Census Current (2022) Legal and Statistical Entities Web Map Service; January 1, 2022 vintage.

Census Regions are groupings of states and the District of Columbia that subdivide the United States for the presentation of census data. There are four census regions-Northeast, Midwest, South, and West. Each of the four census regions is divided into two or more census divisions. Puerto Rico and the Island Areas are not part of any census region or census division.

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Divisions are groupings of states within a census geographic region, established by the Census Bureau for the presentation of census data. The current nine divisions (East North Central, East South Central, Middle Atlantic, Mountain, New England, Pacific, South Atlantic, West North Central, and West South Central) are intended to represent relatively homogeneous areas that are subdivisions of the four census geographic regions.

This layer is a component of ENOW_Counties.

This map service presents spatial information about the Economics: National Ocean Watch (ENOW) data in the Web Mercator projection. The ENOW data provides time-series data on the ocean and Great Lakes economy, which includes six economic sectors dependent on the oceans and Great Lakes, and measures four economic indicators: Establishments, Employment, Wages, and Gross Domestic Product (GDP). The annual time-series data are available for about 400 coastal counties, 30 coastal states, 8 regions, and the nation. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

© NOAA Office for Coastal Management

Regional geophysical maps of the Great Basin, USA were generated from new and existing sources to support ongoing efforts to characterize geothermal resource potential in the western US. These include: (1) a provisional regional gravity grid that was produced from data compiled from multiple sources: data collected by the USGS and Utah Geological Survey under various projects, industry sources, and regional compilations derived from two sources: a Nevada state-wide database (Ponce, 1997), and a public domain dataset (Hildenbrand et al., 2002), (2) a regional magnetic grid derived from the North American magnetic compilation map of Bankey et al. (2002) and, (3) a regional depth-to-basement grid derived from Shaw and Boyd (2018). References: Bankey, V., Cuevas, A., Daniels, D., Finn, C.A., Hernandez, I., Hill, P., Kucks, R., Miles, W., Pilkington, M., Roberts, C., Roest, W., Rystrom, V., Shearer, S., Snyder, S., Sweeney, R.E., Velez, J., Phillips, J.D., and Ravat, D.K.A., 2002, Digital data grids for the magnetic anomaly map of North America, U.S. Geological Survey, Open-File Report 2002-414, https://doi.org/10.3133/ofr02414. Hildenbrand, T.G., Briesacher, A., Flanagan, G., Hinze, W.J., Hittelman, A.M., Keller, G.R., Kucks, R.P., Plouff, D., Roest, W., Seeley, J., Smith, D.A., and Webring, M., 2002, Rationale and operational plan to upgrade the U.S. Gravity Database: U.S. Geological Survey Open-File Report 02-463, 12p. [https://pubs.er.usgs.gov/publication/ofr0246; data downloaded from the Pan-American Center for Earth and Environmental Studies (PACES) gravity database in October 2007 from URL http://paces.geo.utep.edu/research/gravmag/gravmag.shtml]. Ponce, D.A., 1997, Gravity data of Nevada, U.S. Geological Survey Digital Data Series DDS-42. https://pubs.usgs.gov/dds/dds-42/. Shah, A.K, and Boyd, O.S., 2018, Depth to basement and thickness of unconsolidated sediments for the western United States—Initial estimates for layers of the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2018–1115, 13 p., https://doi.org/10.3133/ofr20181115.

This statistic shows the total land and water area of the United States by state and territory. Alabama covers an area of 52,420 square miles.

Layer Information: -Weather Events: Convection in Las Cruces and the Significant Flood Event of 2006 in El Paso are displayed. Clicking on the icon can give information of the phenomena or event. - Major Cities: Major cities and populations are mapped. The bigger the circle the bigger the population of that city. - Observation/ Data collection sites: This layer contains the location of where atmospheric soundings launched from the surface and where in-stu surface observations are gathered. The later includes Weather, Ocean, Lake, River, Water Quality, and Air Quality. - Köppen-Geiger Climate Divisions: General temperatures, precipitation, and latitude define these climate classes. The World Meteorological Organization (WMO) defined a classic climate record to be 30 years, so this current map is based of off the average weather an area has experienced from 1981 to 2010. New normals will be calculated in 2021. To read more click here. -National Weather Service Forecast Offices (WFO): Locations of the continental United States weather forecast offices, including office contact information. App Information: How to use it: Zooming in and out will turn on and off different layers. A zoomed out map will show the global Koppen climate classification. Zooming in will turn off the climate layer, while enabling the National Weather Service (NWS) Offices, Weather Events and other layers. Clicking on a Weather event or NWS office in the map will bring up a window with more information. - The legends and layers are shown by toggling the menus on via the icons at the bottom of the map.

This layer is sourced from maritimeboundaries.noaa.gov.

The ENC_General map service displays ENC data within the scale range of 1:600,001 and 1:1,500,000. The ENC data will be updated weekly. This map service is not intended for navigation purpose.

This data set delineates the boundaries of the U.S. Fish and Wildlife Service geographic Regions. The dataset was created as a geographic representation of the Regional administrative boundaries of the US Fish and Wildlife Service at a very coarse scale. The boundaries were created using the ArcGIS shoreline dataset from approximately 1995. This dataset should not be used for legal purposes or at small scales and does not accurately denote the shorelines of the united states. The Regional Boundaries data set is managed by the FWS Headquarters Information Resources and Technology Management, Branch of Geospatial Data Management. The complete data and metadata can be accessed here: https://catalog.data.gov/dataset/us-fish-and-wildlife-service-regional-boundaries. This data set is a graphical representation and has limitations of accuracy as determined by, among others, the source, scale and resolution of the data. DOI Interior Regions / Regional Boundaries (https://fws.maps.arcgis.com/home/item.html?id=309aa728d6c041ceaefc1526a409b5d1).

This map was created as part of a worldwide series of geologic maps for the U.S. Geological Survey's World Energy Project. These products are available on CD-ROM and through the Internet. The goal of the project is to assess the undiscovered, technically recoverable oil and gas resources of the world. Most of the source data for this map compilation were digitized from the Geologic-Tectonic Map of the Caribbean Region by J.E. Case and T.L. Holcombe, at a scale of 1:2,500,000. For data management purposes, the world was divided into eight energy regions based on political boundaries and corresponding approximately to the economic regions of the world as defined by the U.S. Department of State. Region Six encompasses the Caribbean area, Central America, and South America. Other products are also available related to Region Six, including the Geologic Map of South America (USGS Open File Report 97-470-D). Countries listed below are shown whole or in part within the map extent of the Caribbean region: Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Colombia Costa Rica Cuba Dominica Dominican Republic El Salvador Grenada Guadeloupe Guatemala Guyana Haiti Honduras Jamaica Martinique Mexico Montserrat Netherlands Antilles Nicaragua Panama Puerto Rico St. Kitts and Nevis St. Lucia St. Vincent and the Grenadines Trinidad and Tobago Turks and Caicos Islands United States Venezuela Virgin Islands The world was previously divided into geologic provinces for the World Energy Project, of which a subset is shown on the map. Each province has a set of geologic characteristics that distinguish it from surrounding provinces. These characteristics may include dominant lithologies, the age of the strata, and/or structural type. Each province is assigned a unique number and may fall within two or more countries or assessment regions. The World Geographic Coordinate System of 1984 was used for data storage and map display. Other details about the map compilation and data sources are provided in several metadata formats in the data section on this CD-ROM. Various software packages were used to create this map including: Environmental Systems Research Institute, Inc. (ESRI) ArcGIS 8.3, ArcInfo software, Adobe Photoshop CS, Illustrator CS, and Acrobat 6.0.

USGS map quandrangle boundaries with names and unique identifiers for the 1:24,000 (7.5 minute) quadrangles. Additional attributes provide unique identifiers and hierarchical relationships between these quadrangles and the enclosing 1:100,000 (30 x 60 minute) and 1:250,000 (1 x 2 degree) quadrangles.

FAF domestic region level datasets and products provide information for states, state portions of large metropolitan areas, and remainders of states. Metropolitan areas consist of Metropolitan Statistical Areas or Consolidated Statistical Areas as defined by the Office of Management and Budget. When a metropolitan area is entirely within a state or when a state's portion of a multi-state metropolitan area is large enough to support the sampling procedures in the Commodity Flow Survey, the area becomes a separate FAF region. Small single-state metropolitan areas and small portions of a multi-state metropolitan area are part of the State or Remainder of State. FAF has two metropolitan areas that are each divided into three FAF regions, four that are each divided into two FAF regions, and several that have small pieces combined with States or Remainders of States.

© United States Department of Transportation, Federal Highway Administration. For more information, see the site http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm This layer is sourced from maps.bts.dot.gov.

The spatial component of the FAF network is derived from National Highway System Version 2009.11 and contains state primary and secondary roads, National Highway System (NHS), National Network (NN) and several intermodal connectors as appropriate for the freight network modeling. The network consists of over 447,808 miles of equivalent road mileage. The data set covers the 48 contiguous States plus the District of Columbia, Alaska, and Hawaii. The nominal scale of the data set is 1:100,000 with a maximal positional error of ±80 meters.

© ederal Highway Administration Office of Freight Management and Operations and the Battelle Memorial Institute, Columbus, OH

Context

I needed this dataset to map some countries in the analysis: Advanced Global Warming Analysis with Plotly. Feel free to use this mapping for whatever cool analysis you're doing. :)

Content

• name - Country name in english
• alpha-2 - ISO code formed of 2 letters
• alpha-2 - ISO code formed of 3 letters (use this in your plotly maps ;) )
• country code - unique
• region - the continent of provenience
• sub-region - subcontinent
• intermediate region
• codes for region/ subregion/ intermediate region

Acknowledgements

Dataset was taken from lukes on GitHub: https://github.com/lukes/ISO-3166-Countries-with-Regional-Codes/blob/master/all/all.csv. I made only some small changes to the country names to mach my needs in the dataset (eg. United States of America transformed in United States).

USGS developed The National Map Gazetteer as the Federal and national standard (ANSI INCITS 446-2008) for geographic nomenclature based on the Geographic Names Information System (GNIS). The National Map Gazetteer contains information about physical and cultural geographic features, geographic areas, and locational entities that are generally recognizable and locatable by name (have achieved some landmark status) and are of interest to any level of government or to the public for any purpose that would lead to the representation of the feature in printed or electronic maps and/or geographic information systems. The dataset includes features of all types in the United States, its associated areas, and Antarctica, current and historical, but not including roads and highways. The dataset holds the federally recognized name of each feature and defines the feature location by state, county, USGS topographic map, and geographic coordinates. Other attributes include names or spellings other than the official name, feature classification, and historical and descriptive information. The dataset assigns a unique, permanent feature identifier, the Feature ID, as a standard Federal key for accessing, integrating, or reconciling feature data from multiple data sets. This dataset is a flat model, establishing no relationships between features, such as hierarchical, spatial, jurisdictional, organizational, administrative, or in any other manner. As an integral part of The National Map, the Gazetteer collects data from a broad program of partnerships with federal, state, and local government agencies and other authorized contributors. The Gazetteer provides data to all levels of government and to the public, as well as to numerous applications through a web query site, web map, feature and XML services, file download services, and customized files upon request. The National Map download client allows free downloads of public domain geographic names data by state in a pipe-delimited text format. For additional information on the GNIS, go to http://nationalmap.gov/gnis.html.

This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Point Reyes map area, California. The vector data file is included in "Contours_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. 10-m interval contours of the Offshore of Point Reyes map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

NERC is an international regulatory authority that works to improve the reliability of the bulk power system in North America. NERC works with many different regional entities to improve the coordination and supply of electricity. This data set of vector layer of polygons represents the boundaries of the regional and subregional entities associated with NERC

Analysis of ‘Country Mapping - ISO, Continent, Region’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/andradaolteanu/country-mapping-iso-continent-region on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Context

I needed this dataset to map some countries in the analysis: Advanced Global Warming Analysis with Plotly. Feel free to use this mapping for whatever cool analysis you're doing. :)

Content

• name - Country name in english
• alpha-2 - ISO code formed of 2 letters
• alpha-2 - ISO code formed of 3 letters (use this in your plotly maps ;) )
• country code - unique
• region - the continent of provenience
• sub-region - subcontinent
• intermediate region
• codes for region/ subregion/ intermediate region

Acknowledgements

Dataset was taken from lukes on GitHub: https://github.com/lukes/ISO-3166-Countries-with-Regional-Codes/blob/master/all/all.csv. I made only some small changes to the country names to mach my needs in the dataset (eg. United States of America transformed in United States).

--- Original source retains full ownership of the source dataset ---

Northeastern United States State Boundary data are intended for geographic display of state boundaries at statewide and regional levels. Use it to map and label states on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

Resident Population in the Midwest Census Region was 69596.58400 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, Resident Population in the Midwest Census Region reached a record high of 69596.58400 in January of 2024 and a record low of 26359.00000 in January of 1900. Trading Economics provides the current actual value, an historical data chart and related indicators for Resident Population in the Midwest Census Region - last updated from the United States Federal Reserve on July of 2025.

The locations of principal faults and structural zones that may influence ground-water flow were compiled in support of a three-dimensional ground-water model for the Death Valley regional flow system (DVRFS), which covers 80,000 square km in southwestern Nevada and southeastern California. Faults include Neogene extensional and strike-slip faults and pre-Tertiary thrust faults. Emphasis was given to characteristics of faults and deformed zones that may have a high potential for influencing hydraulic conductivity. These include: (1) faulting that results in the juxtaposition of stratigraphic units with contrasting hydrologic properties, which may cause ground-water discharge and other perturbations in the flow system; (2) special physical characteristics of the fault zones, such as brecciation and fracturing, that may cause specific parts of the zone to act either as conduits or as barriers to fluid flow; (3) the presence of a variety of lithologies whose physical and deformational characteristics may serve to impede or enhance flow in fault zones; (4) orientation of a fault with respect to the present-day stress field, possibly influencing hydraulic conductivity along the fault zone; and (5) faults that have been active in late Pleistocene or Holocene time and areas of contemporary seismicity, which may be associated with enhanced permeabilities. The faults shown on maps A and B are largely from Workman and others (in press), and fit one or more of the following criteria: (1) faults that are more than 10 km in map length; (2) faults with more than 500 m of displacement; and (3) faults in sets that define a significant structural fabric that characterizes a particular domain of the DVRFS. The following fault types are shown: Neogene normal, Neogene strike-slip, Neogene low-angle normal, pre-Tertiary thrust, and structural boundaries of Miocene calderas. We have highlighted faults that have late Pleistocene to Holocene displacement (Piety, 1996). Areas of thick Neogene basin-fill deposits (thicknesses 1-2 km, 2-3 km, and >3 km) are shown on map A, based on gravity anomalies and depth-to-basement modeling by Blakely and others (1999). We have interpreted the positions of faults in the subsurface, generally following the interpretations of Blakely and others (1999). Where geophysical constraints are not present, the faults beneath late Tertiary and Quaternary cover have been extended based on geologic reasoning. Nearly all of these concealed faults are shown with continuous solid lines on maps A and B, in order to provide continuous structures for incorporation into the hydrogeologic framework model (HFM). Map A also shows the potentiometric surface, regional springs (25-35 degrees Celsius, D'Agnese and others, 1997), and cold springs (Turner and others, 1996).