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.

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.

This dataset provides annual numbers for each state in the United States for 2013-2018. Includes the following data: total population, median income, and number of people living at or below the poverty level.

Helpful information on using U.S. Census data is found at https://censusreporter.org/

Dataset population: All usual residents aged 16 and over in employment the week before the census

Location of where people live when working

The location in which an individual lives when they are working.

Place of work

The location in which an individual works.

Geographies of origin areas:

• UK Local Authorities (merged) 2011

Geographies of destination areas:

• UK Local Authorities (merged) 2011
• 2011 UK SWS additional workplace codes

For the area in which people live while they are working, if that address is a work-related second address that is outside of the UK then this is signified by code OD0000005.

*The following codes are used for area of workplace that is not an LAD geographic code:

OD0000001 = Mainly work at or from home

OD0000002 = Offshore installation

OD0000003 = No fixed place

OD0000004 = Outside UK*

There are approximately 8.16 billion people living in the world today, a figure that shows a dramatic increase since the beginning of the Common Era. Since the 1970s, the global population has also more than doubled in size. It is estimated that the world's population will reach and surpass 10 billion people by 2060 and plateau at around 10.3 billion in the 2080s, before it then begins to fall. Asia When it comes to number of inhabitants per continent, Asia is the most populous continent in the world by a significant margin, with roughly 60 percent of the world's population living there. Similar to other global regions, a quarter of inhabitants in Asia are under 15 years of age. The most populous nations in the world are India and China respectively; each inhabit more than three times the amount of people than the third-ranked United States. 10 of the 20 most populous countries in the world are found in Asia. Africa Interestingly, the top 20 countries with highest population growth rate are mainly countries in Africa. This is due to the present stage of Sub-Saharan Africa's demographic transition, where mortality rates are falling significantly, although fertility rates are yet to drop and match this. As much of Asia is nearing the end of its demographic transition, population growth is predicted to be much slower in this century than in the previous; in contrast, Africa's population is expected to reach almost four billion by the year 2100. Unlike demographic transitions in other continents, Africa's population development is being influenced by climate change on a scale unseen by most other global regions. Rising temperatures are exacerbating challenges such as poor sanitation, lack of infrastructure, and political instability, which have historically hindered societal progress. It remains to be seen how Africa and the world at large adapts to this crisis as it continues to cause drought, desertification, natural disasters, and climate migration across the region.

Number of People living in an Area by County

This map compares the number of people living above the poverty line to the number of people living below. Why do this?There are people living below the poverty line everywhere. Nearly every area of the country has a balance of people living above the poverty line and people living below it. There is not an "ideal" balance, so this map makes good use of the national ratio of 6 persons living above the poverty line for every 1 person living below it. Please consider that there is constant movement of people above and below the poverty threshold, as they gain better employment or lose a job; as they encounter a new family situation, natural disaster, health issue, major accident or other crisis. There are areas that suffer chronic poverty year after year. This map does not indicate how long people in the area have been below the poverty line. "The poverty rate is one of several socioeconomic indicators used by policy makers to evaluate economic conditions. It measures the percentage of people whose income fell below the poverty threshold. Federal and state governments use such estimates to allocate funds to local communities. Local communities use these estimates to identify the number of individuals or families eligible for various programs." Source: U.S. Census BureauIn the U.S. overall, there are 6 people living above the poverty line for every 1 household living below. Green areas on the map have a higher than normal number of people living above compared to below poverty. Orange areas on the map have a higher than normal number of people living below the poverty line compared to those above in that same area.The map shows the ratio for counties and census tracts, using these layers, created directly from the U.S. Census Bureau's American Community Survey (ACS)For comparison, an older layer using 2013 ACS data is also provided.The layers are updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Poverty status is based on income in past 12 months of survey. Current Vintage: 2014-2018ACS Table(s): B17020Data downloaded from: Census Bureau's API for American Community Survey National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

A collaborative project between SPC, the World Fish Centre and the University of Wollongong has produced the first detailed population estimates of people living close to the coast in the 22 Pacific Island Countries and Territories (PICTs). These estimates are stratified into 1, 5, and 10km zones. More information about this dataset: https://sdd.spc.int/mapping-coastal

Most of the United States (U.S.) population live together in a few densely populated areas. While this is a well known fact, visual explanations of this characteristic can be quite striking. These four maps illustrate in different ways where we live, and how we actually inhabit so little of our country's space.Map 1 shows the coastal shoreline counties of the U.S., which are the counties that are directly adjacent to an open ocean, a major estuary, or the Great Lakes. According to 2014 Census data, 39.1 percent of the U.S. population lived in those counties, often within miles of the coast.Map 2 highlights the largest and smallest counties in the U.S. Roughly fifty percent of the U.S. population lives in the country's 144 largest counties, while the roughly other 50 percent lives in 2,998 counties.Map 3 compares America's two largest counties (Los Angeles and Downtown Chicago) with the 14 smallest states.Map 4 compares the population of these two counties with 1,437 of the country's smallest counties. Nearly five percent of America's population lives in the counties covering downtown Los Angeles and downtown Chicago, which is the same proportion as those that live in the country's 1,437 smallest counties.Source: Ana Swanson, Washington Post Wonkblog. September 3, 2015

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: All places defined by walls and roofs where one or more people live regularly, that is where they sleep, cook and protect themselves from the elements. Also people can enter and leave the mentioned without passing through another house, having direct access from the street, passage, path or passing through common areas such as patios, hallways, corridors or stairs. - Households: Group of people who live as a family - Group quarters: This is a place or building where a group of people without family ties resides and share the space for reasons of lodging, health, education, military, religion, old age, orphanhood, etc. This includes hotels, boarding houses, guest houses, hospitals, homes for the elderly, internment schools, hospices, jails, etc.

Universe

All people who live in the country and all households nationally. Homeless

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: General Directorate of Statistics and Censuses

SAMPLE SIZE (person records): 510760.

SAMPLE DESIGN: Stratified systematic sample. Homeless

Mode of data collection

Face-to-face [f2f]

Research instrument

Census questionnaire containing questions on demographic and socio-economic characteristics of the population, dwelling unit characteristics, emigration, and mortality.

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

Number of People living in an Area by County

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us at http://goto.arcgisonline.com/landscape7/World_Population_Density_Estimate_2016.This layer is a global estimate of human population density for 2016. The advantage population density affords over raw counts is the ability to compare levels of persons per square kilometer anywhere in the world. Esri calculated density by converting the the World Population Estimate 2016 layer to polygons, then added an attribute for geodesic area, which allowed density to be derived, and that was converted back to raster. A population density raster is better to use for mapping and visualization than a raster of raw population counts because raster cells are square and do not account for area. For instance, compare a cell with 185 people in northern Quito, Ecuador, on the equator to a cell with 185 people in Edmonton, Canada at 53.5 degrees north latitude. This is difficult because the area of the cell in Edmonton is only 35.5% of the area of a cell in Quito. The cell in Edmonton represents a density of 9,810 persons per square kilometer, while the cell in Quito only represents a density of 3,485 persons per square kilometer. Dataset SummaryEach cell in this layer has an integer value with the estimated number of people per square kilometer likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers: World Population Estimate 2016: this layer contains estimates of the count of people living within the the area represented by the cell. World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.What can you do with this layer?This layer is primarily intended for cartography and visualization, but may also be useful for analysis, particularly for estimating where people living above specified densities. There are two processing templates defined for this layer: the default, "World Population Estimated 2016 Density Classes" uses a classification, described above, to show locations of levels of rural and urban populations, and should be used for cartography and visualization; and "None," which provides access to the unclassified density values, and should be used for analysis. The breaks for the classes are at the following levels of persons per square kilometer:100 - Rural (3.2% [0.7%] of all people live at this density or lower) 400 - Settled (13.3% [4.1%] of all people live at this density or lower)1,908 - Urban (59.4% [81.1%] of all people live at this density or higher)16,978 - Heavy Urban (13.0% [24.2%] of all people live at this density or higher)26,331 - Extreme Urban (7.8% [15.4%] of all people live at this density or higher) Values over 50,000 are likely to be erroneous due to spatial inaccuracies in source boundary dataNote the above class breaks were derived from Esri's 2015 estimate, which have been maintained for the sake of comparison. The 2015 percentages are in gray brackets []. The differences are mostly due to improvements in the model and source data. While improvements in the source data will continue, it is hoped the 2017 estimate will produce percentages that shift less.For analysis, Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the average, highest, or lowest density within those zones.

Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

This map shows only shows the San Bernardino County as a view of the total population of people age 18+ in the San Bernardino County as well as the total population in that area. The map shows the density of the total population in 2020 and the total people who are 18+ in the San Bernardino County. This just goes to show that there are a lot of people living in the San Bernardino County who are at 18+ but most part there are more total population in 2020 then people counted to be 18+. A lot of citizens live in the population dense areas like Ontario, Rancho Cucamango, Fontana, and Redlands. On the other hand not a lot of people live in Big Bear City, and West Wood because it is more expensive to live up there than it is to live in an apartment in the bigger cities.To create this layer, the USA Census Tract layer from live atlas was filtered in San Bernardino County then enriched with 2020 data of number of total citizens in 2020 and citizens at the age of 18+.

Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: The dwelling is a building or collection of buildings used as the living unit of the household. - Households: A household is a set of people who live together. An ordinary household is as an individual or a group of people live together to collectively meet their food and other vital needs. It is made up of a group of people, related or not, who recognize the authority of an individual called the "head of household", live under the same roof or in the same compound and take their meals together. - Group quarters: A collective household is made up of a group of people, without a priori family tie, who live together in the same institution for health, study, work, travel, disciplinary or other reasons. Examples of collective households are boarding schools, barracks and military boarding schools, prisons, hotels, hospitals, convents, orphanages, boarding schools, etc.

Universe

The resident population, defined as all people who lived for at least six months in the households where they were enumerated or who intend to stay there for at least six months.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics

SAMPLE SIZE (person records): 1050916.

SAMPLE DESIGN: Systematic Sample of every 10th dwelling with a random start, drawn by IPUMS

Mode of data collection

Face-to-face [f2f]

Research instrument

The Ordinary Household Questionnaire

People living in households with very low work intensity are people aged 0-64 living in households where the adults (aged 18-64) worked less than 20% of their total work potential during the past year. Students, those who are retired or who receive any pension (except survivors pension) are excluded. The MIP auxiliary indicator is expressed as a percentage of the population aged 0 to 64. In the table, values are also presented as changes over a three-year period (in percentage points). The data source is the EU Statistics on Income and Living Conditions (EU-SILC).

This map features a global estimate of human population for 2016 with a focus on the Caribbean region . Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: https://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones.

Number of People living in an Area by sub-county

The coastal zones of Small Island States are hotspots of human habitation and economic endeavour. In the Pacific region, as elsewhere, there are large gaps in understandings of the exposure and vulnerability of people in coastal zones. The 22 Pacific Countries and Territories (PICTs) are poorly represented in global analyses of vulnerability to seaward risks. We combine several data sources to estimate populations to zones 1, 5 and 10 km from the coastline in each of the PICTs. Regional patterns in the proximity of Pacific people to the coast are dominated by Papua New Guinea. Overall, ca. half the population of the Pacific resides within 10 km of the coast but this jumps to 97% when Papua New Guinea is excluded. A quarter of Pacific people live within 1 km of the coast, but without PNG this increases to slightly more than half. Excluding PNG, 90% of Pacific Islanders live within 5 km of the coast. All of the population in the coral atoll nations of Tokelau and Tuvalu live within a km of the ocean. Results using two global datasets, the SEDAC-CIESIN Gridded Population of the World v4 (GPWv4) and the Oak Ridge National Laboratory Landscan differed: Landscan under-dispersed population, overestimating numbers in urban centres and underestimating population in rural areas and GPWv4 over-dispersed the population. In addition to errors introduced by the allocation models of the two methods, errors were introduced as artefacts of allocating households to 1 km x 1 km grid cell data (30 arc–seconds) to polygons. The limited utility of LandScan and GPWv4 in advancing this analysis may be overcome with more spatially resolved census data and the inclusion of elevation above sea level as an important dimension of vulnerability.