In terms of population size, the sex ratio in the United States favors females, although the gender gap is remaining stable. In 2010, there were around 5.17 million more women, with the difference projected to decrease to around 3 million by 2027.

Gender ratios by U.S. state In the United States, the resident population was estimated to be around 331.89 million in 2021. The gender distribution of the nation has remained steady for several years, with women accounting for approximately 51.1 percent of the population since 2013. Females outnumbered males in the majority of states across the country in 2020, and there were eleven states where the gender ratio favored men.

Metro areas by population National differences between male and female populations can also be analyzed by metropolitan areas. In general, a metropolitan area is a region with a main city at its center and adjacent communities that are all connected by social and economic factors. The largest metro areas in the U.S. are New York, Los Angeles, and Chicago. In 2019, there were more women than men in all three of those areas, but Jackson, Missouri was the metro area with the highest share of female population.

Abstract

The 2021 NPHC is tthe first census conducted under the federal structure of Nepal. The main census enumeration was originally scheduled to take place over 15 days- from June 8 to 22, 2021, but due to the COVID-19 pandemic, the enumeration was postponed for five months. Once the impact of the pandemic subsided, the enumeration was carried out according to a new work plan for a 15 dya period from November 11 to 25, 2021.

This report contains statistical tables at the national, provincial, district and municipal levels, derived from the topics covered in the census questionaires. The work of the analyzing the data in detail is still in progress. The report provides insights into the different aspects of the census operation, including its procedure, concepts, methodology, quality control, logistics, communication, data processing, challenges faced, and other management aspects.

This census slightly differs from the previous censuses mainly due to the following activities: i. three modes of data collection (CAPI, PAPI and e-census); ii. a full count of all questions instead of sampling for certain questions, as was done in the previous two censuses, iii. collaboration with Ministry of Health and Population to ascertain the likely maternal mortality cases reported in the census by skilled health personnel; iv. data processing within its premises; v. recuitment of fresh youths as supervisor and enumerators; and vi. using school teachers as master trainers, especially for the local level training of enumerators.

The objectives of the 2021 Population Census were:

a) to develop a set of benchmark data for different purposes. b) to provide distribution of population by demographic, social and economic characteristics. c) to provide data for small administrative areas of the country on population and housing characteristics. d) to provide reliable frames for different types of sample surveys. e) to provide many demographic indicators like birth rates, death rates and migration rates. f) to project population for the coming years.

The total population of Nepal, as of the census day (25 November 2021) is 29,164,578, of which the number of males is 14,253,551 (48.87 %) and the number of females is 14,911,027 (51.13 %). Accordingly, the sex ratio is 95.59 males per 100 females. Annual average population growth rate is 0.92 percent in 2021.

Geographic coverage

National Level, Ecological belt, Urban and Rural, Province, District, Municipality, Ward Level

Analysis unit

The census results provide information up to the ward level (the lowest administrative level of Nepal), household and indivisual.

Universe

The census covered all modified de jure household members (usual residents)

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f] and online

Research instrument

In this census three main questionnaires were developed for data collection. The first was the Listing Form deveoped mainly for capturing the basic household informatioin in each Enumeration area of the whole country. The second questionnaire was the main questionnaire with eight major Sections as mentioned hereunder.

Listing Questionaire Section 1. Introduction Section 2. House information Section 3. Household information Section 4. Agriculture and livestock information Section 5. Other information

Main Questionaire Section 1. Introduction Section 2. Household Information Section 3. Individual Information Section 4. Educational Information Section 5. Migration Section 6. Fertility Section 7.Disability Section 8. Economic Activity

For the first time, the NPHC, 2021 brougt a Community Questionnaire aiming at capturing the socio-economic and demographic characteristics of the Wards (the lowest administrative division under Rural/Urban Municipalities). The Community Questionnaire contains 6 Chapters. The information derived from community questionnaire is expected to validate (cross checks) certain information collected from main questionnaire.

Community questionaire Section 1. Introduction Section 2. Basic information of wards Section 3. Caste and mother tongue information Section 4. Current status of service within wards Section 5. Access of urban services and facilities within wards Section 6. Status of Disaster Risk

It is noteworty that the digital version of questionnare was applied in collecting data within the selected municipalities of Kathmandu Valley. Enumerators mobilized in Kathmandu Valley were well trained to use tablets. Besides, online mode of data collection was adpoted for all the Nepalese Diplomatic Agencies located abroad.

Cleaning operations

For the concistency of data required logics were set in the data entry programme. For the processing and analysis of data SPSS and STATA programme were employed.

Discover the latest total population statistics for every country and region worldwide. Explore accurate, up-to-date data on global population growth, density, and demographic trends — sourced from trusted international databases like the UN and World Bank. Perfect for researchers, students, and data enthusiasts looking to understand how the world’s population is changing.

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 brief summarizes the existing guidance and recommendations related to identifying and surveying youth in the follow-up population at age 21.

Metadata-only record linking to the original dataset. Open original dataset below.

The statistic shows the total population in the United States from 2015 to 2021, with projections up until 2027. In 2021, the total population of the U.S. amounted to approximately 332.18 million inhabitants.

The United States' economy over the last decade

The United States of America is the world’s largest national economy and the second most prominent trader globally, trailing just behind China. The country is also one of the most populated countries in the world, trailing only China and India. The United States' economy prospers primarily due to having a plentiful amount of natural resources and advanced infrastructure to cope with the production of goods and services, as well as the population and workforce to enable high productivity. Efficient productivity led to a slight growth in GDP almost every year over the past decade, despite undergoing several economic hardships towards the late 2000's.

In addition, the United States holds arguably one of the most important financial markets, with the majority of countries around the world having commercial connections with American companies. Dependency on a single market like the United States has however caused several global dilemmas, most evidently seen during the 2008 financial crisis. What initially started off as a bursting of the U.S. housing bubble lead to a worldwide recession and the necessity to reform national economics. The global financial crisis affected the United States most drastically, especially within the unemployment market as well as national debt, which continued to rise due to the United States having to borrow money in order to stimulate its economy.

According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.

The JRC-CENSUS Population Grid 2021 is a dataset providing residential population counts for Europe according to the 2021 census at a resolution of 100 x 100 metre cells. UNIT OF MEASURE: Total resident population. RESOLUTION: 100 metre. COMPLETENESS: 100%. POLICY CONTEXT: This dataset was produced in the context of a collaboration between the JRC and Eurostat to enable analyses of population distribution at high spatial resolution and improved compatibility with other high-resolution spatial datasets. METHODOLOGY: The JRC-CENSUS 2021 100 m grid was derived from the CENSUS 2021 1 km grid through the application of the dasymetric mapping technique. This approach consisted in the disaggregation of population counts from a coarse resolution grid (1 km) to a finer one (100 m) using proxy data at the targeted spatial resolution (100 m). The proxy layer - residential built-up volume - was produced by combining building footprints, land use and building height data from multiple data sources. DATA SOURCES: Eurostat Census grid 2021 V2-0 (version 16-06-2024), DBSMv1 R2023, EUBUCCO v0.1, OVERTURE Maps 2024-09-18.0, LUISA Base Map 2018, HR Water and Wetness Layer 2018, Coastal Zones LCLU 2018, GHS-BUILT-V R2023A, Urban Atlas Building Height 2012- v2, GHS-BUILT-ANBH, R2023A, TomTom Multinet 2018. UNCERTAINTY AND LIMITATIONS: The proxy layer inherits inaccuracies from the original datasets, including land-use classification errors, omission and commission errors, and uncertainties in building height measurements. Moreover, the disaggregation assumes a perfect correlation between residential population and residential built-up volume within each 1 km cell. These two issues ultimately affect the final quality of the JRC-CENSUS 2021 100 m population grid.

Footnotes: 1 Population estimates based on the Standard Geographical Classification (SGC) 2016 as delineated in the 2016 Census. 2 A census metropolitan area (CMA) or a census agglomeration (CA) is formed by one or more adjacent municipalities centred on a population centre (known as the core). A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core based on adjusted data from the previous Census of Population Program. A CA must have a core population of at least 10,000 also based on data from the previous Census of Population Program. To be included in the CMA or CA, other adjacent municipalities must have a high degree of integration with the core, as measured by commuting flows derived from data on place of work from the previous Census Program. If the population of the core of a CA falls below 10,000, the CA is retired from the next census. However, once an area becomes a CMA, it is retained as a CMA even if its total population declines below 100,000 or the population of its core falls below 50,000. All areas inside the CMA or CA that are not population centres are rural areas. When a CA has a core of at least 50,000, based on data from the previous Census of Population, it is subdivided into census tracts. Census tracts are maintained for the CA even if the population of the core subsequently falls below 50,000. All CMAs are subdivided into census tracts (2016 Census Dictionary, catalogue number 98-301-X2016001). 3 An area outside census metropolitan areas and census agglomerations is made up of all areas (within a province or territory) unallocated to a census metropolitan area (CMA) or census agglomeration (CA). 4 Postcensal estimates are based on the latest census counts adjusted for census net undercoverage (including adjustment for incompletely enumerated Indian reserves) and for the estimated population growth that occurred since that census. Intercensal estimates are based on postcensal estimates and census counts adjusted of the censuses preceding and following the considered year. 5 Population estimates as of July 1 are final intercensal up to 2015, final postcensal for 2016 to 2019, updated postcensal for 2020 and preliminary postcensal for 2021. 6 The population growth, which is used to calculate population estimates of census metropolitan areas and census agglomerations (table 17100135), is comprised of the components of population growth (table 17100136). 7 This table replaces table 17100078. 8 Age on July 1.

This table contains data from the censuses of the municipal population since 2013 of each French region. Collection Context The data is uploaded to the [INSEE] website(https://www.insee.fr/fr/accueil) and then integrated into a repository database to make it available to GIS users and departmental agents. The municipal population includes persons: * having their habitual residence in the territory of the municipality, in a dwelling or community; * detained in the penal institutions of the municipality; * homeless persons registered in the territory of the municipality; * usually residing in a mobile dwelling registered in the territory of the municipality. The municipal population of a group of municipalities is equal to the sum of the municipal populations of the municipalities that make up it. The concept of municipal population now corresponds to the concept of population used in statistics. It does not contain double accounts: every person living in France is counted once and only once. In 1999, the concept of a population without double counting corresponded to the notion of a statistical population. The concept of municipal population is defined by Decree No. 2003-485 published in the Official Journal of 8 June 2003 on the population census (source INSEE). Collection method Every year, the table is updated. A new field is created and filled in with the data from the last census of the municipal population. Attributes | field | Alias ▲ Type | – | – — | ‘objectID’ | Unique identifier ‘integer’ | ‘Reg’ | Region code ⋆ ‘char’ -’ | ‘name_reg’ | Name of the region ⋆ ‘char’ | ‘superf’ | Area ▲ ‘double’ ⋆ | ‘p14_pop’ | Municipal population 2017 – 2014 Census ⋆ ‘integer’ — | ‘p15_pop’ | Municipal population 2018 – Census 2015 ⋆ ‘integer’ ⋆ | ‘p16_pop’ | Municipal population 2019 – Census 2016 ⋆ ‘integer’ ⋆ | ‘p17_pop’ | Municipal population 2020 – Census 2017 ⋆ ‘integer’ ⋆ | ‘p18_pop’ | Municipal population 2021 – 2018 Census ▲ ‘integer’ ⋆ | ‘p19_pop’ | Municipal population 2022 – 2019 Census ▲ ‘integer’ ⋆ | ‘p20_pop’ | Municipal population 2023 – 2020 census ⋆ ‘integer’ | ‘p21_pop’ | Municipal population 2024 – Census 2021 ⋆ ‘integer’ -’ For more information, see the metadata on the Isogeo catalog.

This data contains all the essential data in the form of % with respect to rural and urban Indian states . This dataset is highly accurate as this is taken from the Indian govt. it is updated till 2021 for all states and union territories. source of data is data.gov.in titled - ******All India and State/UT-wise Factsheets of National Family Health Survey******

it is advised to you pls search the data keywords you need by using (Ctrl+f) , as it will help to avoid time wastage. States/UTs

Different columns it contains are Area

Number of Households surveyed Number of Women age 15-49 years interviewed Number of Men age 15-54 years interviewed

Female population age 6 years and above who ever attended school (%)

Population below age 15 years (%)

Sex ratio of the total population (females per 1,000 males)

Sex ratio at birth for children born in the last five years (females per 1,000 males)

Children under age 5 years whose birth was registered with the civil authority (%)

Deaths in the last 3 years registered with the civil authority (%)

Population living in households with electricity (%)

Population living in households with an improved drinking-water source1 (%)

Population living in households that use an improved sanitation facility2 (%)

Households using clean fuel for cooking3 (%) Households using iodized salt (%)

Households with any usual member covered under a health insurance/financing scheme (%)

Children age 5 years who attended pre-primary school during the school year 2019-20 (%)

Women (age 15-49) who are literate4 (%)

Men (age 15-49) who are literate4 (%)

Women (age 15-49) with 10 or more years of schooling (%)

Men (age 15-49) with 10 or more years of schooling (%)

Women (age 15-49) who have ever used the internet (%)

Men (age 15-49) who have ever used the internet (%)

Women age 20-24 years married before age 18 years (%)

Men age 25-29 years married before age 21 years (%)

Total Fertility Rate (number of children per woman) Women age 15-19 years who were already mothers or pregnant at the time of the survey (%)

Adolescent fertility rate for women age 15-19 years5 Neonatal mortality rate (per 1000 live births)

Infant mortality rate (per 1000 live births) Under-five mortality rate (per 1000 live births)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Any method6 (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Any modern method6 (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Female sterilization (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Male sterilization (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - IUD/PPIUD (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Pill (%)  

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Condom (%)

Current Use of Family Planning Methods (Currently Married Women Age 15-49 years) - Injectables (%)

Total Unmet need for Family Planning (Currently Married Women Age 15-49 years)7 (%)

Unmet need for spacing (Currently Married Women Age 15-49 years)7 (%)

Health worker ever talked to female non-users about family planning (%)

Current users ever told about side effects of current method of family planning8 (%)

Mothers who had an antenatal check-up in the first trimester (for last birth in the 5 years before the survey) (%)

Mothers who had at least 4 antenatal care visits (for last birth in the 5 years before the survey) (%)

Mothers whose last birth was protected against neonatal tetanus (for last birth in the 5 years before the survey)9 (%)

Mothers who consumed iron folic acid for 100 days or more when they were pregnant (for last birth in the 5 years before the survey) (%)

Mothers who consumed iron folic acid for 180 days or more when they were pregnant (for last birth in the 5 years before the survey} (%)

Registered pregnancies for which the mother received a Mother and Child Protection (MCP) card (for last birth in the 5 years before the survey) (%)

Mothers who received postnatal care from a doctor/nurse/LHV/ANM/midwife/other health personnel within 2 days of delivery (for last birth in the 5 years before the survey) (%)

Average out-of-pocket expenditure per delivery in a public health facility (for last birth in the 5 years before the survey) (Rs.)

Children born at home who were taken to a health facility for a check-up within 24 hours of birth (for last birth in the 5 years before the survey} (%)

Children who received postnatal care from a doctor/nurse/LHV/ANM/midwife/ other health personnel within 2 days of delivery (for last birth in the 5 years before the survey) (%)

Institutional births (in the 5...

These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the The Foreign, Commonwealth & Development Office (FCDO) (OPP1182408). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

Burkina Faso: WorldPop and Institut National de la Statistique et de la Démographie du Burkina Faso. 2021. Census based gridded population estimates for Burkina Faso (2019), version 1.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00687

Democratic Republic of the Congo: Boo G, Darin E, Leasure DR, Dooley CA, Chamberlain HR, Lazar AN, Tatem AJ. 2020. Modelled gridded population estimates for the Kinshasa, Kongo-Central, Kwango, Kwilu, and Mai-Ndombe provinces in the Democratic Republic of the Congo, version 2.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00669

Ghana: Leasure DR, Darin E, Tatem AJ. 2021. Bayesian gridded population estimates for Ghana 2019 (GHA v2.0). WorldPop, University of Southampton. doi:10.5258/SOTON/WP00705.

Mozambique: Bondarenko M, Jones P, Leasure D, Lazar AN, Tatem AJ. 2020. Census disaggregated gridded population estimates for Mozambique (2017), version 1.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00672

Nigeria: WorldPop. 2019. Bottom-up gridded population estimates for Nigeria, version 1.2. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00655

South Sudan: Dooley CA, Jochem WC, Leasure, DR, Sorichetta A, Lazar AN and Tatem AJ. 2021. South Sudan 2020 gridded population estimates from census projections adjusted for displacement, version 2.0. WorldPop, University of Southampton. doi: 10.5258/SOTON/WP00709

Zambia: WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. Bottom-up gridded population estimates for Zambia, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00662

Footnotes: 1 Population estimates based on the Standard Geographical Classification (SGC) 2016 as delineated in the 2016 Census. 2 A census metropolitan area (CMA) or a census agglomeration (CA) is formed by one or more adjacent municipalities centred on a population centre (known as the core). A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core based on adjusted data from the previous Census of Population Program. A CA must have a core population of at least 10,000 also based on data from the previous Census of Population Program. To be included in the CMA or CA, other adjacent municipalities must have a high degree of integration with the core, as measured by commuting flows derived from data on place of work from the previous Census Program. If the population of the core of a CA falls below 10,000, the CA is retired from the next census. However, once an area becomes a CMA, it is retained as a CMA even if its total population declines below 100,000 or the population of its core falls below 50,000. All areas inside the CMA or CA that are not population centres are rural areas. When a CA has a core of at least 50,000, based on data from the previous Census of Population, it is subdivided into census tracts. Census tracts are maintained for the CA even if the population of the core subsequently falls below 50,000. All CMAs are subdivided into census tracts (2016 Census Dictionary, catalogue number 98-301-X2016001). 3 An area outside census metropolitan areas and census agglomerations is made up of all areas (within a province or territory) unallocated to a census metropolitan area (CMA) or census agglomeration (CA). 4 The population growth, which is used to calculate population estimates of census metropolitan areas and census agglomerations (table 17100135), is comprised of the components of population growth (table 17100136). 5 This table replaces table 17100079. 6 The components of population growth for census metropolitan areas (CMAs) and census agglomerations (CAs) sometimes had to be calculated using information at the census division level, using the geographic conversion method. This method involves using the population component calculated at the level of the CD(s) in which the CMA or CA is located and applying a ratio corresponding to the proportion of the CMA or CA population included in the corresponding CD(s). For periods prior to 2005/2006, all demographic components for all CMAs and CAs were calculated using geographic conversions. For the periods from 2005/2006 to 2010/2011 inclusively, emigration and internal migration components for areas that were not CMAs according to the 2011 SGC were calculated using geographic conversions. For the periods 2011/2012 to 2015/2016 inclusively, the emigration and internal migration components of regions that were not CMAs or CAs according to the 2011 SGC were calculated using geographic conversions. For the relevant demographic components, trends should be interpreted with caution where the method of calculation has changed over time. This caveat applies particularly to the intraprovincial migration component, for which the assumptions of the geographic conversion method are more at risk of not being met. 7 Period from July 1 to June 30. 8 Age on July 1. 9 The estimates for immigrants are preliminary for 2020/2021 and final up to 2019/2020.

The GLA Demography Team offers a bespoke population projection service to London local authorities. Boroughs can request population projections based on their own choice of assumptions about future housing delivery. These assumptions are submitted to the team via a standard template. The resulting projections are referred to as the Borough Preferred Option (or BPO) and are commonly used to help support local planning and service delivery.

The GLA does not make the BPO projections and submitted housing trajectories publicly available or share them with anyone other than the commissioning borough. Boroughs wishing to publish BPO projections themselves are free to do so.

This service is offered as an optional, free of charge service to London authorities, and is intended to provide users with an alternative to the standard projections that the GLA publishes on the London Datastore.

Access to outputs

The BPO projections are shared with users via private pages on the London Datastore. These pages include all outputs produced under the service since 2019.

To access outputs, users must have a current Datastore account linked to their local government email address and contact the Demography Team to request permissions be granted for the individual pages relating to their local authority.

Notes on completing the development data template

What periods do the year labels in the template refer to?

The year labels in the template nominally refer to periods ending in the middle of that year (i.e. `2025` refers to the 12 month period ending June 30th 2025). However, development data is often readily available only for financial years and it is common to submit data on this basis, with financial year 2024/25 aligning with `2025` in the template.

Development trajectory

The cells in the template represent annual net changes in the number of dwellings.

The current template covers the period 2012-2041 and are pre-populated with estimated annual net dwelling changes for the period 2012-2019, based on modelling of data from the London Development Database.

For the 2022-based and subsequent projections, dwelling stock estimates are anchored to the results of the 2021 Census and it is not essential to include data for dwelling stock changes that occured prior to this point (i.e. up to and including '2021').

Past development data from 2022 up to the base year of the projections, affects the projected population in all future years as dwelling stock in the base year is used in the estimation of relationships between housing and population in the model.

We are not yet able to pre-populate templates with estimated dwelling changes for years after 2019. In future rounds of projections we intend to incorporate data from the Planning Data Hub.

Blank cells are treated as missing rather than no change, and data based on the 2017 Strategic Housing Land Availability Assessment (SHLAA) will be substituted in its place. To indicate no net change in dwellings in a ward in a particular year, users must explicitly enter a zero in the relevant cell.

Self-contained and Non-self-contained development

Self-contained development should be used for standard residential development (e.g. new build/conversion).

Non-self-contained development should be used for development such as student accommodation. This should be added to the template as the equivalent of self-contained units (i.e. a ratio of non-self-contained to self-contained should be applied). The London Plan ratios are:

· 2.5:1 for student housing

· 1:1 for housing for older people (C2)

· 1.8:1 for all other non-self-contained housing

Requesting projections based on multiple different housing scenarios

While we are willing to try and accommodate requests for multiple sets of projections, capacity in the team is limited and there is no guarantee that we will be able to do so in a timely manner.

Please do not

• Add rows or columns to the template
• Change ward names or codes
• Include formulas or new formatting
• Add notes or comments to the template
• Return data in a different version of the template to those included here

Please return completed templates to:

<a href="mailto:demography@london.gov.uk"

Over the past 24 years, there were constantly more men than women living on the planet. Of the 8.06 billion people living on the Earth in 2024, 4.09 billion were men and 4.05 billion were women. One-quarter of the world's total population in 2024 was below 15 years.

This dataset features three gridded population dadasets of Germany on a 10m grid. The units are people per grid cell.

Datasets

DE_POP_VOLADJ16: This dataset was produced by disaggregating national census counts to 10m grid cells based on a weighted dasymetric mapping approach. A building density, building height and building type dataset were used as underlying covariates, with an adjusted volume for multi-family residential buildings.

DE_POP_TDBP: This dataset is considered a best product, based on a dasymetric mapping approach that disaggregated municipal census counts to 10m grid cells using the same three underyling covariate layers.

DE_POP_BU: This dataset is based on a bottom-up gridded population estimate. A building density, building height and building type layer were used to compute a living floor area dataset in a 10m grid. Using federal statistics on the average living floor are per capita, this bottom-up estimate was created.

Please refer to the related publication for details.

Temporal extent

The building density layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: http://doi.org/10.1594/PANGAEA.920894)

The building height layer is representative for ca. 2015 (doi: 10.5281/zenodo.4066295)

The building types layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: 10.5281/zenodo.4601219)

The underlying census data is from 2018.

Data format

The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (.tif). There is a mosaic in GDAL Virtual format (.vrt), which can readily be opened in most Geographic Information Systems.

Further information

For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de). A web-visualization of this dataset is available here.

Publication

Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE. DOI: 10.1371/journal.pone.0249044

Acknowledgements

Census data were provided by the German Federal Statistical Offices.

Funding This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

Footnotes: 1 Population estimates based on the Standard Geographical Classification (SGC) 2016 as delineated in the 2016 Census.2 A census metropolitan area (CMA) or a census agglomeration (CA) is formed by one or more adjacent municipalities centred on a population centre (known as the core). A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core based on adjusted data from the previous Census of Population Program. A CA must have a core population of at least 10,000 also based on data from the previous Census of Population Program. To be included in the CMA or CA, other adjacent municipalities must have a high degree of integration with the core, as measured by commuting flows derived from data on place of work from the previous Census Program. If the population of the core of a CA falls below 10,000, the CA is retired from the next census. However, once an area becomes a CMA, it is retained as a CMA even if its total population declines below 100,000 or the population of its core falls below 50,000. All areas inside the CMA or CA that are not population centres are rural areas. When a CA has a core of at least 50,000, based on data from the previous Census of Population, it is subdivided into census tracts. Census tracts are maintained for the CA even if the population of the core subsequently falls below 50,000. All CMAs are subdivided into census tracts (2016 Census Dictionary, catalogue number 98-301-X2016001).3 An area outside census metropolitan areas and census agglomerations is made up of all areas (within a province or territory) unallocated to a census metropolitan area (CMA) or census agglomeration (CA).4 The population growth, which is used to calculate population estimates of census metropolitan areas and census agglomerations (table 17100135), is comprised of the components of population growth (table 17100136).5 This table replaces table 17100079.6 The components of population growth for census metropolitan areas (CMAs) and census agglomerations (CAs) sometimes had to be calculated using information at the census division level, using the geographic conversion method. This method involves using the population component calculated at the level of the CD(s) in which the CMA or CA is located and applying a ratio corresponding to the proportion of the CMA or CA population included in the corresponding CD(s). For periods prior to 2005/2006, all demographic components for all CMAs and CAs were calculated using geographic conversions. For the periods from 2005/2006 to 2010/2011 inclusively, emigration and internal migration components for areas that were not CMAs according to the 2011 SGC were calculated using geographic conversions. For the periods 2011/2012 to 2015/2016 inclusively, the emigration and internal migration components of regions that were not CMAs or CAs according to the 2011 SGC were calculated using geographic conversions. For the relevant demographic components, trends should be interpreted with caution where the method of calculation has changed over time. This caveat applies particularly to the intraprovincial migration component, for which the assumptions of the geographic conversion method are more at risk of not being met.7 Period from July 1 to June 30.8 Age on July 1.9 The estimates for immigrants are preliminary for 2020/2021 and final up to 2019/2020.

In 2021, children between the ages of zero and 17 years old made up 22.2 percent of the total population in the United States. This is down from a peak in 1960, where children made up 36 percent of the total population in the country.