This data set represents 1990 population density by block group as a 100-m grid using data from the 1990 Census of Population and Housing (Public Law 94-171 redistricting data). Grid cell values represent population density in people per square kilometer multiplied by 10 so that the data could be stored as integer.

Monthly Intercensal Estimates of the Civilian Population by Single Year of Age and Sex: April 1, 1990 to April 1, 2000 // Source: U.S. Census Bureau, Population Division // For detailed information about the methods used to create the intercensal population estimates, see https://www.census.gov/popest/methodology/intercensal_nat_meth.pdf. // The Census Bureau's Population Estimates Program produces intercensal estimates each decade by adjusting the existing time series of postcensal estimates for a decade to smooth the transition from one decennial census count to the next. They differ from the postcensal estimates that are released annually because they rely on a formula that redistributes the difference between the April 1 postcensal estimate and April 1 census count for the end of the decade across the estimates for that decade. Meanwhile, the postcensal estimates incorporate current data on births, deaths, and migration to produce each new vintage of estimates, and to revise estimates for years back to the last census. The Population Estimates Program provides additional information including historical and postcensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/popest/index.html.

The MARS file contains modified race and age data based on the 1990 Census. Both race and age are tabulated by sex and Hispanic origin for several layers of geography. The race data were modified to make reporting categories comparable to those used by state and local agencies. The 1990 Census included 9,804,847 persons who checked the "other race" category and were therefore not included in one of the 15 racial categories listed on the Census form. "Other race" is usually not an acceptable reporting category for state and local agencies. Therefore, the Census Bureau assigned each "other race" person to the specified race reported by another person geographically close with an identical response to the Hispanic-origin question. Hispanic origin was taken into account because over 95 percent of the "other race" persons were of Hispanic origin. (Hispanic-origin persons may be of any race.) The assignment of race to Hispanic-origin persons did not affect the Hispanic-origin category that they checked (i.e, Mexican, Puerto Rican, Cuban, etc.). Age data were modified because respondents tended to report age as of the date they completed the 1990 questionnaire, instead of age as of the April 1, 1990 Census date. In addition, there may have been a tendency for respondents to round up their age if they were close to having a birthday. Age data for individuals in households were modified by adjusting the reported birth-year data by race and sex for each of the 1990 Census's 449 district offices to correspond with the national level quarterly distribution of births available from the National Center for Health Statistics. The data for persons in group quarters were adjusted similarly, but on a state basis. The age adjustment affects approximately 100 million people. In this file their adjusted age is one year different from that reported in the 1990 Census.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: Not identified - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes (collective households)

UNIT DESCRIPTIONS: - Dwellings: Not applicable - Households: Households can be classified into two types: domestic and institutional. Individuals who live in the same place mostly due to family relationships are counted as a domestic household. Singles who live alone are counted as a domestic household. Individuals who live in the same domestic household should be registered as one household only, regardless of the type of working places and the type of household registrations (agricultural or non-agricultural), and whether they have the formal household registrations. - Group quarters: Unknown

Universe

All individuals who have Chinese nationality and reside in China

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Bureau of Statistics

SAMPLE DESIGN: Stratified cluster design

SAMPLE UNIT: Households

SAMPLE FRACTION: 1%

SAMPLE SIZE (person records): 11,835,947

Mode of data collection

Face-to-face [f2f]

Research instrument

A single questionnaire for regular and collective households.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes (institutional)

UNIT DESCRIPTIONS: - Dwellings: Not available - Households: An individual or group of people living who inhabit part or all of the physical or census building who make common provisions for food and other living essentials. - Group quarters: Institutional households consist of individuals in a residence that manages everyday needs, usually arranged by an organization such as a non-profit institution, school, the military, etc. Includes reformatories, prisons and similar living quarters. Also includes households that rent rooms or parts of buildings lodging ten or more people.

Universe

All population residing in the geographic area of Indonesia regardless of residence status. Homeless, boat people, etc were enumerated.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Statistics Indonesia

SAMPLE DESIGN: Data are derived from the sample of census blocks that received the long form questionnaire, stratified by urban-rural status.

SAMPLE UNIT: Census block

SAMPLE FRACTION: 0.51%

SAMPLE SIZE (person records): 912,544

Mode of data collection

Face-to-face [f2f]

Research instrument

Long form questionnaire SP90-S containing houseing and individual questions distributed to 5% of households.

This dataset is published by the Research & Analytics Group at the Atlanta Regional Commission to show population change by utilizing the 2020 redistricting data and comparable data for 2010, 2000, and 1990 across multiple geographies for the State of Georgia. For a deep dive into the data model including every specific metric, see the Data Manifest. The manifest details ARC-defined naming conventions, names/descriptions and topics where applicable, summary levels; source tables; notes and so forth for all metrics.

It should be noted:The 2020 redistricting release is not as detailed in terms of data compared to ACS estimates; data include total population, population by race and ethnicity, and "voting age" population (i.e., adults) by race and ethnicity, adults are subtracted from the total population to show children (ages 0-17); total number of housing units, occupied housing units, and vacant housing units. Percent and change measures are calculated over four different Censuses.These data are expressed in terms of 2020 geographies such as the new 2020 Census tracts. This means that that historical data for geographies like cities have been estimated to the 2020 boundaries. For example, the city of Atlanta, which has made multiple annexations since 1990, has a higher estimated 1990 population of 400,452 (2020 boundaries) than the 394,017 reported in the 1990 Census (1990 boundaries).Due to changes in block geographies and annexations, 2010 population totals for custom geographies such as City of Atlanta NSAs may differ slightly from the numbers we have published in the past.The procedure to re-estimate historical data to 2020 blocks often results in fractional population (e.g., 1.25 instead of 1 or 2). Counts have been rounded to the nearest whole, but to be more precise, all aggregation, percent, and change measures were performed pre-rounding. Some change measures may appear curious as a result. For example, 100.4 - 20.8 = 79.6 which rounds to 80. But if rounded first, 100.4 rounds down to 100, 20.8 rounds up to 21; 100 - 21 = 79.Asian and Pacific Islander categories are combined to maximize compatibility with the 1990 release, which reported the two groups as a single category. Caution should be exercised with 1990 race data because the Census Bureau changed to the current system (which allows people to identify as biracial or multiracial) starting only in 2000.The "other" race category includes American Indian and Alaska Natives, people identifying with "some other race" and (for 2000 forward), people who identify as biracial or multiracial.For more information regarding Decennial Census source data, visit 2020 Census website

This excel contains results from the 2017 State of Narragansett Bay and Its Watershed Technical Report (nbep.org), Chapter 4: "Population." The methods for analyzing population were developed by the US Environmental Protection Agency ORD Atlantic Coastal Environmental Sciences Division in collaboration with the Narragansett Bay Estuary Program and other partners. Population rasters were generated using the USGS dasymetric mapping tool (see http://geography.wr.usgs.gov/science/dasymetric/index.htm) which uses land use data to distribute population data more accurately than simply within a census mapping unit. The 1990, 2000, and 2010 10m cell population density rasters were produced using Rhode Island state land use data, Massachusetts state land use, Connecticut NLCD land use data, and U.S. Census data. To generate a population estimate (number of persons) for any given area within the boundaries of this raster, NBEP used the the Zonal Statistics as Table tool to sum the 10m cell density values within a given zone dataset (e.g., watershed polygon layer). Results presented include population estimates (1990, 2000, 2010) as well as calculation of acres of developed lands per 100 persons and percent change in estimated population (1990-2000; 2000-2010; 1990-2010).

This data collection provides detailed tabulations of 100-percent data items from the 1990 Census of Population and Housing. These tabulations are presented for states, counties, places with 1,000 or more persons, county subdivisions with 1,000 or more persons (selected states), county subdivisions with fewer than 1,000 persons in Metropolitan Statistical Areas/Consolidated MSAs (MSAs/CMSAs) (selected states), and state and county portions of Native American and Alaskan Native areas. Population items include age, race, sex, marital status, Hispanic origin, household type, and household relationship. Housing items include occupancy/vacancy status, tenure, units in structure, contract rent, meals included in rent, value, and number of rooms in housing unit. Crosstabulations include variables such as single year of age by sex, tenure by age of householder, age by group quarters, aggregate value by units in structure, and tenure by number of nonrelatives. The dataset contains both "A" and "B" records. "A" records are provided for each summary level in a geographic area, and are repeated for each geographic component. "B" records repeat the same data for each summary level/geographic component combination, but are tabulated for each of 34 categories of race and Hispanic origin.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Households and Group Quarters

UNITS IDENTIFIED: - Dwellings: No - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Dwelling places with fewer than ten persons unrelated to a household head, excluding institutions and transient quarters. - Group quarters: Institutions, transient quarters, and dwelling places with ten or more persons unrelated to a household head.

Universe

Residents of the 50 states (not the outlying areas).

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: U.S. Census Bureau

SAMPLE UNIT: Household

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 12,501,046

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1990 census used a single long-form questionnaire completed by one-half of persons in places with a population under 2,500, one-sixth of persons in other tracts and block numbering areas with fewer than 2,000 housing units, and one-eighth of all other areas. Overall, about one-sixth of housing units completed a long form.

Response rate

UNDERCOUNT: No official estimates

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: Place where people reside. - Households: That collectivity composed of one or several people, whether bound by kinship or not, living in the same house or in a portion of the same house, sharing in the provision of service or in the management of the household, who do not separate their income and expenses among themselves. People lacking a kinship bond among themselves, but who live together on a continuous basis for various reasons and make no distinction among themselves in terms of their expenses and earnings, are considered to be households. - Group quarters: Military barracks, jails, hospitals, clinics, boarding schools, prisons, transit stations, factories, embassies.

Universe

The total population within the boundaries of the country on the day of enumeration at localities where they were physically present on the census day.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: State Institute of Statistics of Turkey

SAMPLE DESIGN: Systematic random sampling by province

SAMPLE UNIT: Households, otherwise individuals if enumerated in non-household places on census day.

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 2,817,455

Mode of data collection

Face-to-face [f2f]

Research instrument

Single form with 4 sections: address information, dwelling type information, household questions, and personal characteristics.

SSTF 1 contains sample data weighted to represent the total population. In addition, the file contains 100-percent counts and unweighted sample counts for total persons and total housing units in the 1990 Census. Population variables include citizenship, ability to speak English, age, number of children ever born, class of worker, disability status, earnings in 1989, educational attainment, employment status, household size, industry, labor force status, language spoken at home, occupation, poverty status in 1989, school enrollment, and year of entry into the United States. Housing variables include gross rent, housing units, kitchen facilities, mortgage status, plumbing facilities, tenure, units in structure, and year householder moved into unit. The data are also crosstabulated and presented in a variety of tables. Crosstabulations include citizenship and year of entry by all other variables, age (groups) by sex by school enrollment or college enrollment or educational attainment and employment status, age by poverty status by sex, relationship by family type by subfamily type, and employment status by hours worked last week and year last worked. The dataset includes both "A" and "B" records. "A" records have three population (PA) and three housing (HA) tables. The "B" records present more detail in 66 population (PB) and 10 housing (HB) tables, and are divided into 22 segments of 8,142 characters each.

Throughout the Cold War, the United States and the Soviet Union had relatively similar total populations. The U.S.' population grew from around 205 million to almost 250 million people between 1970 and 1990, while the USSR's population grew from around 240 to 290 million in this time. In these years, the Soviet Union had the third largest population in the world, and the U.S. had the fourth largest (behind China and India respectively). Despite their similar sizes, these populations differed in terms of distribution as the U.S.' population was approximately three quarters urban in this period, whereas the Soviet Union's urban population was just 56 percent in 1970 and 66 percent in 1989. Additionally, the Soviet Union's population was much younger than that of the U.S. due to a higher birth rate and lower life expectancy.

This dataset consists of three raster datasets representing population density for the years 1990, 2000, and 2010. All three rasters are based on block-level census geography data. The 1990 and 2000 data are derived from data normalized to 2000 block boundaries, while the 2010 data are based on 2010 block boundaries. The 1990 and 2000 data are rasters at 100-meter (m) resolution, while the 2010 data are at 60-m resolution. See details about each dataset in the specific metadata for each raster.

Monthly Intercensal Estimates of the Resident plus Armed Forces Overseas Population by Single Year of Age and Sex: April 1, 1990 to April 1, 2000 // Source: U.S. Census Bureau, Population Division // For detailed information about the methods used to create the intercensal population estimates, see https://www.census.gov/popest/methodology/intercensal_nat_meth.pdf. // The Census Bureau's Population Estimates Program produces intercensal estimates each decade by adjusting the existing time series of postcensal estimates for a decade to smooth the transition from one decennial census count to the next. They differ from the postcensal estimates that are released annually because they rely on a formula that redistributes the difference between the April 1 postcensal estimate and April 1 census count for the end of the decade across the estimates for that decade. Meanwhile, the postcensal estimates incorporate current data on births, deaths, and migration to produce each new vintage of estimates, and to revise estimates for years back to the last census. The Population Estimates Program provides additional information including historical and postcensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/popest/index.html.

This collection identifies changes in United States census tracts between 1980 and 1990. The data were derived from the Census Bureaus's TIGER database. Counties with 1980 and 1990 census tracts are not included if there were no changes in the census tract boundaries and/or census tract numbers between 1980 and 1990. Also excluded are counties with census tracts defined for the first time in 1990.

This dataset is published by the Research & Analytics Group at the Atlanta Regional Commission to show population change by utilizing the 2020 redistricting data and comparable data for 2010, 2000, and 1990 across multiple geographies for the State of Georgia. For a deep dive into the data model including every specific metric, see the Data Manifest. The manifest details ARC-defined naming conventions, names/descriptions and topics where applicable, summary levels; source tables; notes and so forth for all metrics.

It should be noted:The 2020 redistricting release is not as detailed in terms of data compared to ACS estimates; data include total population, population by race and ethnicity, and "voting age" population (i.e., adults) by race and ethnicity, adults are subtracted from the total population to show children (ages 0-17); total number of housing units, occupied housing units, and vacant housing units. Percent and change measures are calculated over four different Censuses.These data are expressed in terms of 2020 geographies such as the new 2020 Census tracts. This means that that historical data for geographies like cities have been estimated to the 2020 boundaries. For example, the city of Atlanta, which has made multiple annexations since 1990, has a higher estimated 1990 population of 400,452 (2020 boundaries) than the 394,017 reported in the 1990 Census (1990 boundaries).Due to changes in block geographies and annexations, 2010 population totals for custom geographies such as City of Atlanta NSAs may differ slightly from the numbers we have published in the past.The procedure to re-estimate historical data to 2020 blocks often results in fractional population (e.g., 1.25 instead of 1 or 2). Counts have been rounded to the nearest whole, but to be more precise, all aggregation, percent, and change measures were performed pre-rounding. Some change measures may appear curious as a result. For example, 100.4 - 20.8 = 79.6 which rounds to 80. But if rounded first, 100.4 rounds down to 100, 20.8 rounds up to 21; 100 - 21 = 79.Asian and Pacific Islander categories are combined to maximize compatibility with the 1990 release, which reported the two groups as a single category. Caution should be exercised with 1990 race data because the Census Bureau changed to the current system (which allows people to identify as biracial or multiracial) starting only in 2000.The "other" race category includes American Indian and Alaska Natives, people identifying with "some other race" and (for 2000 forward), people who identify as biracial or multiracial.For more information regarding Decennial Census source data, visit 2020 Census website

1990 Population Census Data for Baltimore, Maryland. Refer to the 1990.pdf enclosures for more information. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

In 2024, the total population of Taiwan increased to approximately 23.4 million people. The significant drop in 2021 and 2022 was mainly due to people leaving the island during the coronavirus pandemic, while the natural growth rate was also slightly negative. The return of many people in 2023 led to a growth in population. According to national statistics and projections, population numbers entered a general declining path in 2020. Taiwan's demographic development Taiwan experienced rapid population growth in the 1950s and 60s, but alongside with economic development, growth rates decreased significantly. Falling birth figures have also been attributed to Taiwan’s family planning policy, which was aimed at keeping population growth at check. This led to a situation on the island where overall population density was very high and still growing, while the total fertility rate dropped quickly and eventually reached extremely low levels compared internationally. In the 21st century, the challenges of a quickly aging society became more and more apparent and the government initiated family friendly and birth promoting policies. However, fertility still kept on decreasing and reached a historical low in 2010 at 0.9 births per woman on average, and only in recent years has the number of births increased slightly. Implications of an aging society Today's Taiwan, like many East Asian societies, faces the challenges of a rapidly aging population. While the share of the population aged 65 and older accounted to around 18 percent in 2023, it is projected to reach 43 percent in 2060. The old-age dependency ratio, which denotes the relation of people of 65 years and above to the working-age population, is expected to reach around 87 percent in those years. This puts heavy pressure on the working people and the economy as a whole. However, compared to mainland China, which is in a very much comparable demographic situation, Taiwan enjoys the advantage of a relatively wealthy society, which helps to curb the negative economic effects of an aging population.

This data set represents U.S. Geological Survey (USGS) historical Land Use and Land Cover (LULC) from the 1970's that has been refined with 1990 population density at the block group level to indicate new residential development representative of the 1990's. Any area having a population density of at least 1,000 people per square mile had been re-classified as "urban" land in this data set.

From 1990 to 2024, the population of the city of Rio de Janeiro grew almost every year, from approximately 5.5 million to 6.7 million residents, which is an increase of 22 percent. The data shows several fluctuations; however, these may be attributed to changes in methodology. It is unclear whether the changes shown in the 2022 census are due to counting methodologies, or if it is representative of the impact of the COVID-19 pandemic. Growth of the population The city of Rio de Janeiro has consistently had a higher birth rate than the death rate, although the gap between these two indicators is narrowing. In 2023, 9.3 births were registered per 1,000 inhabitants of Rio, while in the same period a rate of 8.4 deaths per 1,000 inhabitants was reported. The surrounding of the city Considering the entire metropolitan area of Rio de Janeiro, the region is home to approximately 13 million people. Rio's population is aging, with about eight million people over the age of 30 and half this value between the ages of 30 and 49. In the most recent census, whites made up nearly 44 percent of the population, followed by Pardo Brazilians, who composed about 37 percent of all residents.