Simple municipal name/GEOID lookup table.The table combines GEOID with census county names and municipal names. Stored as view in the demographics schema.

USA Census Block Groups (CBG) for Urban Search and Rescue. This layer can be used for search segment planning. Block groups generally contain between 600 and 5,000 people and the boundaries generally follow existing roads and waterways. The field segment_designation is the last 6 digits of the unique identifier and matches the field in the SARCOP Segment layer.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, and BLOCK.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block group level, since this data has been protected using differential privacy.* *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual block groups will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the block group itself.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

We present a regional geoid model for the area of Lake Vostok, Antarctica, from a combination of local airborne gravity, ice-surface and ice-thickness data and a lake bathymetry model. The topography data are used for residual terrain modelling (RTM) in a remove-compute-restore approach together with the GOCE satellite model GOCO03S. The disturbing potential at the Earth's surface, i.e. the quasigeoid, is predicted by least-squares collocation (LSC) and subsequently converted to geoid heights. Compared to GOCO03S our regional solution provides an additional short-wavelength signal of up to 1.48 m, or 0.56 m standard deviation, respectively. More details can be found in Schwabe et. al (2014).

The geoid model for Taiwan, including the Kinmen and Matzu islands, covers the area 118°E–125°E and 21°N–27°N with a grid resolution of 30" x 30". The gravimetric model is based on land, shipborne and airborne gravity data, as well as marine gravity derived from satellite altimetry. After merging data by least-squares collocation, a remove-restore procedure is applied. First height anomalies are computed by 1D FFT with Wong-Gore modification of the Stokes kernel and then they are converted into the geoid heights. The reference global gravity model is EGM2008 up to degree and order 2190. The used digital terrain model is derived from several photogrammetric surveys at a resolution of 3"×3" and 9"×9" for the inner and outer zone, respectively. The gravimetric model fits the GPS/levelling control points with a standard deviation of 7.9 cm (and a mean difference of 21.9 cm). The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.

We present a geoid solution for the Weddell Sea and adjacent continental Antarctic regions. There, a refined geoid is of interest, especially for oceanographic and glaciological applications. For example, to investigate the Weddell Gyre as a part of the Antarctic Circumpolar Current and, thus, of the global ocean circulation, the mean dynamic topography (MDT) is needed. These days, the marine gravity field can be inferred with high and homogeneous resolution from altimetric height profiles of the mean sea surface. However, in areas permanently covered by sea ice as well as in coastal regions, satellite altimetry features deficiencies. Focussing on the Weddell Sea, these aspects are investigated in detail. In these areas, ground-based data that have not been used for geoid computation so far provide additional information in comparison with the existing high-resolution global gravity field models such as EGM2008. The geoid computation is based on the remove–compute–restore approach making use of least-squares collocation. The residual geoid with respect to a release 4 GOCE model adds up to two meters and more in the near-coastal and continental areas of the Weddell Sea region, also in comparison with EGM2008. Consequently, the thus refined geoid serves to compute new estimates of the regional MDT and geostrophic currents.

This product contains a time series of clock biases for healthy satellites in the GLONASS constellation that are accumulated every minute throughout the day. In addition, formal 1-sigma uncertainties for the corrections are provided. The product is generated at JPL's Global Differential GPS Operations Centers in real-time. The data in this product can be concatenated with other daily products to provide larger coverage in time.

This dataset contains annual mean geostrophic velocity calculated at depth corresponding to negative values of the marine geoid. It is calculated from two open sources from the geodetic (EIGEN-6C4) and oceanographic (NCEI) communities. The first source EIGEN-6C4 is a static global combined gravity field model developed by GFZ Potsdam and GRGS Toulouse up to degree and order 2190. The second source is the “World ocean geostrophic velocity inverted from World Ocean Atlas 2013 with the P-vector method†(NCEI accession 0121576). With the given non-positive values of the geoid, N, (i.e., for the oceans), the absolute geostrophic currents (u, v) are easily identified on N with 1 degree resolution from the second dataset except the equatorial zone (5oS – 5oN) due to the non-existence of the geostrophic balance. Altogether, the dataset contains 15,481 (u, v) data pairs. While there is no geostrophic motion at the surface if it coincided with the geoid, the opposite is not valid. This dataset shows that ocean geostrophic velocity doesn't zero at z=N. Data are in netcdf format.

This product ontains antenna phase center locations relative to the GPS satellite's center of mass. The product is generated at JPL's Global Differential GPS Operations Centers.

This complements our article “Sea-level fingerprints emergent from GRACE mission data” submitted to Earth System Science Data (https://doi.org/10.5194/essd-2019-3). Based on CSR, GFZ, and JPL Stokes coefficients, we derive spherical harmonic coefficients and spatial maps for relative sea level, geoid height change, and vertical bedrock motion. We provide monthly solutions with and without Earth’s rotational feedback included, both in the center-of-mass (CM) and center-of-figure (CF) reference frames.

This file contains a list of geodetic bench marks, identified by a Permanent Identifier (PID), each of which have a precise orthometric height determined by geodetic leveling, a precise ellipsoid height determined by GPS surveying, and a precise modeled hybrid geoid height. The observations were used to constrain a gravimetric geoid model to the surface of a current vertical datum to produce a hybrid geoid model and associated performance metrics. The data is primarily from the US, however some data from Canada and Mexico is included as well.

This layer contains a Vermont-only subset of block group level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, and BLOCK.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block group level, since this data has been protected using differential privacy.*VCGI exported a Vermont-only subset of the nation-wide layer to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract BLKGRP: Block Group AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLAT: Internal Point (Latitude) INTPTLON: Internal Point (Longitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual block groups will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

This product contains antenna phase center locations relative to the Galileo satellite's center of mass. The product is generated at JPL's Global Differential GPS Operations Centers.

This dataset is about: Free air anomalies, Bouguer anomalies and geoid undulations of the Eltanin impact area.

2020 Census Tracts from the US Census for New York City. These boundary files are derived from the US Census Bureau's TIGER data products and have been geographically modified to fit the New York City base map. All previously released versions of this data are available at BYTES of the BIG APPLE- Archive.

The daily solution files are an analysis product that provides estimates of Earth orientation and site positions for each 24-hour session, the covariance matrix of the estimates, and decomposed normal equations. The solution files are in SINEX format. The SINEX product files are available on the same frequency as the EOP-S products: 24 hours after each new session data base is available.

The VIIRS/JPSS1 Moderate Resolution Terrain Corrected Geolocation 6-Min L1 Swath 750m product, short-name VJ103MOD contains the derived line-of-sight (LOS) vectors for each of the 750-m moderate-resolution, or M-bands. The geolocation algorithm uses a number of inputs that include an Earth ellipsoid, geoid, and a digital terrain model along with the SNPP platform’s ephemeris and attitude data, and knowledge of the VIIRS sensor and satellite geometry. It produces geodetic coordinates (latitude and longitude), and related parameters for each VIIRS L1 pixel. The VJ103MOD product includes geodetic latitude, longitude, surface height above the geoid, solar zenith and azimuth angles, sensor zenith and azimuth angles, land/water mask, and quality flag for every pixel location.

The VIIRS/NPP Moderate Resolution Terrain-Corrected Geolocation 6-Min L1 Swath 750 m product, short-name VNP03MOD, contains the derived line-of-sight (LOS) vectors for each of the 750-m moderate-resolution, or M-bands. The geolocation algorithm uses a number of inputs that include an Earth ellipsoid, geoid, and a digital terrain model along with the SNPP platform’s ephemeris and attitude data, and knowledge of the VIIRS sensor and satellite geometry. It produces geodetic coordinates (latitude and longitude), and related parameters for each VIIRS L1 pixel. The VNP03MOD product includes geodetic latitude, longitude, surface height above the geoid, solar zenith and azimuth angles, sensor zenith and azimuth angles, land/water mask, and quality flag for every pixel location.

The VIIRS/JPSS2 Moderate Resolution Terrain Corrected Geolocation 6-Min L1 Swath 750 m, short-name VJ203MOD is the Joint Polar-orbiting Satellite System-2 (JPSS-2/NOAA-21) platform-based NASA Visible-Infrared Imaging-Radiometer Suite (VIIRS) L1 terrain-corrected geolocation product, and contains the derived line-of-sight (LOS) vectors for each of the 750-m moderate-resolution, or M-bands. The geolocation algorithm uses a number of inputs that include an Earth ellipsoid, geoid, and a digital terrain model along with the SNPP platform’s ephemeris and attitude data, and knowledge of the VIIRS sensor and satellite geometry. It produces geodetic coordinates (latitude and longitude), and related parameters for each VIIRS L1 pixel. The VJ203MOD product includes geodetic latitude, longitude, surface height above the geoid, solar zenith and azimuth angles, sensor zenith and azimuth angles, land/water mask, and quality flag for every pixel location. VJ203MOD provides a fundamental input to derive a number of VIIRS M-band higher-level products.The J2 VIIRS geolocation underwent an on-orbit validation. Geolocation errors of about 350 m in the along-scan direction and about 165 m in the along-track direction were corrected for the image-resolution bands and moderate-resolution bands. The Day-Night band (DNB) geolocation error of about 2000 m was corrected. For more information and documents, visit LAADS product page at:https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/VJ203MOD

The VIIRS/NPP Imagery Resolution Terrain-Corrected Geolocation 6-Min L1 Swath 375m, short-name VNP03IMG, product contains the derived line-of-sight (LOS) vectors for each of the 375-m image-resolution or I-bands. The geolocation algorithm uses a number of inputs that include an Earth ellipsoid, geoid, and a digital terrain model along with the SNPP platform’s ephemeris and attitude data, and knowledge of the VIIRS sensor and satellite geometry. It produces geodetic coordinates (latitude and longitude), and related parameters for each VIIRS L1 pixel. The VNP03IMG product includes geodetic latitude, longitude, surface height above the geoid, solar zenith and azimuth angles, sensor zenith and azimuth angles, land/water mask, and quality flag for every pixel _location.

This product contains a time series of attitude quaternion components for healthy satellites in the Galileo constellation that are accumulated every minute throughout the day. The product is generated at JPL's Global Differential GPS Operations Centers in real-time. The data in this product can be concatenated with other daily products to provide larger coverage in time.