This resource is a member of a series. 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) System (MTS). The MTS 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 TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state but may extend across county and county subdivision boundaries. An incorporated place is usually a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs are often defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2024, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2024 BAS as well.

The 2022 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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

The population and housing unit estimates are released on a flow basis throughout each year. Each new series of data (called vintages) incorporates the latest administrative record data, geographic boundaries, and methodology. Therefore, the entire time series of estimates beginning with the date of the most recent decennial census is revised annually, and estimates from different vintages of data may not be consistent across geography and characteristics detail.
When multiple vintages of data are available, the most recent vintage is the preferred data.

The vintage year (e.g., V2021) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified.

Additional estimates files may also be accessed via the Census Bureau application programming interface (API).

Additional information on the Census Bureau's Population Estimates Program (PEP) is available on the PEP's homepage Census Bureau's Population Estimates Program.

Notes: For vintage 2019: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. All geographic boundaries for the 2019 population estimates are as of January 1, 2019.

For vintage 2021: The estimates are developed from a base that incorporates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates. The estimates are developed from a base that incorporates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates.

For population estimates methodology statements, see http://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html">http://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html.

Sources: U.S. Census Bureau, Population Division Annual Estimates of the Resident Population for Counties in Pennsylvania: April 1, 2010 to July 1, 2019 (CO-EST2019-ANNRES-42) - Release Date: March 2020

Annual Estimates of the Resident Population for Counties in Pennsylvania: April 1, 2020 to July 1, 2021 (CO-EST2021-POP-42) - Release Date: March 2022

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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This resource is a member of a series. 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) System (MTS). The MTS 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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined because of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard Census Bureau geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous.

Exercise Only

This Web Map provides the foundation for a Situational Awareness application for Wilkes Barre, PA that can be used by emergency management staff to identify the impact of a flood on public infrastructure and human populations. The Situational Awareness Viewer is a configuration of Web AppBuilder for ArcGIS that can be used to analyze the impact to people and places within an incident area. The application can be configured within ArcGIS Online or deployed on-premises.This web map is based on a flood hazard assessment of Luzerne County, PA.

Populations along the Susquehanna River Basin, which includes areas of New York, Pennsylvania, and Maryland, reside in one of the most flood prone areas in the United States. Major floods have occurred about every 15 years and flash floods are a consistent threat. Luzerne County, PA communities have long histories of flood emergencies, as the river bisects the county and tributaries are spread throughout. Based on the existing models and historical data, flood protection and management are already high priorities. However, rapidly changing demographics and unpredictable environmental conditions expose the need for more detailed and constantly evolving models for emergency preparedness and response.

This Hazard Analysis of Luzerne County augments the existing flood hazard area models with two additional critical factors for consideration. First, areas with vulnerable populations are identified using the Agency for Toxic Substances and Disease Registry's (ATSDR) 2014 Social Vulnerability Index. This data model incorporates a variety of socioeconomic indicators as part of an analytical matrix that measures the potential resilience of communities facing emergency conditions. All tracts are given a percentile rank (0= Lowest Vulnerability to 1=Highest Vulnerability) for fifteen variables. Four major theme rankings (Socioeconomic, Housing Composition and Disability, Minority Status & Language, and Housing & Transportation) are compiled as a sum of the variables for each theme. An overall percentile ranking is determined for each tract. For the purposes of this study, Natural Breaks classification was used to group tracts with similar overall tract scores. All tracts with overall ratings above .7372 (top 2 of 5 classes) are defined as “High Vulnerability”, with populations that are at the highest risk during crisis level events of any kind. In addition, critical infrastructure locations are identified and mapped.

Given the incalculable value of human life and importance of essential infrastructure to response and recovery, both the “High Vulnerability” areas and critical emergency locations layers are intersected with a layer of flood hazard areas from the FEMA Flood Map Service Center. The Special Flood Hazard Areas (SFHA) that intersect with High Vulnerability areas are defined as “High Hazard Areas”.

The United States National Grid (USNG) for Luzerne County is also available as a comparative layer.

About the SFHA

The land area covered by the floodwaters of the base flood is the Special Flood Hazard Area (SFHA) on NFIP maps. The SFHA is the area where the National Flood Insurance Program's (NFIP's) floodplain management regulations must be enforced and the area where the mandatory purchase of flood insurance applies.

What is the SVI?

Social vulnerability refers to the resilience of communities when confronted by external stresses on human health, stresses such as natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The Agency for Toxic Substances and Disease Registry's (ATSDR) Social Vulnerability Index uses U.S. census variables at tract level to help local officials identify communities that may need support in preparing for hazards or recovering from disaster.

What is the USNG?

The United States National Grid (USNG) is a point reference system of grid references commonly used in the United States. It provides a nationally consistent language of location in a user-friendly format. It is similar in design to the national grid reference systems used throughout other nations.

Data Sources

US Homeland Infrastructure Foundation Level Data (HIFLD Open Data Portal)

Emergency Shelters Emergency Services Hospitals Fire Stations Police Stations Colleges and Universities Private Schools Public Schools

ATSDR 2014 Social Vulnerability Index (link)

FEMA Flood Map Service Center (link)

The United States National Grid (USNG) (link)

This EnviroAtlas dataset demonstrates the effect of changes in pollution concentration on local populations in 3974 block groups in Philadelphia, PA. The US EPA's Environmental Benefits Mapping and Analysis Program (BenMAP) was used to estimate the incidence of adverse health effects (i.e., mortality and morbidity) and associated monetary value that result from changes in pollution concentrations for Philadelphia City and County, PA, New Castle County, DE, Cecil County, MD, Camden County, NJ, Atlantic County, NJ, Gloucester County, NJ, Burlington County, NJ, Delaware County, PA, Bucks County, PA, Chester County, PA, and Montgomery County, PA. Incidence and value estimates for the block groups are calculated using i-Tree models (www.itreetools.org), local weather data, pollution data, and U.S. Census derived population data. This dataset was produced by the USDA Forest Service with support from The Davey Tree Expert Company to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

The 2015 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 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.

A common problem in applied research involves harmonizing geographic units across time or different levels of aggregation. We provide crosswalks that allow researchers i) to harmonize U.S. county boundaries over time across Census decades and ii) to generate congressional district level variables from county-level data. The crosswalks include an area-based approach as in Hornbeck (2010), as well as the new population-based methods from Ferrara, Testa, and Zhou (2021), which are based on granular sub-county population information. We also provide teaching material to demonstrate the utility of these new crosswalks.Reference:Ferrara, A., Testa, P.A., and Zhou, L. (2022) "New Area- and Population-based Geographic Crosswalks for U.S. Counties and Congressional Districts, 1790-2020", SSRN working paper: https://dx.doi.org/10.2139/ssrn.4019521

The PA Department of Conservation and Natural Resources (DCNR) and PA Game Commission (PGC) have teamed up to create an interactive map specifically for hunters. Collectively, State Forest Land and Gamelands comprise over 3.7 million acres of public forest open to hunting in Pennsylvania. Hunters can use this map to:View public forests open to hunting.Search hunting seasons and bag limits across different parts of the state.Display hunting hours (starting/ending times) across different parts of the state.Add personal GPS data to the map (waypoints and tracklogs).View different types of wildlife habitat across public forest lands, including mature oak forests, meadows, food plots, openings, winter thermal (coniferous) cover, and young aspen forest.See where recent timber harvests have occurred on public forest lands.Get deer management assistance program (DMAP) information for state forest lands.Add map layers associated with chronic wasting disease (CWD).Identify where bear check stations are located and get driving directions.Display the elk hunting zones and get information about them.Get the location of gated roads opened for hunters on public forest lands and when those gates will be opened.Analyze graphs and trends in antlerless/antlered deer harvests and antlerless license allocations from 2004 to the present.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 19006 (Huntingdon Valley, PA). Interactive charts load automatically as you scroll for improved performance.

COVID-19 Cases information is reported through the Pennsylvania State Department’s National Electronic Disease Surveillance System (PA-NEDSS). As new cases are passed to the Allegheny County Health Department they are investigated by case investigators. During investigation some cases which are initially determined by the State to be in the Allegheny County jurisdiction may change, which can account for differences between publication of the files on the number of cases, deaths and tests. Additionally, information is not always reported to the State in a timely manner, delays can range from days to weeks, which can also account for discrepancies between previous and current files. Test and Case information will be updated daily. This resource contains individuals who received a COVID-19 test and individuals whom are probable cases. Every day, these records are overwritten with updates. Each row in the data reflects a person that is tested, not tests that are conducted. People that are tested more than once will have their testing and case data updated using the following rules: Positive tests overwrite negative tests. Polymerase chain reaction (PCR) tests overwrite antibody or antigen (AG) tests. The first positive PCR test is never overwritten. Data collected from additional tests do not replace the first positive PCR test. Note: On April 4th 2022 the Pennsylvania Department of Health no longer required labs to report negative AG tests. Therefore aggregated counts that included AG tests have been removed from the Municipality/Neighborhood files going forward. Versions of this data up to this cut-off have been retained as archived files. Individual Test information is also updated daily. This resource contains the details and results of individual tests along with demographic information of the individual tested. Only PCR and AG tests are included. Every day, these records are overwritten with updates. This resource should be used to determine positivity rates. The remaining datasets provide statistics on death demographics. Demographic, municipality and neighborhood information for deaths are reported on a weekly schedule and are not included with individual cases or tests. This has been done to protect the privacy and security of individuals and their families in accordance with the Health Insurance Portability and Accountability Act (HIPAA). Municipality or City of Pittsburgh Neighborhood is based off the geocoded home address of the individual tested. Individuals whose home address is incomplete may not be in Allegheny County but whose temporary residency, work or other mitigating circumstance are determined to be in Allegheny County by the Pennsylvania Department of Health are counted as "Undefined". Since the start of the pandemic, the ACHD has mapped every day’s COVID tests, cases, and deaths to their Allegheny County municipality and neighborhood. Tests were mapped to patient address, and if this was not available, to the provider _location. This has recently resulted in apparent testing rates that exceeded the populations of various municipalities -- mostly those with healthcare providers. As this was brought to our attention, the health department and our data partners began researching and comparing methods to most accurately display the data. This has led us to leave those with missing home addresses off the map. Although these data will still appear in test, case and death counts, there will be over 20,000 fewer tests and almost 1000 fewer cases on the map. In addition to these map changes, we have identified specific health systems and laboratories that had data uploading errors that resulted in missing locations, and are working with them to correct these errors. Due to minor discrepancies in the Municipal boundary and the City of Pittsburgh Neighborhood files individuals whose City Neighborhood cannot be identified are be counted as “Undefined (Pittsburgh)”.

The Valley of the Shadow is an electronic archive of two communities in the American Civil War--Augusta County, Va. and Franklin Co., Pa. The Valley Web site includes searchable newspapers, geographic information systems data, maps, population;census data, agricultural census data, manufacturing census data, slaveowner census data, and tax records. The Valley Web site also contains letters and diaries, images, maps, church records, and military rosters. The Valley of the Shadow will be;published in CD-ROM version by W. W. Norton & Co. in three parts. The first part Web site focuses on the coming of the Civil War, the second on the Civil War battles and homefront, and the third part on Emancipation and Reconstruction after the;war. The Valley project is a University ofVirginia research project funded in part by the National Endowment of the Humanities.

DescriptionExercise OnlyA Situational Awareness application for Wilkes Barre, PA that can be used by emergency management staff to identify the impact of a flood on public infrastructure and human populations. The Situational Awareness Viewer is a configuration of Web AppBuilder for ArcGIS that can be used to analyze the impact to people and places within an incident area. The application can be configured within ArcGIS Online or deployed on-premises.This web map is based on a flood hazard assessment of Luzerne County, PA.Populations along the Susquehanna River Basin, which includes areas of New York, Pennsylvania, and Maryland, reside in one of the most flood prone areas in the United States. Major floods have occurred about every 15 years and flash floods are a consistent threat. Luzerne County, PA communities have long histories of flood emergencies, as the river bisects the county and tributaries are spread throughout. Based on the existing models and historical data, flood protection and management are already high priorities. However, rapidly changing demographics and unpredictable environmental conditions expose the need for more detailed and constantly evolving models for emergency preparedness and response.This Hazard Analysis of Luzerne County augments the existing flood hazard area models with two additional critical factors for consideration. First, areas with vulnerable populations are identified using the Agency for Toxic Substances and Disease Registry's (ATSDR) 2014 Social Vulnerability Index. This data model incorporates a variety of socioeconomic indicators as part of an analytical matrix that measures the potential resilience of communities facing emergency conditions. All tracts are given a percentile rank (0= Lowest Vulnerability to 1=Highest Vulnerability) for fifteen variables. Four major theme rankings (Socioeconomic, Housing Composition and Disability, Minority Status & Language, and Housing & Transportation) are compiled as a sum of the variables for each theme. An overall percentile ranking is determined for each tract. For the purposes of this study, Natural Breaks classification was used to group tracts with similar overall tract scores. All tracts with overall ratings above .7372 (top 2 of 5 classes) are defined as “High Vulnerability”, with populations that are at the highest risk during crisis level events of any kind. In addition, critical infrastructure locations are identified and mapped.Given the incalculable value of human life and importance of essential infrastructure to response and recovery, both the “High Vulnerability” areas and critical emergency locations layers are intersected with a layer of flood hazard areas from the FEMA Flood Map Service Center. The Special Flood Hazard Areas (SFHA) that intersect with High Vulnerability areas are defined as “High Hazard Areas”.The United States National Grid (USNG) for Luzerne County is also available as a comparative layer.About the SFHAThe land area covered by the floodwaters of the base flood is the Special Flood Hazard Area (SFHA) on NFIP maps. The SFHA is the area where the National Flood Insurance Program's (NFIP's) floodplain management regulations must be enforced and the area where the mandatory purchase of flood insurance applies.What is the SVI?Social vulnerability refers to the resilience of communities when confronted by external stresses on human health, stresses such as natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The Agency for Toxic Substances and Disease Registry's (ATSDR) Social Vulnerability Index uses U.S. census variables at tract level to help local officials identify communities that may need support in preparing for hazards or recovering from disaster.What is the USNG?The United States National Grid (USNG) is a point reference system of grid references commonly used in the United States. It provides a nationally consistent language of location in a user-friendly format. It is similar in design to the national grid reference systems used throughout other nations.Data SourcesUS Homeland Infrastructure Foundation Level Data (HIFLD Open Data Portal)Emergency SheltersEmergency ServicesHospitalsFire StationsPolice StationsColleges and UniversitiesPrivate SchoolsPublic SchoolsATSDR 2014 Social Vulnerability Index (link)FEMA Flood Map Service Center (link)The United States National Grid (USNG) (link)

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.

This GIS layer delineates the spatial boundaries of Important Bird Areas (IBAs), which are sites recognized as globally significant for the conservation of bird populations within York County, Pennsylvania. The dataset includes polygon features representing IBAs identified through standardized criteria developed by BirdLife International, including species vulnerability, population thresholds, and habitat significance. Each feature contains associated attributes such as site name, location, area, key species, IBA criteria met, protection status, and designation year. This layer supports conservation planning, environmental assessment, and biodiversity monitoring efforts, and is intended for use by researchers, land managers, policymakers, and conservation organizations.

This School District Boundaries GIS layer delineates the geographic boundaries of public school districts within York County, Pennsylvania. This spatial dataset includes detailed polygon features representing each school district, attributed with relevant metadata such as district name, district type (e.g., elementary, secondary, unified), district code, and jurisdictional identifiers (e.g., county, state, or region). Developed using authoritative data sources such as state education departments and local government records, this layer is intended for use in educational planning, demographic analysis, resource allocation, and policy development. The layer supports spatial analysis in relation to population density, transportation networks, socioeconomic indicators, and land use. Regular updates ensure alignment with changes due to redistricting, annexation, or other administrative modifications. The dataset is compatible with standard GIS software and adheres to common geospatial data formats and projections.