In 2023, the metropolitan area of New York-Newark-Jersey City had the biggest population in the United States. Based on annual estimates from the census, the metropolitan area had around 19.5 million inhabitants, which was a slight decrease from the previous year. The Los Angeles and Chicago metro areas rounded out the top three. What is a metropolitan statistical area? In general, a metropolitan statistical area (MSA) is a core urbanized area with a population of at least 50,000 inhabitants – the smallest MSA is Carson City, with an estimated population of nearly 56,000. The urban area is made bigger by adjacent communities that are socially and economically linked to the center. MSAs are particularly helpful in tracking demographic change over time in large communities and allow officials to see where the largest pockets of inhabitants are in the country. How many MSAs are in the United States? There were 421 metropolitan statistical areas across the U.S. as of July 2021. The largest city in each MSA is designated the principal city and will be the first name in the title. An additional two cities can be added to the title, and these will be listed in population order based on the most recent census. So, in the example of New York-Newark-Jersey City, New York has the highest population, while Jersey City has the lowest. The U.S. Census Bureau conducts an official population count every ten years, and the new count is expected to be announced by the end of 2030.

This data set describes metropolitan areas in the conterminous United States, developed from U.S. Bureau of the Census boundaries of Consolidated Metropolitan Statistical Areas (CMSA) and Metropolitan Statistical Areas (MSA), that have been processed to extract the largest contiguous urban area within each MSA or CMSA.

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

This statistic provides projected figures for the Gross Metropolitan Product (GMP) of the United States in 2021, by metropolitan area. Only the 100 leading metropolitan areas are shown here. In 2022, the GMP of the New York-Newark-Jersey City metro area is projected to be around of about **** trillion U.S. dollars. Los Angeles metropolitan areaA metropolitan area in the U.S. is characterized by a relatively high population density and close economic ties through the area, albeit, without the legal incorporation that is found within cities. The Gross Metropolitan Product is measured by the Bureau of Economic Analysis under the U.S. Department of Commerce and includes only metropolitan areas. The GMP of the Los Angeles-Long Beach-Anaheim metropolitan area located in California is projected to be among the highest in the United States in 2021, amounting to *** trillion U.S. dollars. The Houston-The Woodlands-Sugar Land, Texas metro area is estimated to be approximately *** billion U.S. dollars in the same year. The Los Angeles metro area had one of the largest populations in the country, totaling ****** million people in 2021. The Greater Los Angeles region has one of the largest economies in the world and is the U.S. headquarters of many international car manufacturers including Honda, Mazda, and Hyundai. Its entertainment industry has generated plenty of tourism and includes world famous beaches, shopping, motion picture studios, and amusement parks. The Hollywood district is known as the “movie capital of the U.S.” and has its historical roots in the country’s film industry. Its port, the Port of Los Angeles and the Port of Long Beach are aggregately one of the world’s busiest ports. The Port of Los Angelesgenerated some ****** million U.S. dollars in revenue in 2019.

United States US: Population in Largest City: as % of Urban Population data was reported at 7.020 % in 2017. This records a decrease from the previous number of 7.065 % for 2016. United States US: Population in Largest City: as % of Urban Population data is updated yearly, averaging 8.675 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 11.200 % in 1960 and a record low of 7.020 % in 2017. United States US: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

This data collection provides statistics gathered from a variety of federal agencies and national associations. Demographic, economic, and governmental data from both the federal government and private agencies are presented to enable multiarea comparisons as well as single-area profiles. Current estimates and benchmark census results are included. Data are available for five types of geographic coverage: (1) Metro Areas data cover 249 metropolitan statistical areas (MSAs), 17 consolidated metropolitan statistical areas (CMSAs), 54 primary metropolitan statistical areas (PSMAs), and 16 New England county metropolitan areas (NECMAs). Metro Areas data include the following general subjects: area and population, households, vital statistics, health, education, crime, housing, money income, personal income, civilian labor force, employment, construction, commercial office space, manufacturing, wholesale and retail trade, service industries, banking, federal funds and grants, and government employment. There are 14 parts for Metro Areas. (2) State Metro/Nonmetro data cover the United States, the 50 states, the District of Columbia, and the metropolitan and nonmetropolitan portions of these areas. State Metro/Nonmetro data include most of the subjects listed for Metro Areas. There are six parts for State Metro/Nonmetro. (3) Metro Counties data cover 336 metropolitan areas and their component counties and include topics identical to those presented in the State Metro/Nonmetro data. Six parts are supplied for Metro Counties. (4) Metro Central Cities data cover 336 metropolitan areas and their 522 central cities and 336 outside central cities portions. Metro Central Cities variables are limited to 13 items, which include area and population, money income, civilian labor force, and retail trade. There is one part for Metro Central Cities. (5) States data cover the United States, the 50 states, the District of Columbia, and census regions and divisions. States data include the same items as the Metro Areas data, plus information on social welfare programs, geography and environment, domestic travel and parks, gross state product, poverty, wealth holders, business, research and development, agriculture, forestry and fisheries, minerals and mining, transportation, communications, energy, state government, federal government, and elections. There are 101 parts for States.

Among the 81 largest metropolitan areas (by population) in the United States, Knoxville, Tennessee was ranked first with **** percent of residents reporting as white, non-Hispanic in 2023.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Metropolitan Divisions subdivide a Metropolitan Statistical Area containing a single core urban area that has a population of at least 2.5 million to form smaller groupings of counties or equivalent entities. Not all Metropolitan Statistical Areas with urban areas of this size will contain Metropolitan Divisions. Metropolitan Division are defined by the Office of Management and Budget (OMB) and consist of one or more main counties or equivalent entities that represent an employment center or centers, plus adjacent counties associated with the main county or counties through commuting ties. Because Metropolitan Divisions represent subdivisions of larger Metropolitan Statistical Areas, it is not appropriate to rank or compare Metropolitan Divisions with Metropolitan and Micropolitan Statistical Areas. The Metropolitan Divisions boundaries are those defined by OMB based on the 2010 Census, published in 2013, and updated in 2017.

This statistics shows a list of the top 20 largest-metropolitan areas in the United States in 2010, by land area. Riverside-San Bernardino-Ontario in California was ranked first enclosing an area of 70,612 square kilometers.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

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 SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. 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 August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

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 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

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

This multi-scale map shows counts of the total population the US. Data is from U.S. Census Bureau's 2020 PL 94-171 data for county, tract, block group, and block.County and metro area highlights:The largest county in the United States in 2020 remains Los Angeles County with over 10 million people.The largest city (incorporated place) in the United States in 2020 remains New York with 8.8 million people.312 of the 384 U.S. metro areas gained population between 2010 and 2020.The fastest-growing U.S. metro area between the 2010 Census and 2020 Census was The Villages, FL, which grew 39% from about 93,000 people to about 130,000 people.72 U.S. metro areas lost population from the 2010 Census to the 2020 Census. The U.S. metro areas with the largest percentage declines were Pine Bluff, AR, and Danville, IL, at -12.5 percent and -9.1 percent, respectively.View more 2020 Census statistics highlights on local populations changes.

This statistics shows the top 20 fastest growing large-metropolitan areas in the United States between July 1st, 2022 and July 1st, 2023. The total population in the Wilmington, North Carolina, metropolitan area increased by 0.05 percent from 2022 to 2023.

Metropolitan Divisions A Metropolitan Division may exist as a division of an MSA Metropolitan and Micropolitan Statistical Areas and Related Statistical Areas Metropolitan and micropolitan statistical areas (referred to generically as 'core based statistical areas 'or CBSAs) are statistical geographic areas defined by the federal Office of Management and Budget (OMB), following a set of official standards published in the Federal Register. To meet the needs of various users for standard units at various geographic scales, OMB's standards provide for a flexible framework of area definitions that includes, in addition to metropolitan and micropolitan statistical areas, metropolitan divisions, combined statistical areas, New England city and town areas (NECTAs), NECTA divisions, and combined NECTAs. Documentation of the metropolitan and micropolitan statistical area standards and how they are applied is available on the Census Bureau's website or from the Population Distribution Branch, Population Division, U.S. Census Bureau, Washington, DC 20233-8800, telephone (301) 763-2419. Each metropolitan or micropolitan statistical area consists of a core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core. Metropolitan statistical areas contain at least one U.S. Census Bureau-defined urbanized area of 50,000 or more population; micropolitan statistical areas contain at least one Census Bureau-defined urban cluster of at least 10,000 and less than 50,000 population. If specified criteria are met, a metropolitan statistical area containing a single urbanized area with a population of 2.5 million or more may be subdivided into metropolitan divisions, which function as distinct social and economic areas within the larger metropolitan statistical area. The territory, population, and housing units in metropolitan statistical areas are referred to as 'metropolitan. 'The metropolitan category is subdivided into 'inside principal city 'and 'outside principal city. 'The territory, population, and housing units located outside territory designated 'metropolitan 'are referred to as 'nonmetropolitan; 'the latter designation also include micropolitan statistical areas. These categories do not equate to an urban/rural classification; indeed, all metropolitan and micropolitan statistical areas and territory located outside CBSAs contain a mixture of urban and rural territory, population, and housing units. While it is the case that the populations of metropolitan statistical areas tend to be predominantly urban, according to Census 2000 data, over 50 percent of the U.S. rural population resides within metropolitan statistical areas.

Sustainable cities depend on urban forests. City trees -- a pillar of urban forests -- improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=5,660,237 trees from 63 of the largest US cities. The data comes from tree inventories conducted at the level of cities and/or neighborhoods. Each data sheet includes detailed information on tree location, species, nativity status (whether a tree species is naturally occurring or introduced), health, size, whether it is in a park or urban area, and more (comprising 28 standardized columns per datasheet). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems. Methods See eLife manuscript for full details. Below, we provide a summary of how the dataset was collected and processed.

Data Acquisition We limited our search to the 150 largest cities in the USA (by census population). To acquire raw data on street tree communities, we used a search protocol on both Google and Google Datasets Search (https://datasetsearch.research.google.com/). We first searched the city name plus each of the following: street trees, city trees, tree inventory, urban forest, and urban canopy (all combinations totaled 20 searches per city, 10 each in Google and Google Datasets Search). We then read the first page of google results and the top 20 results from Google Datasets Search. If the same named city in the wrong state appeared in the results, we redid the 20 searches adding the state name. If no data were found, we contacted a relevant state official via email or phone with an inquiry about their street tree inventory. Datasheets were received and transformed to .csv format (if they were not already in that format). We received data on street trees from 64 cities. One city, El Paso, had data only in summary format and was therefore excluded from analyses.

Data Cleaning All code used is in the zipped folder Data S5 in the eLife publication. Before cleaning the data, we ensured that all reported trees for each city were located within the greater metropolitan area of the city (for certain inventories, many suburbs were reported - some within the greater metropolitan area, others not). First, we renamed all columns in the received .csv sheets, referring to the metadata and according to our standardized definitions (Table S4). To harmonize tree health and condition data across different cities, we inspected metadata from the tree inventories and converted all numeric scores to a descriptive scale including “excellent,” “good”, “fair”, “poor”, “dead”, and “dead/dying”. Some cities included only three points on this scale (e.g., “good”, “poor”, “dead/dying”) while others included five (e.g., “excellent,” “good”, “fair”, “poor”, “dead”). Second, we used pandas in Python (W. McKinney & Others, 2011) to correct typos, non-ASCII characters, variable spellings, date format, units used (we converted all units to metric), address issues, and common name format. In some cases, units were not specified for tree diameter at breast height (DBH) and tree height; we determined the units based on typical sizes for trees of a particular species. Wherever diameter was reported, we assumed it was DBH. We standardized health and condition data across cities, preserving the highest granularity available for each city. For our analysis, we converted this variable to a binary (see section Condition and Health). We created a column called “location_type” to label whether a given tree was growing in the built environment or in green space. All of the changes we made, and decision points, are preserved in Data S9. Third, we checked the scientific names reported using gnr_resolve in the R library taxize (Chamberlain & Szöcs, 2013), with the option Best_match_only set to TRUE (Data S9). Through an iterative process, we manually checked the results and corrected typos in the scientific names until all names were either a perfect match (n=1771 species) or partial match with threshold greater than 0.75 (n=453 species). BGS manually reviewed all partial matches to ensure that they were the correct species name, and then we programmatically corrected these partial matches (for example, Magnolia grandifolia-- which is not a species name of a known tree-- was corrected to Magnolia grandiflora, and Pheonix canariensus was corrected to its proper spelling of Phoenix canariensis). Because many of these tree inventories were crowd-sourced or generated in part through citizen science, such typos and misspellings are to be expected. Some tree inventories reported species by common names only. Therefore, our fourth step in data cleaning was to convert common names to scientific names. We generated a lookup table by summarizing all pairings of common and scientific names in the inventories for which both were reported. We manually reviewed the common to scientific name pairings, confirming that all were correct. Then we programmatically assigned scientific names to all common names (Data S9). Fifth, we assigned native status to each tree through reference to the Biota of North America Project (Kartesz, 2018), which has collected data on all native and non-native species occurrences throughout the US states. Specifically, we determined whether each tree species in a given city was native to that state, not native to that state, or that we did not have enough information to determine nativity (for cases where only the genus was known). Sixth, some cities reported only the street address but not latitude and longitude. For these cities, we used the OpenCageGeocoder (https://opencagedata.com/) to convert addresses to latitude and longitude coordinates (Data S9). OpenCageGeocoder leverages open data and is used by many academic institutions (see https://opencagedata.com/solutions/academia). Seventh, we trimmed each city dataset to include only the standardized columns we identified in Table S4. After each stage of data cleaning, we performed manual spot checking to identify any issues.

According to figures recently released by the United States Census, America’s largest metro areas are currently gaining population at impressive rates. The growth in these areas is in fact driving much of the population growth across the nation. Upon closer examination of the data, this growth is the result of two very different migrations – one coming from the location choices of Americans themselves, the other shaped by where new immigrants from outside the United States are heading.While many metro areas are attracting a net-inflow of migrants from other parts of the country, in several of the largest metros – New York, Los Angeles., and Miami, especially – there is actually a net outflow of Americans to the rest of the country. Immigration is driving population growth in these places. Sunbelt metros like Houston, Dallas, and Phoenix, and knowledge hubs like Austin, Seattle, San Francisco, and the District of Columbia are gaining much more from domestic migration.This map charts overall or net migration – a combination of domestic and international migration. Most large metros, those with at least a million residents, had more people coming in than leaving. The metros with the highest levels of population growth due to migration are a mix of knowledge-based economies and Sunbelt metros, including Houston, Dallas, Miami, District of Columbia, San Francisco, Seattle, and Austin. Eleven large metros, nearly all in or near the Rustbelt, had a net outflow of migrants, including Chicago, Detroit, Memphis, Philadelphia, and Saint Louis.Source: Atlantic Cities

This statistics shows the leading metropolitan areas in the United States in 2023 with the highest percentage of Asian population. Among the 81 largest metropolitan areas, Urban Honolulu, Hawaii was ranked first with **** percent of residents reporting as Asian in 2023.

Disclaimer: These data are updated by the author and are not an official product of the Federal Reserve Bank of Cleveland.This project provides two sets of migration estimates for the major US metro areas. The first series measures net migration of people to and from the urban neighborhoods of the metro areas. The second series covers all neighborhoods but breaks down net migration to other regions by four region types: (1) high-cost metros, (2) affordable, large metros, (3) midsized metros, and (4) small metros and rural areas. These series were introduced in a Cleveland Fed District Data Brief entitled “Urban and Regional Migration Estimates: Will Your City Recover from the Pandemic?"The migration estimates in this project are created with data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP). The CCP is a 5 percent random sample of the credit histories maintained by Equifax. The CCP reports the census block of residence for over 10 million individuals each quarter. Each month, Equifax receives individuals’ addresses, along with reports of debt balances and payments, from creditors (mortgage lenders, credit card issuers, student loan servicers, etc.). An algorithm maintained by Equifax considers all of the addresses reported for an individual and identifies the individual’s most likely current address. Equifax anonymizes the data before they are added to the CCP, removing names, addresses, and Social Security numbers (SSNs). In lieu of mailing addresses, the census block of the address is added to the CCP. Equifax creates a unique, anonymous identifier to enable researchers to build individuals’ panels. The panel nature of the data allows us to observe when someone has migrated and is living in a census block different from the one they lived in at the end of the preceding quarter. For more details about the CCP and its use in measuring migration, see Lee and Van der Klaauw (2010) and DeWaard, Johnson and Whitaker (2019). DefinitionsMetropolitan areaThe metropolitan areas in these data are combined statistical areas. This is the most aggregate definition of metro areas, and it combines Washington DC with Baltimore, San Jose with San Francisco, Akron with Cleveland, etc. Metro areas are combinations of counties that are tightly linked by worker commutes and other economic activity. All counties outside of metropolitan areas are tracked as parts of a rural commuting zone (CZ). CZs are also groups of counties linked by commuting, but CZ definitions cover all counties, both metropolitan and non-metropolitan. High-cost metropolitan areasHigh-cost metro areas are those where the median list price for a house was more than $200 per square foot on average between April 2017 and April 2022. These areas include San Francisco-San Jose, New York, San Diego, Los Angeles, Seattle, Boston, Miami, Sacramento, Denver, Salt Lake City, Portland, and Washington-Baltimore. Other Types of RegionsMetro areas with populations above 2 million and house price averages below $200 per square foot are categorized as affordable, large metros. Metro areas with populations between 500,000 and 2 million are categorized as mid-sized metros, regardless of house prices. All remaining counties are in the small metro and rural category.To obtain a metro area's total net migration, sum the four net migration values for the the four types of regions.Urban neighborhoodCensus tracts are designated as urban if they have a population density above 7,000 people per square mile. High density neighborhoods can support walkable retail districts and high-frequency public transportation. They are more likely to have the “street life” that people associate with living in an urban rather than a suburban area. The threshold of 7,000 people per square mile was selected because it was the average density in the largest US cities in the 1930 census. Before World War II, workplaces, shopping, schools and parks had to be accessible on foot. Tracts are also designated as urban if more than half of their housing units were built before WWII and they have a population density above 2,000 people per square mile. The lower population density threshold for the pre-war neighborhoods recognizes that many urban tracts have lost population since the 1960s. While the street grids usually remain, the area also needs su

In 2023, the real GDP of the Los Angeles metro area amount to around 1.08 trillion U.S. dollars, and increase after 2021. The overall quarterly GDP growth in the United States can be found here. Gross domestic product of Los AngelesWith a population of over 12.8 million inhabitants in 2023, Los Angeles is the second-largest city in America, following only New York. The Los Angeles metro area also ranked second among U.S. metro areas in terms of gross metropolitan product, second again only to New York City metro area, which came in with a GMP of 1.99 trillion U.S. dollars to Los Angeles’ 1.13 trillion U.S. dollars in the fiscal year of 2021. Chicago metro area ranked third with GMP of 757.2 billion U.S. dollars. Additional detailed statistics about GDP in the United States is available here. Despite Los Angeles’ high GDP, L.A. did not do as well as some cities in terms of median household income. Los Angeles ranked 9th with a median household income of 76,135 U.S. dollars annually in 2022. This was slightly higher than the median household income of the United States in 2022, which came in at 74,580 U.S. dollars annually. Located in Southern California, Los Angeles is home to Hollywood, the famous epicenter of the U.S. film and television industries. The United States is one of the leading film markets worldwide, producing 449 films in 2022, many of them produced by Hollywood-based studios. In 2018, movie ticket sales in North America generated over 11.89 billion U.S. dollars in box office revenue. Famous Hollywood actresses earn millions annually, with the best paid, Sofia Vergara, earning 43 million U.S. dollars in 2020. Second on the list was Angelina Jolie with earnings of 35.5 million U.S. dollars.

Chart and table of population level and growth rate for the Los Angeles metro area from 1950 to 2025.

A dataset listing New York cities by population for 2024.