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 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.

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 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.

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.

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.

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;

In 2023, San Jose-Sunnyvale-Santa Clara Metro area in California was ranked first with median household income of 153,202 U.S. dollars. The Washington-Arlington-Alexandria metro area had a median household income of 121,469 U.S. dollars.

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.

The Inrix Inc. study reveals that the United States (U.S.) is ranked as the most congested developed country in the world, with drivers spending an average of 42 hours a year in traffic during peak hours. According to this study, the direct and indirect costs of congestion to all U.S. drivers amounts to nearly $300 billion in 2016, an average of $1,400 per driver.U.S. cities dominated the top 10 most congested cities globally, with Los Angeles (first), New York (third), San Francisco (fourth), Atlanta (eighth), and Miami (10th) each dealing with an economic drain on the city upwards of $2.5 billion caused by traffic congestion. Los Angeles commuters spent an average of 104 hours last year in traffic jams during peak congestion hours more than any other city in the world. This contributed to congestion costing drivers in Los Angeles $2,408 each and the city as a whole $9.6 billion from direct and indirect costs. Direct costs relate to the value of fuel and time wasted, and indirect costs refer to freight and business fees from company vehicles idling in traffic, which are passed on to households through higher prices.

This statistic shows the top 10 U.S. metropolitan statistical areas with the largest amount of employment in drugs and pharmaceuticals in 2023. New York-Newark-Jersey City (NY-NJ-PA) ranked second highest, with around ****** persons employed within this industry.

Graph and download economic data for All Employees: Information in Philadelphia-Camden-Wilmington, PA-NJ-DE-MD (MSA) (PHIL942INFO) from Jan 1990 to Apr 2025 about DE, Philadelphia, information, NJ, MD, PA, employment, and USA.

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.

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

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.

"The Statistical Abstract of the United States, published since 1878, is the standard summary of statistics on the social, political, and economic organization of the United States. It is designed to serve as a convenient volume for statistical reference and as a guide to other statistical publications and sources. The latter function is served by the introductory text to each section, the source note appearing below each table, and Appendix I, which comprises the Guide to Sources of Statisti cs, the Guide to State Statistical Abstracts, and the Guide to Foreign Statistical Abstracts. The Statistical Abstract sections and tables are compiled into one Adobe PDF named StatAbstract2007.pdf. This PDF is bookmarked by section and by table and can be searched using the Acrobat Search feature. The Statistical Abstract on CD-ROM is best viewed using Adobe Acrobat 5, or any subsequent version of Acrobat or Acrobat Reader. The Statistical Abstract tables and the metropolitan areas tables from Appendix II are available as Excel(.xls or .xlw) spreadsheets. In most cases, these spreadsheet files offer the user direct access to more data than are shown either in the publication or Adobe Acrobat. These files usually contain more years of data, more geographic areas, and/or more categories of subjects than those shown in the Acrobat version. The extensive selection of statistics is provided for the United States, with selected data for regions, divisions, states, metropolitan areas, cities, and foreign countries from reports and records of government and private agencies. Software on the disc can be used to perform full-text searches, view official statistics, open tables as Lotus worksheets or Excel workbooks, and link directly to source agencies and organizations for su pporting information. Except as indicated, figures are for the United States as presently constituted. Although emphasis in the Statistical Abstract is primarily given to national data, many tables present data for regions and individual states and a smaller number for metropolitan areas and cities.Statistics for the Commonwealth of Puerto Rico and for island areas of the United States are included in many state tables and are supplemented by information in Section 29. Additional information for states, cities, counties, metropolitan areas, and other small units, as well as more historical data are available in various supplements to the Abstract. Statistics in this edition are generally for the most recent year or period available by summer 2006. Each year over 1,400 tables and charts are reviewed and evaluated; new tables and charts of current interest are added, continuing series are updated, and less timely data are condensed or eliminated. Text notes and appendices are revised as appropriate. This year we have introduced 72 new tables covering a wide range of subject areas. These cover a variety of topics including: learning disability for children, people impacted by the hurricanes in the Gulf Coast area, employees with alternative work arrangements, adult computer and Internet users by selected characteristics, North America cruise industry, women- and minority-owned businesses, and the percentage of the adult population considered to be obese. Some of the annually surveyed topics are population; vital statistics; health and nutrition; education; law enforcement, courts and prison; geography and environment; elections; state and local government; federal government finances and employment; national defense and veterans affairs; social insurance and human services; labor force, employment, and earnings; income, expenditures, and wealth; prices; business enterprise; science and technology; agriculture; natural resources; energy; construction and housing; manufactures; domestic trade and services; transportation; information and communication; banking, finance, and insurance; arts, entertainment, and recreation; accommodation, food services, and other services; foreign commerce and aid; outlying areas; and comparative international statistics." Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission to represent the United States Census Bureau's 2000 Decennial Census data at the block geography.Attributes:FIPSSTCO = The Federal Information Processing Series (FIPS) state and county codes. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.TRACT2000 = Census Tract Codes and Numbers. Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.BLOCK2000= Census Block Numbers are numbered uniquely with a four-digit census block number from 0000 to 9999 within census tract, which nest within state and county. The first digit of the census block number identifies the block group. Block numbers beginning with a zero (in Block Group 0) are only associated with water-only areas.STFID = A concatenation of FIPSSTCO, TRACT2000, and BLOCK2000, which creates the entire FIPS code for this geography.WFD = Workforce Development Area (WFD) is a seven-county area created by agreement of county chief-elected officials, administered by the Atlanta Regional Commission and funded for training and employment activities under the federal Workforce Investment Act (WIA). For more information on ARC’s Workforce Development programs and services please consult www.atlantaregional.com/workforce/workforce.html.RDC_AAA = ARC Area Agency on Aging is a 10-county area funded by the Department of Human Resources and designated by the Older Americans Act to plan for the needs of the rapidly expanding group of older citizens in the Atlanta region. It is part of a statewide network of 12 AAAs and a national network of more than 670 AAAs. For more information on aging services please consult www.agewiseconnection.com.MNGWPD = The Metro North Georgia Water Planning District provides water resource plans, policies and coordination for metropolitan Atlanta. The District has developed regional plans for stormwater management, wastewater treatment and water supply and water conservation. The 15-county Water Planning District includes the ten counties in the ARC plus five additional counties (Bartow, Coweta, Forsyth, Hall, & Paulding). For more information please consult www.northgeorgiawater.org. MPO = The Metropolitan Planning Organization (MPO) is a 19-county area federally-designated for regional transportation planning to meet air quality standards and for programming projects to implement the adopted Regional Transportation Plan (RTP). The MPO planning area boundary includes the 10-county state-designated Regional Commission and nine additional counties (all of Coweta, Forsyth, & Paulding and parts of Barrow, Dawson, Newton, Pike, Spalding and Walton). This boundary takes into consideration both the current urbanized area as well as areas forecast to become urbanized in the next 20 years.MSA = the 29-County “Atlanta-Sandy Springs-Roswell, GA” Metropolitan Statistical Area (MSA) and the 39-county “Atlanta--Athens-Clarke County--Sandy Springs, GA” Combined Statistical Area (CSA), which includes the 29 counties of the Atlanta MSA along with the Athens-Clarke County and Gainesville MSAs and the micropolitan statistical areas of Calhoun, Cedartown, Jefferson, LaGrange and Thomaston, GA. The U.S. Office of Management and Budget (OMB) defines CSAs, MSAs and the smaller micropolitan statistical areas nationwide according to published standards applied to U.S. Census Bureau data. These various statistical areas describe substantial core areas of population together with adjacent communities having a high degree of economic and social integration, often illustrated in high rates of commuting from the adjacent areas to job locations in the core. For more information, please consult http://www.census.gov/population/metro/data/metrodef.htmlF1HR_NA = The Federal 1-Hour Air Quality Non-Attainment Area is a fine particulate matter standard (PM2.5). The non-attainment area under this standard includes the 15-county eight-hour ozone nonattainment area plus Barrow, Carroll, Hall, Spalding, Walton, and small parts of Heard and Putnam counties.F8HR_NA: The Federal 8-Hour Air Quality Non-Attainment Area for the 2008 eight-hour ozone standard is 15 counties.ACRES = The number of acres contained within the Block.SQ_MILES = The number of square miles contained within the Block.Source: United States Census Bureau, Atlanta Regional CommissionDate: 2000For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

50 year Projected Urban Growth scenarios. Base year is 2000. Projected year in this dataset is 2050.

By 2020, most forecasters agree, California will be home to between 43 and 46 million residents-up from 35 million today. Beyond 2020 the size of California's population is less certain. Depending on the composition of the population, and future fertility and migration rates, California's 2050 population could be as little as 50 million or as much as 70 million. One hundred years from now, if present trends continue, California could conceivably have as many as 90 million residents. Where these future residents will live and work is unclear. For most of the 20th Century, two-thirds of Californians have lived south of the Tehachapi Mountains and west of the San Jacinto Mountains-in that part of the state commonly referred to as Southern California. Yet most of coastal Southern California is already highly urbanized, and there is relatively little vacant land available for new development. More recently, slow-growth policies in Northern California and declining developable land supplies in Southern California are squeezing ever more of the state's population growth into the San Joaquin Valley. How future Californians will occupy the landscape is also unclear. Over the last fifty years, the state's population has grown increasingly urban. Today, nearly 95 percent of Californians live in metropolitan areas, mostly at densities less than ten persons per acre. Recent growth patterns have strongly favored locations near freeways, most of which where built in the 1950s and 1960s. With few new freeways on the planning horizon, how will California's future growth organize itself in space? By national standards, California's large urban areas are already reasonably dense, and economic theory suggests that densities should increase further as California's urban regions continue to grow. In practice, densities have been rising in some urban counties, but falling in others.

These are important issues as California plans its long-term future. Will California have enough land of the appropriate types and in the right locations to accommodate its projected population growth? Will future population growth consume ever-greater amounts of irreplaceable resource lands and habitat? Will jobs continue decentralizing, pushing out the boundaries of metropolitan areas? Will development densities be sufficient to support mass transit, or will future Californians be stuck in perpetual gridlock? Will urban and resort and recreational growth in the Sierra Nevada and Trinity Mountain regions lead to the over-fragmentation of precious natural habitat? How much water will be needed by California's future industries, farms, and residents, and where will that water be stored? Where should future highway, transit, and high-speed rail facilities and rights-of-way be located? Most of all, how much will all this growth cost, both economically, and in terms of changes in California's quality of life? Clearly, the more precise our current understanding of how and where California is likely to grow, the sooner and more inexpensively appropriate lands can be acquired for purposes of conservation, recreation, and future facility siting. Similarly, the more clearly future urbanization patterns can be anticipated, the greater our collective ability to undertake sound city, metropolitan, rural, and bioregional planning.

Consider two scenarios for the year 2100. In the first, California's population would grow to 80 million persons and would occupy the landscape at an average density of eight persons per acre, the current statewide urban average. Under this scenario, and assuming that 10% percent of California's future population growth would occur through infill-that is, on existing urban land-California's expanding urban population would consume an additional 5.06 million acres of currently undeveloped land. As an alternative, assume the share of infill development were increased to 30%, and that new population were accommodated at a density of about 12 persons per acre-which is the current average density of the City of Los Angeles. Under this second scenario, California's urban population would consume an additional 2.6 million acres of currently undeveloped land. While both scenarios accommodate the same amount of population growth and generate large increments of additional urban development-indeed, some might say even the second scenario allows far too much growth and development-the second scenario is far kinder to California's unique natural landscape.

This report presents the results of a series of baseline population and urban growth projections for California's 38 urban counties through the year 2100. Presented in map and table form, these projections are based on extrapolations of current population trends and recent urban development trends. The next section, titled Approach, outlines the methodology and data used to develop the various projections. The following section, Baseline Scenario, reviews the projections themselves. A final section, entitled Baseline Impacts, quantitatively assesses the impacts of the baseline projections on wetland, hillside, farmland and habitat loss.

In 20212, the San Jose-Sunnyvale-Santa Clara metro area in California had the highest per capita income at 64,169 U.S. dollars. The second highest, San Francisco-Oakland-Berkeley metro area is also located in California.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission to represent the United States Census Bureau's 2010 Decennial Census Urbanized Areas and Urban Clusters.In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles. The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes.Attributes:UACE10 = Census urbanized area/urban cluster codeGEOID10 = UACE10NAME10 = Name of the urbanized area or urban clusterNAMELSAD10 = NAME10 + "Urbanized Area" or "Urban Cluster"LSAD10 = Legal/statistical area descriptionMTFCC10 = MAF/TIGER feature class codeUATYP10 = Census urban area typeFUNCSTAT10 = Functional statusALAND10 = Total land area in square metersAWATER10 = Total water area in square metersINTPTLAT10 = Latitude of geography centroidINTPTLON10 = Longitude of geography centroidShape.STArea() = Total area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2010For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com