Land area (sq. km) in United States was reported at 9147420 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Land area (sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

Surface area (sq. km) in United States was reported at 9831510 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Surface area (sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

United States US: Surface Area data was reported at 9,831,510.000 sq km in 2017. This stayed constant from the previous number of 9,831,510.000 sq km for 2016. United States US: Surface Area data is updated yearly, averaging 9,629,090.000 sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 9,831,510.000 sq km in 2017 and a record low of 9,629,090.000 sq km in 1999. United States US: Surface Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Land Use, Protected Areas and National Wealth. Surface area is a country's total area, including areas under inland bodies of water and some coastal waterways.; ; Food and Agriculture Organization, electronic files and web site.; Sum;

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

The statistic shows the 30 largest countries in the world by area. Russia is the largest country by far, with a total area of about 17 million square kilometers.

Population of Russia

Despite its large area, Russia - nowadays the largest country in the world - has a relatively small total population. However, its population is still rather large in numbers in comparison to those of other countries. In mid-2014, it was ranked ninth on a list of countries with the largest population, a ranking led by China with a population of over 1.37 billion people. In 2015, the estimated total population of Russia amounted to around 146 million people. The aforementioned low population density in Russia is a result of its vast landmass; in 2014, there were only around 8.78 inhabitants per square kilometer living in the country. Most of the Russian population lives in the nation’s capital and largest city, Moscow: In 2015, over 12 million people lived in the metropolis.

In 2022, the population density in the United States remained nearly unchanged at around 36.43 inhabitants per square kilometer. Nevertheless, 2022 still represents a peak in the population density in the United States. Population density is calculated by dividing the total population by the total land area, to show the average number of people living there per square kilometer of land.Find more key insights for the population density in countries like Mexico.

United States Land Use: Land Area: Other data was reported at 1,925,342.000 sq km in 2022. This records an increase from the previous number of 1,913,948.000 sq km for 2021. United States Land Use: Land Area: Other data is updated yearly, averaging 1,984,061.000 sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 4,889,480.000 sq km in 1989 and a record low of 1,863,894.000 sq km in 1991. United States Land Use: Land Area: Other data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Land Use: OECD Member: Annual.

The average for 2021 based on 24 countries was 312072.4 sq. km. The highest value was in Canada: 3468911.3 sq. km and the lowest value was in Aruba: 4.2 sq. km. The indicator is available from 1990 to 2022. Below is a chart for all countries where data are available.

United States Land Use: Land Area: Forest data was reported at 3,097,950.000 sq km in 2022. This stayed constant from the previous number of 3,097,950.000 sq km for 2021. United States Land Use: Land Area: Forest data is updated yearly, averaging 3,066,464.000 sq km from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 3,100,950.000 sq km in 2016 and a record low of 3,024,500.000 sq km in 1990. United States Land Use: Land Area: Forest data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Land Use: OECD Member: Annual.

The average for 2021 based on 24 countries was 854251 sq. km. The highest value was in the USA: 9147420 sq. km and the lowest value was in Bermuda: 54 sq. km. The indicator is available from 1961 to 2022. Below is a chart for all countries where data are available.

The site suitability criteria included in the techno-economic land use screens are listed below. As this list is an update to previous cycles, tribal lands, prime farmland, and flood zones are not included as they are not technically infeasible for development. The techno-economic site suitability exclusion thresholds are presented in table 1. Distances indicate the minimum distance from each feature for commercial scale wind developmentAttributes: Steeply sloped areas: change in vertical elevation compared to horizontal distancePopulation density: the number of people living in a 1 km2 area Urban areas: defined by the U.S. Census. Water bodies: defined by the U.S. National Atlas Water Feature Areas, available from Argonne National Lab Energy Zone Mapping Tool Railways: a comprehensive database of North America's railway system from the Federal Railroad Administration (FRA), available from Argonne National Lab Energy Zone Mapping Tool Major highways: available from ESRI Living Atlas Airports: The Airports dataset including other aviation facilities as of July 13, 2018 is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). The Airports database is a geographic point database of aircraft landing facilities in the United States and U.S. Territories. Attribute data is provided on the physical and operational characteristics of the landing facility, current usage including enplanements and aircraft operations, congestion levels and usage categories. This geospatial data is derived from the FAA's National Airspace System Resource Aeronautical Data Product. Available from Argonne National Lab Energy Zone Mapping Tool Active mines: Active Mines and Mineral Processing Plants in the United States in 2003Military Lands: Land owned by the federal government that is part of a US military base, camp, post, station, yard, center, or installation. Table 1 Wind Steeply sloped areas >10o Population density >100/km2 Capacity factor <20% Urban areas <1000 m Water bodies <250 m Railways <250 m Major highways <125 m Airports <5000 m Active mines <1000 m Military Lands <3000m For more information about the processes and sources used to develop the screening criteria see sources 1-7 in the footnotes. Data updates occur as needed, corresponding to typical 3-year CPUC IRP planning cyclesFootnotes:[1] Lopez, A. et. al. “U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis,” 2012. https://www.nrel.gov/docs/fy12osti/51946.pdf[2] https://greeningthegrid.org/Renewable-Energy-Zones-Toolkit/topics/social-environmental-and-other-impacts#ReadingListAndCaseStudies[3] Multi-Criteria Analysis for Renewable Energy (MapRE), University of California Santa Barbara. https://mapre.es.ucsb.edu/[4] Larson, E. et. al. “Net-Zero America: Potential Pathways, Infrastructure, and Impacts, Interim Report.” Princeton University, 2020. https://environmenthalfcentury.princeton.edu/sites/g/files/toruqf331/files/2020-12/Princeton_NZA_Interim_Report_15_Dec_2020_FINAL.pdf.[5] Wu, G. et. al. “Low-Impact Land Use Pathways to Deep Decarbonization of Electricity.” Environmental Research Letters 15, no. 7 (July 10, 2020). https://doi.org/10.1088/1748-9326/ab87d1.[6] RETI Coordinating Committee, RETI Stakeholder Steering Committee. “Renewable Energy Transmission Initiative Phase 1B Final Report.” California Energy Commission, January 2009.[7] Pletka, Ryan, and Joshua Finn. “Western Renewable Energy Zones, Phase 1: QRA Identification Technical Report.” Black & Veatch and National Renewable Energy Laboratory, 2009. https://www.nrel.gov/docs/fy10osti/46877.pdf.[8]https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Urban+Areas[9]https://ezmt.anl.gov/[10]https://www.arcgis.com/home/item.html?id=fc870766a3994111bce4a083413988e4[11]https://mrdata.usgs.gov/mineplant/Credits Title: Techno-economic screening criteria for utility-scale wind energy installations for Integrated Resource Planning Purpose for creation: These site suitability criteria are for use in electric system planning, capacity expansion modeling, and integrated resource planning. Keywords: wind energy, resource potential, techno-economic, IRP Extent: western states of the contiguous U.S. Use Limitations The geospatial data created by the use of these techno-economic screens inform high-level estimates of technical renewable resource potential for electric system planning and should not be used, on their own, to guide siting of generation projects nor assess project-level impacts.Confidentiality: Public ContactEmily Leslie Emily@MontaraMtEnergy.comSam Schreiber sam.schreiber@ethree.com Jared Ferguson Jared.Ferguson@cpuc.ca.govOluwafemi Sawyerr femi@ethree.com

Agricultural land (sq. km) in United States was reported at 4058104 sq. Km in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Agricultural land (sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

Density of all roads within a 3-km radius developed using a circular focal moving window analysis.

This data set represents predicted nitrate concentration in ground water used for drinking, in milligrams per liter, in the conterminous United States, and was generated by a national nonlinear regression model based on 14 input parameters. Nolan and Hitt (2006) developed two national models to predict contamination of ground water by nonpoint sources of nitrate. The nonlinear approach to national-scale Ground-WAter Vulnerability Assessment (GWAVA) uses components representing nitrogen (N) sources, transport, and attenuation. One model (GWAVA-S) predicts nitrate contamination of shallow (typically less than 5 meters deep), recently recharged ground water, which may or may not be used for drinking. The other (GWAVA-DW) predicts ambient nitrate concentration in deeper supplies used for drinking. This data set is a national map of nitrate concentration (in milligrams per liter) in U.S ground water used for drinking as predicted by the GWAVA-DW model. The data set is one of 14 spatial data sets (1 output data set and 13 input data sets) associated with the GWAVA-DW model. Full details of the model development are in Nolan and Hitt (2006). This data set represents the model output, which is depicted in figure 3 of Nolan and Hitt (2006) that shows predicted nitrate concentration in milligrams per liter in ground water used for drinking. The model results can be used to indicate areas of the Nation that may be vulnerable to nitrate contamination. For inputs to the model, spatial attributes representing 13 nitrogen loading and transport and attenuation factors were compiled as raster data sets (1-km by 1-km grid cell size) for the conterminous United States (see table 1). >Table 1.-- Parameters of nonlinear regression model for > nitrate in ground water used for drinking (GWAVA-DW) > and corresponding input spatial data sets. > [kg, kilograms; km2, square kilometers.] > >Nitrogen Source Factors Data Set Name > 1 farm fertilizer (kg/hectare) gwava-dw_ffer > 2 confined manure (kg/hectare) gwava-dw_conf > 3 orchards/vineyards (percent) gwava-dw_orvi > 4 population density (people/km2) gwava-dw_popd > >Transport to Aquifer Factors > 5 water input (km2/cm) gwava-dw_wtin > 6 glacial till (yes/no) gwava-dw_gtil > 7 semiconsolidated sand aquifers gwava-dw_semc > (yes/no) > 8 sandstone and carbonate rocks gwava-dw_sscb > (yes/no) > 9 drainage ditch (km2) gwava-dw_ddit > 10 Hortonian overland flow gwava-dw_hor > (percent of streamflow) > >Attenuation Factors > 11 fresh surface water withdrawal gwava-dw_swus > for irrigation (megaliters/day) > 12 irrigation tailwater recovery (km2) gwava-dw_twre > 13 Dunne overland flow gwava-dw_dun > (percent of streamflow) > 14 well depth (meters) - "Farm fertilizer" is the average annual nitrogen input from commercial fertilizer applied to agricultural lands, 1992-2001, in kilograms per hectare. "Confined manure" is the average annual nitrogen input from confined animal manure, 1992 and 1997, in kilograms per hectare. "Orchards/vineyards" is the percent of orchards/vineyards land cover classification. "Population density" is 1990 block group population density, in people per square kilometer. "Water input" is the ratio of the total area of irrigated land to precipitation, in square kilometers per centimeter. "Glacial till" is the presence or absence of poorly sorted glacial till east of the Rocky Mountains. "Semiconsolidated sand aquifers" is the presence or absence of semiconsolidated sand aquifers. "Sandstone and carbonate rocks" is the presence or absence of sandstone and carbonate rock aquifers. "Drainage ditch" is the area of National Resources Inventory surface drainage, field ditch conservation practice, in square kilometers. "Hortonian overland flow" is infiltration excess overland flow estimated by TOPMODEL, in percent of streamflow. "Fresh surface water withdrawal for irrigation" is the amount of fresh surface water withdrawal for irrigation, in megaliters per day. "Irrigation tailwater recovery" is the area of National Resources Inventory irrigation system, tailwater recovery conservation practice, in square kilometers. "Dunne overland flow" is saturation overland flow estimated by TOPMODEL, in percent of streamflow. "Well depth" is the depth of the well, in meters. Well depth was not compiled as a spatial data set. Well depth equals 50 meters for the model simulation being presented. Reference cited: Nolan, B.T. and Hitt, K.J., 2006, Vulnerability of shallow ground water and drinking-water wells to nitrate in the United States: Environmental Science and Technology, vol. 40, no. 24, pages 7834-7840.

This dataset of 40 square kilometer (sq. km) hexagons was created by the U.S. EPA's Environmental Monitoring and Assessment Program (EMAP) and is being released by the U.S. Geological Survey for public use. The 40 sq. km hexagons were derived from a grid consisting of a triangular array of points that cover the United States and neighboring Canada and Mexico. The base grid of points had a companion areal structure called a tessellation. The base tessellation hexagons constituted this tessellation. In other words, surrounding each grid point was a hexagon that defines the area within which all points are closer to this grid point than to any other, and the set of hexagons defined this way completely and -mutually exclusively covers the space of the grid. The grid had a base density of approximately 648 sq. km per point with a spacing of approximately 27 km between points. The original 40 sq. km hexagons (which do not form a tessellation) were centered about the randomized grid points and are exactly 1/16th the size of the tessellation hexagons (and therefore slightly more than 40 sq. km). Hexagon boundaries are distributed in geodetic coordinates based on the Clarke 1866 model of the Earth, meaning that the coordinates are latitude and longitude on the ellipsoid used by most North American geodetic coordinate systems. Distribution can also be made in GRS 80 coordinates if desired. The precision of the coordinates is to millionths of a degree (i.e., to 6 decimal places of a degree). This corresponds to about 0.1 meter on the surface of the Earth. The point grid was constructed in the plane of a special version of the Lambert azimuthal equal area projection; for subsequent use they may be projected using other map projections. When other projections are used, the geometry of the point grid will not be perfectly triangular nor will the hexagons surrounding the points be perfect, since sizes and/or shapes and/or distances will necessarily be distorted in another projection relative to the one used to construct the grid. This 40 sq. km hexagon tessellation was created by two successive enhancements of the 648 sq. km tessellation by factors of four. See White et al. 1992 in references.

This dataset provides values for ROAD DENSITY KM OF ROAD PER SQ KM OF LAND AREA WB DATA.HTML reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

United States Land Cover: Bare Area: Unconsolidated data was reported at 0.000 sq km th in 2019. This stayed constant from the previous number of 0.000 sq km th for 2018. United States Land Cover: Bare Area: Unconsolidated data is updated yearly, averaging 0.000 sq km th from Dec 1992 (Median) to 2019, with 5 observations. The data reached an all-time high of 0.000 sq km th in 2019 and a record low of 0.000 sq km th in 2019. United States Land Cover: Bare Area: Unconsolidated data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Land Cover: OECD Member: Annual.

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies of sea-floor sediment distribution, processes that control sediment distribution, nearshore environmental concerns, and the relation of benthic community structures to the sea-floor geology. Acoustic data collected during hydrographic surveys provide valuable base maps for marine geological interpretations. These maps help define the geological variability of the seafloor (one of the primary controls of benthic habitat diversity); improve our understanding of the processes that control the distribution and transport of bottom sediments, and the distribution of benthic habitats and associated infaunal community structures; and provide a detailed framework for future research, monitoring, and management activities. This shapefile represents the geologic interpretation of features influencing the bathymetry of study area H11250, The Race. Sharing of multibeam bathymetric data (NOAA Ship Thomas Jefferson, October 2003 survey H11250) between NOAA's Atlantic Hydrographic Branch and the State of Connecticut/USGS Geologic Mapping Cooperative has yielded a new geologic perspective on approximately 94 km2 of the sea floor in the vicinity of The Race, an area where the Orient Point-Fishers Island segment of the Harbor Hill-Roanoke Point-Orient Point-Fishers Island-Charlestown Moraine marks the dividing line between easternmost Long Island Sound and northwestern Block Island Sound. The detailed bathymetry collected by NOAA has been examined in relation to seismic data collected concurrently, as well as archive data collected as part of a long-standing geologic mapping partnership between the State of Connecticut and the U.S. Geological Survey (USGS). These new data reveal previously unknown details of the physical character of the sea floor such as bedforms, moraines, and ship wrecks. These features have been mapped as interpretive GIS data layers that can be used in conjunction with the multibeam grid H11250G or related shaded relief graphics (h11250gcolhs.tif).

This data set provides the first global inventory of the spatial distribution and density of constructed impervious surface area (ISA) based on the brightness of satellite observed and calibrated nighttime lights [U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS)] and population count from ORNL LandScan 2004 [which includes input from three satellite data sources: NASA MODIS land cover, the topographic data from the Shuttle Radar Topography Mission (SRTM), and the high resolution Controlled Image Base (CIB) from the U.S. National Geospatial Intelligence Agency (NGA)]. Examples of ISA include roads, parking lots, buildings, driveways, sidewalks, and other manmade surfaces. While high spatial resolution is required to observe these features, this product was made at one km2 resolution. The reference data used in the calibration were derived from 30-meter resolution ISA estimates of the USA from the U.S. Geological Survey. Nominally the product is for the years 2000-2001 since both the nighttime lights and reference data are from those two years. Investigators used the product to estimate the world’s total ISA, to rank the leading countries in total ISA and to calculate the quantity of ISA per person for individual countries. In addition, they aggregated the ISA density for the major watershed units of the world to identify those watersheds impacted by the proliferation of ISA. Investigators found that 1.05% of the United States land area is impervious surface (83,337 km2) and 0.43% of the world's land surface (579,703 km2) is constructed impervious surface. China has more ISA than any other country (87,182 km2), but has only 67 m2 of ISA per person, compared to 297 m2 per person in the USA. Hydrologic and environmental impacts of ISA begin to be exhibited when the density of ISA reaches 10% of the land surface. An examination of the areas with 10% or more ISA in watersheds finds that with the exception of Europe, the majority of watershed areas have less than 0.4% of their area at or above the 10% ISA threshold. The investigators believe the next step for improving the product is to include reference ISA data from many more areas around the world. For additional information, see Elvidge, C.D., B.T. Tuttle, P.C. Sutton, K.E. Baugh, A.T. Howard, C. Milesi, B.L. Bhaduri, and R. Nemani. 2007. Global Distribution and Density of Constructed Impervious Surfaces. Sensors 7: 1962-1979.

The following is from the Methods section of the related journal article. Please see the article and its accompanying appendix to read more about these data.

We considered the spatial configuration of land protection in the coterminous US. Specifically, we used all 3108 US counties as our units of analysis (median county area in coterminous US = 1670 km2). While other choices of spatial unit would have been possible, counties provide meaningful spatial units for many smaller conservation actors, a convenient reporting unit for relevant socioenvironmental data, and a large enough area to encompass a range of conservation actors.

Protected area data

Protected area data were obtained from the PAD-US 2.0 (US Geological Survey Gap Analysis Project 2018). Data for lands managed by the Bureau of Indian Affairs were collected from PAD-US 1.4 (US Geological Survey Gap Analysis Project 2016) because those data are absent from PAD-US 2.0. Data for rental contract lands managed by the USDA Farm ...