The North Carolina State Demographer data platform houses the latest data produced by the Office of the State Demographer. The platform allows users to create visualizations, download full (or partial) datasets, and create maps. Registered users can save their visualizations and be notified of dataset updates. This new platform is a subdomain of OSBM’s Log In to North Carolina (LINC) – a service containing over 900 data items including items pertaining to population, labor force, education, transportation, etc. LINC includes topline statistics from the State Demographer’s population estimates and projections while the North Carolina State Demographer data platform includes more detailed datasets for users requiring more detailed demographic information.

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

This ArcGIS Map Package contains information on brook trout occupancy in the southern portion of the brook trout range (PA and south). Fish sample data from a number of state and federal agencies/organizations were used to define patches for brook trout as groups of occupied contiguous catchment polygons from the National Hydrography Dataset Plus Version 1 (NHDPlusV1) catchment GIS layer. After defining patches, NHDPlusV1 catchments were assigned occupancy codes. Then state and federal agencies reviewed patches and codes to verify data accuracy. A similar effort is currently being conducted by the Eastern Brook Trout Joint Venture to develop occupancy data for the remainder of the brook trout range including states of New York, Maine, New Hampshire, Connecticut, Vermont, Massachusetts, Rhode Island, and Ohio. This ArcGIS Map Package contains data for the entire southern portion of the brook trout range with preset symbology that displays brook trout occupancy. The Map Package also includes the same information clipped into seperate layers for each state. State information is provided for the convenience of users that are interested in data for only a particular state. Additional layers displaying state boundaries, quadrangle maps, and the brook trout range are also included as spatial references.

The 2016 cartographic boundary KMLs 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 records in this file allow users to map the parts of Urban Areas that overlap a particular county.

After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes.

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 as of January 1, 2010.

The 2015 cartographic boundary KMLs 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 records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. 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, 2010.

Geographic information systems (GIS) can be used to map mosquito larval and adult habitats and human populations at risk for mosquito exposure and possible arbovirus transmission. Along with traditional methods of surveillance-based targeted mosquito control, GIS can help simplify and target efforts during routine surveillance and post-disaster (e.g., hurricane-related flooding) to protect emergency workers and public health. A practical method for prioritizing areas for emergency mosquito control has been developed and is described here. North Carolina (NC) One Map was used to identify state-level data layers of interest based on human population distribution and mosquito habitat in Brunswick, Columbus, Onslow, and Robeson Counties in eastern NC. Relevant data layers were included to create mosquito control treatment areas for targeted control and an 18-step protocol for map development is discussed. This protocol is expected to help state, territorial, tribal, and/or local public health officials and associated mosquito control programs efficiently create treatment area maps to improve strategic planning in advance of a disaster. This protocol may be applied to any NC county and beyond, thereby increasing local disaster preparedness.

This data set provides four feature classes. The base feature class is called BlockGroups_bg and isn't generalized. The weighted centroids feature class is called BlockGroups_bg_cent. The centroids are weighted by the U.S. Block Centroids population distribution. Use the weighted centroids in report aggregation and spatial overlay operations. The BlockGroups_bg and BlockGroups_bg_cent feature classes contain all the attributes. There are two generalized boundaries feature classes and called: BlockGroups_bg_gen2, and BlockGroups_bg_gen3. Use the generalized boundaries when creating study areas.

This data set provides four feature classes. The base feature class is called CensusTracts_tr and isn't generalized. The weighted centroids feature class is called CensusTracts_tr_cent. The centroids are weighted by the U.S. Block Centroids population distribution. Use the weighted centroids in report aggregation and spatial overlay operations. The CensusTracts_tr and CensusTracts_tr_cent feature classes contain all the attributes. There are two generalized boundaries feature classes and called: CensusTracts_tr_gen2, and CensusTracts_tr_gen3. Use the generalized boundaries when creating study areas.

In the face of sea level rise and as climate change conditions increase the frequency and intensity of tropical storms along the north-Atlantic Coast, coastal areas will become increasingly vulnerable to storm damage, and the decline of already-threatened species could be exacerbated. Predictions about response of coastal birds to effects of hurricanes will be essential for anticipating and countering environmental impacts. This project will assess coastal bird populations, behavior, and nesting in Hurricane Sandy-impacted North Carolina barrier islands. The project comprises three components: 1) ground-based and airborne lidar analyses to examine site specific selection criteria of coastal birds; 2) NWI classification habitat mapping of DOI lands to examine habitat change associated with Hurricane Sandy, particularly in relation to coastal bird habitat; and 3) a GIS-based synthesis of how patterns of coastal bird distribution and abundance and their habitats have been shaped by storms such as Hurricane Sandy, coastal development, population density, and shoreline management over the past century. We will trace historic changes to shorebird populations and habitats in coastal North Carolina over the past century. Using historic maps and contemporary imagery, the study will quantify changes in shorebird populations and their habitats resulting from periodic storms such as Hurricane Sandy in 2012, to development projects such as the Intracoastal Waterway early in the last century, as well as more recent urban development. We will synthesize existing data on the distribution and abundance of shorebirds in North Carolina and changes in habitats related to storms, coastal development, inlet modifications, and shoreline erosion to give us a better understanding of historic trends for shorebirds and their coastal habitats. Historic data on the distribution and abundance of shorebirds are available from a variety of sources and include bird species identification, location, activity, habitat, and band data. Habitat maps of federal lands in the study area will be created using National Wetlands Inventory mapping standards to assess storm impacts on available nesting habitat. Ground-based LIDAR and high-accuracy GPS data will be collected to develop methods to estimate shorebird nest elevation and microtopography to make predictions about nest site selection and success. Microtopography information collected from lidar data in the area immediately surrounding nest site locations will be used to analyze site specific nesting habitat selection criteria related to topography, substrate (coarseness of sand or cobble), and vegetation cover. The data will be used in future models to assess storm impacts on nest locations, predict long-term population impacts, and influence landscape-scale habitat management strategies that might lessen future impacts of hurricanes on coastal birds and lead to better restoration alternatives.

In the face of sea level rise and as climate change conditions increase the frequency and intensity of tropical storms along the north-Atlantic Coast, coastal areas will become increasingly vulnerable to storm damage, and the decline of already-threatened species could be exacerbated. Predictions about response of coastal birds to effects of hurricanes will be essential for anticipating and countering environmental impacts. This project will assess coastal bird populations, behavior, and nesting in Hurricane Sandy-impacted North Carolina barrier islands. The project comprises three components: 1) ground-based and airborne lidar analyses to examine site specific selection criteria of coastal birds; 2) NWI classification habitat mapping of DOI lands to examine habitat change associated with Hurricane Sandy, particularly in relation to coastal bird habitat; and 3) a GIS-based synthesis of how patterns of coastal bird distribution and abundance and their habitats have been shaped by storms such as Hurricane Sandy, coastal development, population density, and shoreline management over the past century. We will trace historic changes to shorebird populations and habitats in coastal North Carolina over the past century. Using historic maps and contemporary imagery, the study will quantify changes in shorebird populations and their habitats resulting from periodic storms such as Hurricane Sandy in 2012, to development projects such as the Intracoastal Waterway early in the last century, as well as more recent urban development. We will synthesize existing data on the distribution and abundance of shorebirds in North Carolina and changes in habitats related to storms, coastal development, inlet modifications, and shoreline erosion to give us a better understanding of historic trends for shorebirds and their coastal habitats. Historic data on the distribution and abundance of shorebirds are available from a variety of sources and include bird species identification, location, activity, habitat, and band data. Habitat maps of federal lands in the study area will be created using National Wetlands Inventory mapping standards to assess storm impacts on available nesting habitat. Ground-based LIDAR and high-accuracy GPS data will be collected to develop methods to estimate shorebird nest elevation and microtopography to make predictions about nest site selection and success. Microtopography information collected from lidar data in the area immediately surrounding nest site locations will be used to analyze site specific nesting habitat selection criteria related to topography, substrate (coarseness of sand or cobble), and vegetation cover. The data will be used in future models to assess storm impacts on nest locations, predict long-term population impacts, and influence landscape-scale habitat management strategies that might lessen future impacts of hurricanes on coastal birds and lead to better restoration alternatives.

The 2019 cartographic boundary KMLs 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 records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. 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 as of January 1, 2010.