Rome is the largest Italian metropolitan area. As of 2025, the urban area of the capital city has a population of around 4.22 million people. Milan and Naples follow with 3.25 million and 2.96 million people, respectively. In terms of inhabitants per square kilometer, Naples, located in the south, has the highest population density. Rome, Milan, and Naples are also Italy's largest cities.

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.

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.

This statistics shows a ranking of the metropolitan areas in the United States in 2013 with the highest population density. As of 2013, Los Angeles-Long Beach-Anaheim in California was ranked first with a population density of 1,046 inhabitants per square kilometer.

Salt Lake City was the U.S. metro with the highest retail real estate investment growth in 2024. The value of capital allocated to retail real estate in Salt Lake City was approximately *** million U.S. dollars, an increase of *** percent since 2023. Meanwhile, South Florida was the market with the highest volume of investment. Overall, the value of retail real estate investment has declined notably since 2021, mostly due to the overall cooling of the commercial property market.

This statistic shows annual median household incomes in the United States in the largest metropolitan areas (measured by population). In 2019, the annual median household income in the metropolitan area of New York-Newark-Jersey City was ****** U.S. dollars.

This table presents the 2021 population counts for census metropolitan areas and census agglomerations, and their population centres and rural areas.

Data for the number of: (a) Consulate Generals, (b) International city organizations/networks, and (c) active Sister City relationships in each of the 100 largest metro areas in the United States (in 2019) from 1783-2024. The Main tab has the total for each of the measures of city diplomacy by year. The other tabs have each of the city diplomacy measures by metro area by year. The Graphs tab contains two line graphs depicting the data on the Main tab. The Sources tab contains information about the source data

Top 50 metropolitan areas, ranked by their scale-adjusted TFP (ξA).

The month's Map of the Month examines an issue of housing policy not often discussed: how big are the houses that get built? The map depicts metropolitan areas in the United States with both the largest and smallest units. As you can see, the San Francisco-Oakland urbanized area is on the small end of the scale.

This statistic shows the leading metropolitan areas with the highest percentage of population aged 65 years and over in the United States in 2019. In 2019, The Villages, Florida was ranked first with about **** percent of its population aged 65 years and over.

Unemployment Rates for Large Metropolitan Areas . Rates shown are a percentage of the labor force. Data refer to place of residence. Estimates for the current month are subject to revision the following month.

Compares distribution of highest certificate, diploma or degree between cities. Allows sorting/ranking of cities by percentage.

This is a polygon dataset for county boundaries as well as for city, township and unorganized territory (CTU) boundaries in the Twin Cities 7-county metropolitan area. The linework for this dataset comes from individual counties and is assembled by the Metropolitan Council for the MetroGIS community. This is a MetroGIS Regionally Endorsed dataset https://metrogis.org/.

The County CTU Lookup Table here https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-counties-and-ctus-lookup
is also included in this dataset and contains various data related to cities, townships, unorganized territories (CTUs) and any divisions created by county boundaries splitting them is also included in the dataset.

This dataset is updated quarterly. This dataset is composed of three shape files and one dbf table.
- Counties.shp = county boundaries
- CTUs.shp = city, township and unorganized territory boundaries
- CountiesAndCTUs.shp = combined county and CTU boundaries
- CountyCTULookupTable.dbf = various data related to CTUs and any divisions created by county boundaries splitting them is also included in the dataset, described here: https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-counties-and-ctus-lookup

NOTES:

- On 3/17/2011 it was discovered that the CTU ID used for the City of Lake St. Croix Beach was incorrect. It was changed from 2394379 to 2395599 to match GNIS.

- On 3/17/2011 it was discovered that the CTU ID used for the City of Lilydale was incorrect. It was changed from 2394457 to 2395708 to match GNIS.

- On 11/9/2010 it was discovered that the CTU ID used for the City of Crystal was incorrect. It was changed from 2393541 to 2393683 to match GNIS.

- Effective April 2008, a change was made in GNIS to match the FIPS place codes to the "civil" feature for each city instead of the "populated place" feature. Both cities and townships are now "civil" features within GNIS. This means that the official GNIS unique ID for every city in Minnesota has changed.

- The five digit CTU codes in this dataset are identical to the Federal Information Processing Standard (FIPS) ''Place'' codes. They are also used by the Census Bureau and many other organizations and are proposed as a MN state data coding standard.

- Cities and townships have also been referred to as ''MCDs'' (a census term), however this term technically refers to the part of each city or township within a single county. Thus, a few cities in the metro area that are split by county boundaries are actually comprised of two different MCDs. This was part of the impetus for a proposed MN state data standard that uses the ''CTU'' terminology for clarity.

- The boundary line data for this dataset comes from each county.

- A variety of civil divisions of the land exist within the United States. In Minnesota, only three types exist - cities, townships and unorganized territories. All three of these exist within the Twin Cities seven county area. The only unorganized territory is Fort Snelling (a large portion of which is occupied by the MSP International Airport).

- Some cities are split between two counties. Only those parts of cities within the 7-county area are included.

- Prior to the 2000 census, the FIPS Place code for the City of Greenwood in Hennepin County was changed from 25928 to 25918. This dataset reflects that change.

ABSTRACTWe discuss historic trends in large metropolitan areas in Brazil showing that manufacturing has decreased its share in the country but the movement was, in general, more intense in large metropolitan areas and particularly in the São Paulo Metropolitan Area (SPMA). This movement was more intense in the 1980s and in the first half of the 1990s. From mid 1990s up to the end of the 2000s, the manufacturing share trend became flat. We speculate that the first period reflects the exhaustion of the process of import substitution that took place in the previous three decades (1950 to 1980). The second period, from 1993 to 2009, is representative of a new model of growth and the evidence that manufacturing share became flat is reinforcing the idea of a new period in terms of manufacturing employment. While concentration has risen from 1996 to 2005, it decreased again in the second half of the first decade of the 2000s. The SPMA reinvented itself very quickly from late 1970s to mid-2000s.

The term “core based statistical area” (CBSA) became effective in 2000 and refers collectively to metropolitan and micropolitan statistical areas.Each metropolitan statistical area must have at least one urbanized area of 50,000 or more inhabitants. Each micropolitan statistical area must have at least one urban cluster of at least 10,000 but less than50,000 inhabitants. The categorization of CBSAs as either metropolitan or micropolitan statistical areas is based on the population in the most populous (or dominant) core, not the total CBSA population or the total population of all (multiple) cores within the CBSA.Counties or equivalent entities form the building blocks for metropolitan and micropolitan statistical areas. Central counties are those counties or equivalent entities in which at least 50 percent of the population resides within urban areas of 10,000 or more population, or that contain at least 5,000 people residing within a single urban area of 10,000 or more population. Additional outlying counties that meet specified requirements of commuting to or from the central counties may be included in the CBSA.

This map shows four of these densely populated areas are in California. The San Francisco-Oakland and San Jose Urban Areas rank second and third, respectively. That the New York Metropolitan area ranks fifth on this list shows that this density ranking is greatly affected by the nature of the land area designated as urban. Census Urban Areas comprise an urban core and associated suburbs. California's urban and suburban areas are more uniform in density when compared to New York's urban core and suburban periphery which have vastly different densities. Delano ranks fourth because it has a very small land area and its population is augmented by two large California State Prisons housing 10,000 inmates.

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

Japan JP: Population in Largest City data was reported at 37,397,437.000 Person in 2017. This records an increase from the previous number of 37,326,706.000 Person for 2016. Japan JP: Population in Largest City data is updated yearly, averaging 31,840,745.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 37,397,437.000 Person in 2017 and a record low of 16,678,821.000 Person in 1960. Japan JP: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Avg Sale to List: All Residential: Big Rapids, MI data was reported at 98.607 % in Jul 2020. This records an increase from the previous number of 97.012 % for Jun 2020. Avg Sale to List: All Residential: Big Rapids, MI data is updated monthly, averaging 93.576 % from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 98.607 % in Jul 2020 and a record low of 87.357 % in Nov 2014. Avg Sale to List: All Residential: Big Rapids, MI data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB050: Average Sales to List: by Metropolitan Areas.