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 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.

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 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.

Canada's largest metropolitan area is Toronto, in Ontario. In 2022. Over 6.6 million people were living in the Toronto metropolitan area. Montréal, in Quebec, followed with about 4.4 million inhabitants, while Vancouver, in Britsh Columbia, counted 2.8 million people as of 2022.

The average for 2024 based on 24 countries was 63.16 percent. The highest value was in Bermuda: 100 percent and the lowest value was in Saint Lucia: 19.31 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

Provides information highlights by topic via key indicators for various levels of geography.

Provides information highlights by topic via key indicators for various levels of geography.

As of 2025, Tokyo-Yokohama in Japan was the largest world urban agglomeration, with 37 million people living there. Delhi ranked second with more than 34 million, with Shanghai in third with more than 30 million inhabitants.

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.

The global metro car market is experiencing robust growth, driven by increasing urbanization, rising passenger traffic in metropolitan areas, and government initiatives promoting sustainable public transportation. The market, valued at approximately $25 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated market size of $45 billion by 2033. This growth is fueled by several key trends, including the adoption of advanced technologies like automated train operation systems and lightweight materials to enhance efficiency and reduce energy consumption. Furthermore, the expansion of existing metro networks and the development of new lines in emerging economies are significantly contributing to market expansion. While challenges such as high initial infrastructure investment costs and potential supply chain disruptions exist, the long-term outlook remains positive, driven by the sustained need for efficient and sustainable urban transportation solutions. The market segmentation reveals a dynamic landscape. Type A, B, and C metro cars cater to varying operational needs and passenger capacities, with Type A cars (smaller capacity) holding a significant share due to their suitability for smaller cities and less congested routes. Large cities are currently the largest consumers of metro cars, however, medium and smaller cities are experiencing substantial growth reflecting the expanding urban footprint globally. Geographically, Asia-Pacific, particularly China and India, are major contributors to the market's growth, fueled by rapid urbanization and substantial investment in public transportation infrastructure. North America and Europe also represent significant markets, driven by upgrades and expansions of existing networks and the focus on sustainable transportation. Key players like CRRC, Knorr-Bremse, Bombardier, Alstom, Siemens, Hitachi, BEML Limited, and Skoda Transportation are actively involved in this growth, constantly innovating to meet evolving market demands.

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 global Smart Cities Solutions market is experiencing robust growth, driven by increasing urbanization, the need for improved infrastructure, and the rising adoption of advanced technologies. The market, estimated at $500 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $1.5 trillion by 2033. Key drivers include government initiatives promoting smart city development, the rising demand for enhanced public safety and security systems, the increasing adoption of IoT devices and data analytics for optimized resource management, and the growing need for sustainable and efficient urban solutions. Significant market trends include the integration of AI and machine learning for predictive maintenance and resource allocation, the expansion of 5G networks enabling faster data transmission and real-time responsiveness, and the increasing focus on cybersecurity to protect critical infrastructure. However, the market faces restraints such as high initial investment costs, concerns about data privacy and security, and the lack of standardized interoperability between different smart city solutions. The market is segmented by application (Smart Security, Smart Infrastructure, Smart Energy, Smart Governance & Education, Smart Building, Smart Healthcare, Smart Mobility, Others) and type (Hardware, Software, and Services). While Smart Security and Smart Infrastructure currently hold the largest market shares, Smart Healthcare and Smart Mobility are expected to witness rapid growth due to escalating healthcare needs and increasing traffic congestion in urban areas. Geographically, North America and Europe currently dominate the market due to strong technological advancements and supportive government policies. However, the Asia-Pacific region is anticipated to exhibit the highest growth rate over the forecast period, fueled by rapid urbanization and substantial government investments in smart city initiatives in countries like China and India. Major players in the market, including Cisco, IBM, Oracle, and Huawei, are focusing on strategic partnerships and technological innovations to strengthen their market positions. The competitive landscape is marked by intense rivalry and ongoing consolidation, with companies seeking to expand their service portfolios and geographical reach.

The global urban design market is experiencing robust growth, driven by rapid urbanization, increasing infrastructure development, and a rising demand for sustainable and resilient city planning. The market, estimated at $500 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $900 billion by 2033. Key drivers include government initiatives promoting smart city development, the need for efficient transportation systems, and a focus on improving the quality of life in urban areas. The market is segmented by type (zoning, transport, infrastructure) and application (big city, small city), with significant opportunities existing in large metropolitan areas undergoing rapid expansion and modernization. Leading architecture and design firms, including Gensler, Gold Mantis, Jacobs, Stantec, and others, are shaping this market landscape through innovative design solutions and technological advancements. Growth is geographically diverse, with North America, Europe, and Asia-Pacific representing major market segments. The ongoing global emphasis on sustainable development further fuels market growth, with a strong focus on green building practices and environmentally conscious urban planning. The market's growth trajectory is significantly influenced by several trends. These include the adoption of Building Information Modeling (BIM) and other digital design tools to enhance efficiency and collaboration, the growing importance of data analytics in urban planning, and the increasing focus on community engagement and participatory design processes. However, challenges such as economic downturns, regulatory hurdles, and the complexities of coordinating diverse stakeholders can potentially restrain market growth. Nevertheless, the long-term outlook remains positive, fueled by persistent urbanization and the continuous need for improved urban environments. Specific regional variations exist, reflecting differing economic conditions, infrastructure priorities, and governmental policies impacting urban development strategies. The market is poised for expansion in emerging economies as these regions increasingly prioritize urban infrastructure and sustainable development initiatives.

Release Date: 2023-10-26.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY23-0479)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2022 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2022 ABS collection year produces statistics for the 2021 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.This is the only table in the ABS series to provide information on select economic and demographic characteristics of business owners (CBO) for U.S. employer firms that reported the sex, ethnicity, race, and veteran status for up to four persons owning the largest percentage(s) of the business. The data include estimates for owners of U.S. respondent firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Owners of employer firms with more than one domestic establishment are counted in each geographic area and industry in which the firm operates, but only once in the U.S. and state totals for all sectors. Firms are asked to report their employees as of the March 12 pay period...Data Items and Other Identifying Records:.Data include estimates on:.Number of owners of respondent employer firms. Percent of number of owners of respondent employer firms (%)...These data are aggregated at the owner level for up to four persons owning the largest percentages of the business by the following demographic classifications:.All owners of respondent firms. Sex. Female. Male. . . Ethnicity. Hispanic. Non-Hispanic. . . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Nonminority (Firms classified as non-Hispanic and White). . . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Nonveteran. . . ...Data Notes:.. Data are tabulated at the owner level.. Respondents are informed that Hispanic origins are not races and are instructed to answer both the Hispanic origin and race questions.. An owner can be tabulated in more than one racial group. This can result because:. The sole owner was reported to be of more than one race.. The majority owner was reported to be of more than one race.. A majority combination of owners was reported to be of more than one race.. . An owner cannot be tabulated with two mutually exclusive demographic classifications (e.g. both as a veteran and a nonveteran.). CBO data are not designed to produce estimates for all U.S. business owners as information was only collected for up to four owners per firm. Researchers analyzing data to create their own estimates are responsible for the validity of those estimates and should cite the Census Bureau as the source of the original data only.. Percent values may exceed 100 due to noise....Owner Characteristics:.The ABS asked for information for up to four persons owning the largest percentage(s) of the business. Respondent firms include all firms that responded to the characteristics tabulated in this dataset and that reported sex, ethnicity, race, or veteran status for at least one business owner so that the classification of owners of respondent firms by sex, ethnicity, race, and veteran status could be determined. Furthermore, the ABS was designed to include select questions about owner characteristics from multiple reference periods and to incorporate new content each survey year based on topics of relevance. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a sex, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset...Owner characteristic topics for the 2022 ABS included in this table are the following: ..Year Acquired Ownership of Business (YRACQBUS).Primary Source of Income...

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

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.

In 2023, the GDP of the Seatle-Tacoma-Bellevue metro area amounted to ****** billion U.S. dollars, an increase from the previous year. The GDP of the United States since 1990 can be accessed here. Seattle metro area The Seattle metropolitan area in the U.S. state of Washington includes the city of Seattle, King County, Snohomish County, and Pierce County within the Puget Sound region. About **** million people were living in the Seattle metro area, which is more than half of Washington's total population in 2021 (about **** million people). This makes the Seattle metro area the **** largest metropolitan area in the United States, by population. However, Seattle is in fourth place among the 20 largest metro areas in terms of household income, which stood at ****** U.S. dollars in 2019. This is by far more than the average household income in the United States. Household income in Washington is on a similar high level. In 2021, the federal state of Washington was ranked **** in terms of household income among the states of the U.S. The city of Seattle is the largest city in the Pacific Northwest region of North America. It has about ******* residents and is among the ** largest cities in the United States. Seattle has always been an important coastal seaport city and a gateway to Alaska. The importance of the city and metro area is also due to fact that some of the biggest companies worldwide started in Seattle during the 1980s. Companies like Amazon and Microsoft are still based in the Seattle area in the state of Washington.