associations, soil spectra for land use types, etc.), and as aggregations based on a conceptual framework of a different level of complexity (e.g., ecosystem establishment, human-induced land cover transformation, biochemical cycle analysis, etc.). Coverage includes:

(1) Climate Database. Temperature (annual and seasonal) and Precipitation... Visit https://dataone.org/datasets/Land_Resources_of_Russia%2C_Version_1.1.xml for complete metadata about this dataset.

This data set is the Former Soviet Union (FSU) portion of the Generalized World Forest Map (WCMC, 1998), a 1-kilometer resolution generalized forest cover map for the land area of the Former Soviet Union. There are five forest classes in the original global generalized map. Only two of those classes were distinguished in the geographical portion comprising the FSU.

The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.

This data set is a 1:2.5 million scale forest cover map for the land area of the Former Soviet Union that was completed in 1990 (Garsia 1990). There are forty-five classes distinguished in this data set, of which 38 are forest cover classes. The purpose of this map was to create a generalized and up-to-date map of forest cover for the USSR. This map should not be viewed as a detailed forest cover map but more like an economic forestry map. The most important tree species of a region are highlighted rather than the dominant trees species or tree cover. Very few tree species are defined. In many cases, of course, the dominant and the most important trees species are the same.

This data set consists of roads, drainage, railroads, utilities, and population center information in readily usable vector format for the land area of the Former Soviet Union. The purpose of this dataset was to create a completely intact vector layer which could be readily used to aid in mapping efforts for the area of the FSU. These five vector data layers were assembled from the Digital Chart of the World (DCW), 1993. Individual record attributes were stored for population centers only. Vector maps for the FSU are in ArcView shapefile format.

Norway’s borders on land and sea contain the county and municipal division as of 1 January 2020. A table provides an overview of the counties, municipalities, administrative site, area and population. The map also shows Norway’s maritime borders, and the agreed delimitation line against Russia, which entered into force on 7 July 2011.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

In 1938, the year before the outbreak of the Second world War, the countries with the largest populations were China, the Soviet Union, and the United States, although the United Kingdom had the largest overall population when it's colonies, dominions, and metropole are combined. Alongside France, these were the five Allied "Great Powers" that emerged victorious from the Second World War. The Axis Powers in the war were led by Germany and Japan in their respective theaters, and their smaller populations were decisive factors in their defeat. Manpower as a resource In the context of the Second World War, a country or territory's population played a vital role in its ability to wage war on such a large scale. Not only were armies able to call upon their people to fight in the war and replenish their forces, but war economies were also dependent on their workforce being able to meet the agricultural, manufacturing, and logistical demands of the war. For the Axis powers, invasions and the annexation of territories were often motivated by the fact that it granted access to valuable resources that would further their own war effort - millions of people living in occupied territories were then forced to gather these resources, or forcibly transported to work in manufacturing in other Axis territories. Similarly, colonial powers were able to use resources taken from their territories to supply their armies, however this often had devastating consequences for the regions from which food was redirected, contributing to numerous food shortages and famines across Africa, Asia, and Europe. Men from annexed or colonized territories were also used in the armies of the war's Great Powers, and in the Axis armies especially. This meant that soldiers often fought alongside their former-enemies. Aftermath The Second World War was the costliest in human history, resulting in the deaths of between 70 and 85 million people. Due to the turmoil and destruction of the war, accurate records for death tolls generally do not exist, therefore pre-war populations (in combination with other statistics), are used to estimate death tolls. The Soviet Union is believed to have lost the largest amount of people during the war, suffering approximately 24 million fatalities by 1945, followed by China at around 20 million people. The Soviet death toll is equal to approximately 14 percent of its pre-war population - the countries with the highest relative death tolls in the war are found in Eastern Europe, due to the intensity of the conflict and the systematic genocide committed in the region during the war.

The world's Jewish population has had a complex and tumultuous history over the past millennia, regularly dealing with persecution, pogroms, and even genocide. The legacy of expulsion and persecution of Jews, including bans on land ownership, meant that Jewish communities disproportionately lived in urban areas, working as artisans or traders, and often lived in their own settlements separate to the rest of the urban population. This separation contributed to the impression that events such as pandemics, famines, or economic shocks did not affect Jews as much as other populations, and such factors came to form the basis of the mistrust and stereotypes of wealth (characterized as greed) that have made up anti-Semitic rhetoric for centuries. Development since the Middle Ages The concentration of Jewish populations across the world has shifted across different centuries. In the Middle Ages, the largest Jewish populations were found in Palestine and the wider Levant region, with other sizeable populations in present-day France, Italy, and Spain. Later, however, the Jewish disapora became increasingly concentrated in Eastern Europe after waves of pogroms in the west saw Jewish communities move eastward. Poland in particular was often considered a refuge for Jews from the late-Middle Ages until the 18th century, when it was then partitioned between Austria, Prussia, and Russia, and persecution increased. Push factors such as major pogroms in the Russian Empire in the 19th century and growing oppression in the west during the interwar period then saw many Jews migrate to the United States in search of opportunity.

In 2024, Monaco was the European country estimated to have the highest fertility rate. The country had a fertility rate of 2.1 children per woman. Other small countries such as Gibraltar or Montenegro also came towards the top of the list for 2024, while the large country with the highest fertility rate was France, with 1.64 children per woman. On the other hand, Ukraine had the lowest fertility rate, averaging around one child per woman.