Each year, the Forecasting and Trends Office (FTO) publishes population estimates and future year projections. The population estimates can be used for a variety of planning studies including statewide and regional transportation plan updates, subarea and corridor studies, and funding allocations for various planning agencies.The 2020 population estimates reported are based on the US Census Bureau 2020 Decennial Census. The 2021 population estimates are based on the population estimates developed by the Bureau of Economic and Business Research (BEBR) at the University of Florida. BEBR uses the decennial census count for April 1, 2020, as the starting point for state-level projections. More information is available from BEBR here.This dataset contains boundaries for all incorporated places (e.g., city, town, village) and each county’s unincorporated area in the State of Florida with 2020 census population and 2021 population estimates. All legal boundaries and names in this dataset are from the US Census Bureau’s TIGER/Line Files (2021).Note: The City of Weeki Wachee was disincorporated on June 9, 2020, and is now part of the unincorporated areas of Hernando County.Please see the Data Dictionary for more information on data fieldsData Sources:US Census Bureau 2020 Decennial CensusUS Census Bureau’s TIGER/Line Files (2021)Bureau of Economic and Business Research (BEBR) – Florida Estimates of Population 2021 Data Coverage: StatewideData Time Period: 2020 – 2021 Date of Publication: July 2022 Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

The National Population and Housing Census (NPHC) is part of an integrated national statistical system of Nepal. It provides the benchmark for population count at national and sub-national levels at regular intervals of ten years. The preliminary data contains: Total family number Total household number Total population

Each year, the Forecasting and Trends Office (FTO) publishes population estimates and future year projections. The population estimates can be used for a variety of planning studies including statewide and regional transportation plan updates, subarea and corridor studies, and funding allocations for various planning agencies.The 2021 population estimates are based on the population estimates developed by the Bureau of Economic and Business Research (BEBR) at the University of Florida. BEBR uses the decennial census count for April 1, 2020, as the starting point for state-level projections. More information is available from BEBR here.This dataset contains county boundaries in the State of Florida with 2021 population density estimates. All legal boundaries and names in this dataset are from the US Census Bureau’s TIGER/Line Files (2021). Please see the Data Dictionary for more information on data fields. Data Sources:FDOT FTO 2020 and 2021 Population Estimates by CountyUS Census Bureau 2020 Decennial CensusUS Census Bureau’s TIGER/Line Files (2021)Bureau of Economic and Business Research (BEBR) – Florida Estimates of Population 2021 Data Coverage: StatewideData Time Period: 2021 Date of Publication: October 2022 Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

Annual population estimates as of July 1st, by economic region, single year of age, five-year age group and gender, based on the Standard Geographical Classification (SGC) 2021.

Description: Census 2021 - Population (total Belgium) according to: Gender, Age (H) and Family Position (H)

The level of detail of the variables is expressed via the letters in parentheses, (L) for low = low, (M) medium = medium and (H) high = high.

Period: 2021

Metadata: Variables, European Implementing Regulation (EU) No 2017/543, Regulation (EC) No 763/2008

More information, data and publications can be found on Census 2021

This dataset contains gridded human population with a spatial resolution of 1 km x 1 km for the UK based on Census 2021 (Census 2022 for Scotland) and Land Cover Map 2021 input data. Data on population distribution for the United Kingdom is available from statistical offices in England, Wales, Northern Ireland and Scotland and provided to the public e.g. via the Office for National Statistics (ONS). Population data is typically provided in tabular form or, based on a range of different geographical units, in file types for geographical information systems (GIS), for instance as ESRI Shapefiles. The geographical units reflect administrative boundaries at different levels of detail, from Devolved Administration to Output Areas (OA), wards or intermediate geographies. While the presentation of data on the level of these geographical units is useful for statistical purposes, accounting for spatial variability for instance of environmental determinants of public health requires a more spatially homogeneous population distribution. For this purpose, the dataset presented here combines 2021/2022 UK Census population data on Output Area level with Land Cover Map 2021 land-use classes 'urban' and 'suburban' to create a consistent and comprehensive gridded population data product at 1 km x 1 km spatial resolution. The mapping product is based on British National Grid (OSGB36 datum). Full details about this dataset can be found at https://doi.org/10.5285/7beefde9-c520-4ddf-897a-0167e8918595

Note: The estimates are developed from a base that incorporates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates. For population estimates methodology statements, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html See Geographic Terms and Definitions at http://www.census.gov/programs-surveys/popest/guidance-geographies/terms-and-definitions.html for a list of the states that are included in each region. The estimates feature geographic boundaries from the Vintage 2020 estimates series; the geographic boundaries for these 2021 population estimates are as of January 1, 2020.Suggested Citation:Annual Estimates of the Resident Population for the United States, Regions, States, District of Columbia, and Puerto Rico: April 1, 2020 to July 1, 2021 (NST-EST2021-POP)Source: U.S Census Bureau, Population DivisionRelease Date: December 2021

Description: Census 2021 - Population according to: Place of residence (Commune), Sex and Age (M)

The level of detail of the variables is expressed via the letters in parentheses, (L) for low = low, (M) medium = medium and (H) high = high.

Period: 2021

Metadata: Variables, European Implementing Regulation (EU) No 2017/543, Regulation (EC) No 763/2008

More information, data and publications can be found on Census 2021

The Population and Dwellings data from the 2021 Federal Census covers population in private households by age and gender. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Population in private households refers to all persons or group of persons who occupy the same dwelling and do not have a usual place of residence elsewhere in Canada or abroad. For census purposes, households are classified into three groups: private households, collective households, and households outside Canada. Unless otherwise specified, all data in census products are for private households only. Population in private households includes Canadian citizens and landed immigrants whose usual place of residence is Canada. Also includes refugee claimants, holders of work and study permits, Canadian citizens and landed immigrants at sea or in port aboard merchant or government vessels, and Canadian citizens away from Canada on military or diplomatic business. Excludes government representatives and military members of other countries and residents of other countries visiting Canada.

Age refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well‑defined reference date).

Gender refers to an individual's personal and social identity as a man, woman, or non‑binary person (a person who is not exclusively a man or a woman). A person's gender may differ from their sex at birth, and from what is indicated on their current identification or legal documents such as their birth certificate, passport, or driver's licence. A person's gender may change over time. Statistics Canada collected data about transgender and non-binary populations for the first time on the 2021 Census. The category "Men+" includes men (and/or boys), as well as some non-binary persons. The category "Women+" also includes women (and/or girls), as well as some non-binary persons.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

This is 10% of the 2021 Ghana Population and Housing Census dataset made available to the public, including researchers.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME
Population estimates

LAST UPDATED
February 2023

DESCRIPTION
Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCE
California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
Table E-6: County Population Estimates (1960-1970)
Table E-4: Population Estimates for Counties and State (1970-2021)
Table E-8: Historical Population and Housing Estimates (1990-2010)
Table E-5: Population and Housing Estimates (2010-2021)

Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs
Computed using 2020 US Census TIGER boundaries

U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University
1970-2020

U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/
2011-2021
Form B01003

Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).

The following is a list of cities and towns by geographical area:

Big Three: San Jose, San Francisco, Oakland

Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside

Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville

Unincorporated: all unincorporated towns

About this dataset

Context

The dataset tabulates the New Haven County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of New Haven County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2021, the population of New Haven County was 863,700, a 0.02% increase year-by-year from 2020. Previously, in 2020, New Haven County population was 863,498, an increase of 1.13% compared to a population of 853,818 in 2019. Over the last 20 plus years, between 2000 and 2021, population of New Haven County increased by 38,859. In this period, the peak population was 864,732 in the year 2012. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

https://i.neilsberg.com/ch/population-of-new-haven-county-ct-population-by-year-2000-2021.jpeg" alt="New Haven County population by year">

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2021

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2021)
• Population: The population for the specific year for the New Haven County is shown in this column.
• Year on Year Change: This column displays the change in New Haven County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Haven County Population by Year. You can refer the same here

Description: Census 2021 - Population according to: Place of residence (Province), Gender, Age (M), Civil status (L) and Educational attainment

The level of detail of the variables is expressed via the letters in parentheses, (L) for low = low, (M) medium = medium and (H) high = high.

Period: 2021

Metadata: Variables, European Implementing Regulation (EU) No 2017/543, Regulation (EC) No 763/2008

More information, data and publications can be found on Census 2021

Mid-year (30 June) estimates of the usual resident population for Lower layer Super Output Areas (LSOAs) in England and Wales by broad age groups and sex.

This map symbolizes the relative population counts for the City's 12 Data Divisions, aggregating the tract-level estimates from the the Census Bureau's American Community Survey 2021 five-year samples. Please refer to the map's legend for context to the color shading -- darker hues indicate more population.If you click on each Data Division, you can view other Census demographic information about that Data Division in addition to the population count.About the Census Data:The data comes from the U.S. Census Bureau's American Community Survey's 2017-2021 five-year samples. The American Community Survey (ACS) is an ongoing survey conducted by the federal government that provides vital information annually about America and its population. Information from the survey generates data that help determine how more than $675 billion in federal and state funds are distributed each year.For more information about the Census Bureau's ACS data and process of constructing the survey, visit the ACS's About page.About the City's Data Divisions:As a planning analytic tool, an interdepartmental working group divided Rochester into 12 “data divisions.” These divisions are well-defined and static so they are positioned to be used by the City of Rochester for statistical and planning purposes. Census data is tied to these divisions and serves as the basis for analyses over time. As such, the data divisions are designed to follow census boundaries, while also recognizing natural and human-made boundaries, such as the River, rail lines, and highways. Historical neighborhood boundaries, while informative in the division process, did not drive the boundaries. Data divisions are distinct from the numerous neighborhoods in Rochester. Neighborhood boundaries, like quadrant boundaries, police precincts, and legislative districts often change, which makes statistical analysis challenging when looking at data over time. The data division boundaries, however, are intended to remain unchanged. It is hoped that over time, all City data analysts will adopt the data divisions for the purpose of measuring change over time throughout the city.

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

Dataset SummaryAbout this data:This feature layer symbolizes the relative population counts for the City's 12 Data Divisions, aggregating the tract-level estimates from the the Census Bureau's American Community Survey 2021 five-year samples.If you click on each Data Division, you can view other Census demographic information about that Data Division in addition to the population count.About the Census Data:The data comes from the U.S. Census Bureau's American Community Survey's 2017-2021 five-year samples. The American Community Survey (ACS) is an ongoing survey conducted by the federal government that provides vital information annually about America and its population. Information from the survey generates data that help determine how more than $675 billion in federal and state funds are distributed each year.For more information about the Census Bureau's ACS data and process of constructing the survey, visit the ACS's About page.About the City's Data Divisions:As a planning analytic tool, an interdepartmental working group divided Rochester into 12 “data divisions.” These divisions are well-defined and static so they are positioned to be used by the City of Rochester for statistical and planning purposes. Census data is tied to these divisions and serves as the basis for analyses over time. As such, the data divisions are designed to follow census boundaries, while also recognizing natural and human-made boundaries, such as the River, rail lines, and highways. Historical neighborhood boundaries, while informative in the division process, did not drive the boundaries. Data divisions are distinct from the numerous neighborhoods in Rochester. Neighborhood boundaries, like quadrant boundaries, police precincts, and legislative districts often change, which makes statistical analysis challenging when looking at data over time. The data division boundaries, however, are intended to remain unchanged. It is hoped that over time, all City data analysts will adopt the data divisions for the purpose of measuring change over time throughout the city.Dictionary: Division: The name of the data division. Total_Popu: The total population of the division. The population is calculated from the Census Bureau’s American Community Survey 2021 five-year samples. Percentage: Represents the percentage of City of Rochester residents which live in the division. Area_in_Sq: The total area in square miles of a given division. Source:City of Rochester Office of Innovation

In 2021, about 13.43 million households were counted in the federal state of California, the most out of any state. Texas, Florida, New York, and Pennsylvania rounded out the top five states with the most number of households in that year.

Census 2021 rounded population and household estimates for local authorities in Wales, by sex and five-year age group.

Latest update on the 2021 Census and data outputs Provides information about the 2021 Census. Lists output topics and provides links to data.