Metropolitan DivisionsThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Metropolitan Divisions within the United States. According to the USCB, "Metropolitan Divisions subdivide a Metropolitan Statistical Area (MSA) containing a single core urban area that has a population of at least 2.5 million to form smaller groupings of counties or equivalent entities. Not all MSAs with urban areas of this size will contain Metropolitan Divisions. Not all MSAs with urban areas of this size will contain Metropolitan Divisions. Metropolitan Division are defined by the Office of Management and Budget (OMB) and consist of one or more main counties or equivalent entities that represent an employment center or centers, plus adjacent counties associated with the main county or counties through commuting ties."Nassau County-Suffolk County, NY Metro Division & New Brunswick-Lakewood, NJ Metro DivisionData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Metropolitan Divisions) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 83 (Series Information for Metropolitan Division National TIGER/Line Shapefiles, Current)OGC API Features Link: (Metropolitan Divisions - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: Geographic LevelsFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Metropolitan Divisions subdivide a Metropolitan Statistical Area containing a single core urban area that has a population of at least 2.5 million to form smaller groupings of counties or equivalent entities. Not all Metropolitan Statistical Areas with urban areas of this size will contain Metropolitan Divisions. Metropolitan Division are defined by the Office of Management and Budget (OMB) and consist of one or more main counties or equivalent entities that represent an employment center or centers, plus adjacent counties associated with the main county or counties through commuting ties. Because Metropolitan Divisions represent subdivisions of larger Metropolitan Statistical Areas, it is not appropriate to rank or compare Metropolitan Divisions with Metropolitan and Micropolitan Statistical Areas. The Metropolitan Divisions boundaries are those defined by OMB based on the 2010 Census, published in 2013, and updated in 2017.

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. Metropolitan and Micropolitan Statistical Areas are together termed Core Based Statistical Areas (CBSAs) and are defined by the Office of Management and Budget (OMB) and consist of the county or counties or equivalent entities associated with at least one urban core (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties containing the core. Categories of CBSAs are: Metropolitan Statistical Areas, based on urbanized areas of 50,000 or more population, and Micropolitan Statistical Areas, based on urban clusters of at least 10,000 population but less than 50,000 population. The CBSAs for the 2010 Census are those defined by OMB and published in December 2009.

© The United States CBSA Boundaries files were compiled from a variety of sources including the US Bureau of the Census, and data supplied by individual states. This layer is sourced from maps.bts.dot.gov.

Provides regional identifiers for county based regions of various types. These can be combined with other datasets for visualization, mapping, analyses, and aggregation. These regions include:Metropolitan Statistical Areas (Current): MSAs as defined by US OMB in 2023Metropolitan Statistical Areas (2010s): MSAs as defined by US OMB in 2013Metropolitan Statistical Areas (2000s): MSAs as defined by US OMB in 2003Region: Three broad regions in North Carolina (Eastern, Western, Central)Council of GovernmentsProsperity Zones: NC Department of Commerce Prosperity ZonesNCDOT Divisions: NC Dept. of Transportation DivisionsNCDOT Districts (within Divisions)Metro Regions: Identifies Triangle, Triad, Charlotte, All Other Metros, & Non-MetropolitanUrban/Rural defined by:NC Rural Center (Urban, Regional/Suburban, Rural) - 2020 Census designations2010 Census (Urban = Counties with 50% or more population living in urban areas in 2010)2010 Census Urbanized (Urban = Counties with 50% or more of the population living in urbanized areas in 2010 (50,000+ sized urban area))Municipal Population - State Demographer (Urban = counties with 50% or more of the population living in a municipality as of July 1, 2019)Isserman Urban-Rural Density Typology

This map contains state and county boundaries for the United States for every decennial census from 1790-2020. Original data is from the NHGIS and was simplified to reduce file size using mapshaper.org

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

The 1998 Dress Rehearsal was conducted as a prelude to the United States Census of Population and Housing, 2000, in the following locations: (1) Columbia, South Carolina, and surrounding areas, including the town of Irmo and the counties of Chester, Chesterfield, Darlington, Fairfield, Kershaw, Lancaster, Lee, Marlboro, Newberry, Richland, and Union, (2) Sacramento, California, and (3) Menominee County, Wisconsin, including the Menominee American Indian Reservation. This collection contains map files showing various levels of geography (in the form of Census Tract Outline Maps, Voting District/State Legislative District Outline Maps, and County Block Maps), TIGER/Line digital files, and Corner Point files for the Census 2000 Dress Rehearsal sites. The Corner Point data files contain the bounding latitude and longitude coordinates for each individual map sheet of the 1998 Dress Rehearsal Public Law (P.L.) 94-171 map products. These files include a sheet identifier, minimum and maximum longitude, minimum and maximum latitude, and the map scale (integer value) for each map sheet. The latitude and longitude coordinates are in decimal degrees and expressed as integer values with six implied decimal places. There is a separate Corner Point File for each of the three map types: County Block Map, Census Tract Outline Map, and Voting District/State Legislative District Outline Map. Each of the three map file types is provided in two formats: Portable Document Format (PDF), for viewing, and Hewlett-Packard Graphics Language (HP-GL) format, for plotting. The County Block Maps show the greatest detail and the most complete set of geographic information of all the maps. These large-scale maps depict the smallest geographic entities for which the Census Bureau presents data -- the census blocks -- by displaying the features that delineate them and the numbers that identify them. These maps show the boundaries, names, and codes for American Indian/Alaska Native areas, county subdivisions, places, census tracts, and, for this series, the geographic entities that the states delineated in Phase 2, Voting District Project, of the Redistricting Data Program. The HP-GL version of the County Block Maps is broken down into index maps and map sheets. The map sheets cover a small area, and the index maps are composed of multiple map sheets, showing the entire area. The intent of the County Block Map series is to provide a map for each county on the smallest possible number of map sheets at the maximum practical scale, dependent on the area size of the county and the density of the block pattern. The latter affects the display of block numbers and feature identifiers. The Census Tract Outline Maps show the boundaries and numbers of census tracts, and name the features underlying the boundaries. These maps also show the boundaries and names of counties, county subdivisions, and places. They identify census tracts in relation to governmental unit boundaries. The mapping unit is the county. These large-format maps are produced to support the P.L. 94-171 program and all other 1998 Dress Rehearsal data tabulations. The Voting District/State Legislative District Outline Maps show the boundaries and codes for voting districts as delineated by the states in Phase 2, Voting District Project, of the Redistricting Data Program. The features underlying the voting district boundaries are shown, as well as the names of these features. Additionally, for states that submit the information, these maps show the boundaries and codes for state legislative districts and their underlying features. These maps also show the boundaries of and names of American Indian/Alaska Native areas, counties, county subdivisions, and places. The scale of the district maps is optimized to keep the number of map sheets for each area to a minimum, but the scale and number of map sheets will vary by the area size of the county and the voting districts and state legislative districts delineated by the states. The Census 2000 Dress Rehearsal TIGER/Line Files consist of line segments representing physical features and governmental and statistical boundaries. The files contain information distributed over a series of record types for the spatial objects of a county. These TIGER/Line Files are an extract of selected geographic and cartographic information from the Census TIGER (Topological

The Metropolitan Planning Organizations (MPO) dataset was compiled on July 07, 2025 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This dataset contains the geographic boundaries of Metropolitan Planning Organizations. It provides users with transportation planning locations, sizes and names and is intended for metropolitan area multimodal transportation planning and programming. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529038

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

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. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are based on those as of January 1, 2022, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

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

Incorporated Places are those reported to the Census Bureau as legally in existence as of the latest Boundary and Annexation Survey (BAS), under the laws of their respective states. An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division, which generally is created to provide services or administer an area without regard, necessarily, to population. Places always are within a single state or equivalent entity, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough but can have other legal descriptions. For Census Bureau data tabulation and presentation purposes, incorporated places exclude:

1) The boroughs in Alaska (treated as statistical equivalents of counties).

2) Towns in the New England states, New York, and Wisconsin (treated as MCDs).

3) The boroughs in New York (treated as MCDs).

The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

The Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.Terrestrial and Freshwater Data• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels which comprise the spatial features of CPAD, generally corresponding to ownership boundaries. • The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity. Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership. •The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such, boundaries represented within it may not align with other data sources. • Numerous datasets representing designated boundaries for entities such as National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas, and others, were downloaded from publicly available sources, typically hosted by the managing agency.Methodology1.CPAD and CCED represent the most accurate location and ownership information for parcels in California which contribute to the preservation of open space and cultural and biological resources.2. Superunits are collections of parcels (Holdings) within CPAD which share a name, manager, and access policy. Most Superunits are also managed with a generally consistent strategy for biodiversity conservation. Examples of Superunits include Yosemite National Park, Giant Sequoia National Monument, and Anza-Borrego Desert State Park. 3. Some Superunits, such as those owned and managed by the Bureau of Land Management, U.S. Forest Service, or National Park Service , are intersected by one or more designations, each of which may have a distinct management emphasis with regards to biodiversity. Examples of such designations are Wilderness Areas, Wild and Scenic Rivers, or National Monuments.4. CPAD Superunits and CCED easements were intersected with all designation boundary files to create the operative spatial units for conservation analysis, henceforth 'Conservation Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit. 5. Each Conservation Unit was intersected with the PAD-US dataset in order to determine the management emphasis with respect to biodiversity, i.e., the GAP code. Because PAD-US is national in scope and not specifically parcel aligned with California assessors' surveys, a direct spatial extraction of GAP codes from PAD-US would leave tens of thousands of GAP code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single GAP code was uniformly assigned that code. Additionally, the total area of GAP codes 1 and 2 were summed for the remaining uncoded Conservation Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2. 6.Subsequent to this stage of analysis, certain Conservation Units remained uncoded, either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset. 7.These uncoded Conservation Units were then broken down into their constituent, finer resolution Holdings, which were then analyzed according to the above workflow. 8. Areas remaining uncoded following the two-step process of coding at the Superunit and then Holding levels were assigned a GAP code of 4. This is consistent with the definition of GAP Code 4: areas unknown to have a biodiversity management focus. 9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.10. PAD-US is a principal data source for understanding the spatial distribution of GAP coded lands, but it is national in scope, and may not always be the most current source of data with respect to California holdings. GreenInfo Network, which develops and maintains the CPAD and CCED datasets, has taken a lead role in establishing communication with land stewards across California in order to make GAP attribution of these lands as current and accurate as possible. The tabular attribution of these datasets is analyzed in addition to PAD-US in order to understand whether a holding may be considered conserved. Tracking Conserved Areas The total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing improvements in our understanding of existing biodiversity conservation efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data. CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review.The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

This web map created by the Colorado Governor's Office of Information Technology GIS team, serves as a basemap specific to the state of Colorado. The basemap includes general layers such as counties, municipalities, roads, waterbodies, state parks, national forests, national wilderness areas, and trails.Layers:Layer descriptions and sources can be found below. Layers have been modified to only represent features within Colorado and are not up to date. Layers last updated February 23, 2023. Colorado State Extent: Description: “This layer provides generalized boundaries for the 50 States and the District of Columbia.” Notes: This layer was filtered to only include the State of ColoradoSource: Esri Living Atlas USA States Generalized Boundaries Feature LayerState Wildlife Areas:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state wildlife areas layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer hosted in ArcGIS Online Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerMunicipal Boundaries:Description: "Boundaries data from the State Demography Office of Colorado Municipalities provided by the Department of Local Affairs (DOLA)"Source: Colorado Information Marketplace Municipal Boundaries in ColoradoCounties:Description: “This layer presents the USA 2020 Census County (or County Equivalent) boundaries of the United States in the 50 states and the District of Columbia. It is updated annually as County (or County Equivalent) boundaries change. The geography is sources from US Census Bureau 2020 TIGER FGDB (National Sub-State) and edited using TIGER Hydrology to add a detailed coastline for cartographic purposes. Geography last updated May 2022.” Notes: This layer was filtered to only include counties in the State of ColoradoSource: Esri USA Census Counties Feature LayerInterstates:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: Interstates are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointU.S. Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: U.S. Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointState Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: State Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointMajor Roads:Description: Authoritative data from the Colorado Department of Transportation representing major roads Source: Colorado Department of Transportation Major Roads REST EndpointLocal Roads:Description: Authoritative data from the Colorado Department of Transportation representing local roads Source: Colorado Department of Transportation Local Roads REST EndpointRail Lines:Description: Authoritative data from the Colorado Department of Transportation representing rail lines Source: Colorado Department of Transportation Rail Lines REST EndpointCOTREX Trails:Description: “The Colorado Trail System, now titled the Colorado Trail Explorer (COTREX), endeavors to map every trail in the state of Colorado. Currently their are nearly 40,000 miles of trails mapped. Trails come from a variety of sources (USFS, BLM, local parks & recreation departments, local governments). Responsibility for accuracy of the data rests with the source.These data were last updated on 2/5/2019” Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerNHD Waterbodies:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include waterbodies in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerNHD Flowlines:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include flowline features in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerState Parks:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state parks layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerDenver Parks:Description: "This dataset should be used as a reference to locate parks, golf courses, and recreation centers managed by the Department of Parks and Recreation in the City and County of Denver. Data is based on parcel ownership and does not include other areas maintained by the department such as medians and parkways. The data should be used for planning and design purposes and cartographic purposes only."Source: City and County of Denver Parks REST EndpointNational Wilderness Areas:Description: “A parcel of Forest Service land congressionally designated as wilderness such as National Wilderness Area.”Notes: This layer was filtered to only include National Wilderness Areas in the State of ColoradoSource: United States Department of Agriculture National Wilderness Areas REST EndpointNational Forests: Description: “A depiction of the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with subsequent Executive Orders, Proclamations, Public Laws, Public Land Orders, Secretary of Agriculture Orders, and Secretary of Interior Orders creating modifications thereto, along with lands added to the NFS which have taken on the status of 'reserved from the public domain' under the General Exchange Act. The following area types are included: National Forest, Experimental Area, Experimental Forest, Experimental Range, Land Utilization Project, National Grassland, Purchase Unit, and Special Management Area.”Notes: This layer was filtered to only include National Forests in the State of ColoradoSource: United States Department of Agriculture Original Proclaimed National Forests REST Endpoint

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Ventura map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Monterey Canyon and Vicinity map area data layers. Data layers are symbolized as shown on the associated map sheets.

The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentationMunicipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are mostly as of January 1, 2013, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS). However, some changes made after January 2013, including the addition and deletion of counties, are included.

This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

This edition of the Congressional District Atlas contains maps and tables for the 105th Congress of the United States. The maps show the boundaries of each congressional district. Tables listing the jurisdictions that are completely or partially within each congressional district are included. For states with only one congressional district, a state map is included but there is no table. The maps and tables are designed for page size (8 1/2 x 11) printed output. Although the map images use co lor for enhanced viewing, the design allows for acceptable black and white desktop printing. For more information, see the sections on Maps and Tables. Background: 103rd and 104th Congress Following the 1990 decennial census, most states redistricted for the 103rd Congress based upon the apportionment of the seats for the U.S. House of Representatives and the most recent decennial census data. For the 104th Congress, six states redistricted or through court action had either plans revised or redrawn. These states were Georgia, Louisiana, Maine, Minnesota, South Carolina and Virginia. The 104th Congress began January 1995 and continued through the beginning of January 1997. 105th Congress The 105th Congress began January 5, 1997 and continues through the beginning of January 1999. For the 105th Congress, Florida, Georgia, Kentucky, Louisiana, and Texas had new or revised congressional district plans. The Census Bureau retabulated demographic data from the 1990 census to accommodate any congressional district boundary changes from the previous Congress. This data is available on a separate CD-ROM from the Census Bureau Customer Service Branch (301) 457-4100. The 105th Congressional District Atlas CD-ROM provides maps showing the boundaries of the congressional districts of the 105th Congress. To meet the data needs for the 105th Congress, the Census Bureau designed this product on CD-ROM for all states. It contains maps and related entity tables in Adobe. 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.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a main map that shows fifteen condensed maps of geostatistical units used by the 1951 Census. The main map shows the census divisions as used in that census to gather, compile and publish many of the results of the censuses of Canada. Census divisions normally correspond to counties, but the Dominion Bureau of Statistics (which is now Statistics Canada) had to create equivalent units for counties in each of Newfoundland, Manitoba, Saskatchewan, Alberta and British Columbia. The main map has a table listing all of the census divisions. Around the main map are individual maps for each of the 15 census metropolitan areas as used in the 1951 Census. Each of these small maps shows the component municipalities in the metropolitan area and also shows the built-up area. These small maps are all at the same scale, which is about 1:650 000.