Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under Basic Parcels."Database containing parcel boundary, parcel identifier, parcel address, owner type, and county recorder contact information" - HB113. The intent of the bill was to not include any attributes that the counties rely on for data sales. If you want other attributes associated with the parcels you need to contact the county recorder.Users should be aware the owner type field 'OWN_TYPE' in the parcel polygons is a very generalized ownership type (Federal, Private, State, Tribal). It is populated with the value of the 'OWNER' field where the parcel's centroid intersects the CADASTRE.LandOwnership polygon layer.This dataset is a snapshot in time and may not be the most current. For the most current data contact the county recorder.

This U.S. Geological Survey (USGS) data release for the geologic map of the Arlington quadrangle, Carbon County, Wyoming, is a Geologic Map Schema (GeMS, 2020)-compliant version of the printed geologic map published in USGS Geologic Map Quadrangle GQ-643 (Hyden and others, 1967). The database represents the geology for the 35,776-acre map plate at a publication scale of 1:24,000. References: Hyden, H.J., King, J.S., and Houston, R.S., 1967, Geologic map of the Arlington quadrangle, Carbon County, Wyoming: U.S. Geological Survey, Geologic Quadrangle Map GQ-643, scale 1:24,000; https://doi.org/10.3133/gq643. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

This U.S. Geological Survey (USGS) data release provides a digital geospatial database for the geologic map of the White Rock Canyon quadrangle, Carbon County, Wyoming (Hyden and others, 1968). Attribute tables and geospatial features (points, lines and polygons) conform to the Geologic Map Schema (GeMS, 2020) and represent the geologic map as published in USGS Geologic Quadrangle Map GQ-789. The 35,758-acre map area represents the geology at a publication scale of 1:24,000. References: Hyden, H.J., Houston, R.S., and King, J.S., 1968, Geologic map of the White Rock Canyon quadrangle, Carbon County, Wyoming: U.S. Geological Survey, Geologic Quadrangle Map GQ-789, scale 1:24,000, https://doi.org/10.3133/gq789. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

Carbon County Cadastral Data ResourcesA snapshot of property and parcel data for June 2022.Department of Revenue Orion SQL property record database provided as both an SQL database and as tables in a file geodatabase.File Geodatabase and Shapefile options for parcel polygon GIS data.Visit the Montana State Library Cadastral MSDI page for more information on cadastral data and Orion property database : MSDI Cadastral (mt.gov)The Montana Cadastral Framework shows the taxable parcels and tax-exempt parcels for most of Montana. The parcels contain selected information such as owner names, property and owner addresses, assessed value, agricultural use, and tax district information that were copied from the Montana Department of Revenue's ORION tax appraisal database. The data are maintained by the MT Department of Revenue, except for Ravalli, Silver Bow, Missoula, Flathead and Yellowstone counties that are maintained by the individual counties. The Revenue and county data are integrated by Montana State Library staff. Each parcel contains an attribute called ParcelID (geocode) that is the parcel identifier. View a pdf map of the counties that were updated this month here: https://ftpgeoinfo.msl.mt.gov/Data/Spatial/MSDI/Cadastral/Parcels/Statewide/MonthlyCadastralUpdateMap.pdf The parcel boundaries were aligned to fit with the Bureau of Land Management Geographic Coordinate Database (GCDB) of public land survey coordinates. Parcels whose legal descriptions consisted of aliquot parts of the public land survey system were created from the GCDB coordinates by selecting and, when necessary, subdividing public land survey entities. Other parcels were digitized from paper maps and the data from each map were transformed to fit with the appropriate GCDB boundaries.

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This map shows specific water-quality items and hydrologic data site information which come from QWDATA (Water Quality) and GWSI (Ground Water Information System). Both QWDATA and GWSI are subsystems of NWIS (National Water Inventory System)of the USGS (United States Geologic Survey). This map is for Carbon County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/

This U.S. Geological Survey (USGS) data release provides a digital geospatial database for the geologic map of Precambrian metasedimentary rocks of the Medicine Bow Mountains, Albany and Carbon Counties, Wyoming (Houston and Karlstrom, 1992). Attribute tables and geospatial features (points, lines and polygons) conform to the Geologic Map Schema (GeMS, 2020) and represent the geologic map plates as published at a scale of 1:50,000. The 358,697-acre map area includes the geologically complex Medicine Bow Mountains located 30 miles (48 kilometers) west of Laramie in southeastern Wyoming. References: Houston, R.S., and Karlstrom, K.E., 1992, Geologic map of Precambrian metasedimentary rocks of the Medicine Bow Mountains, Albany and Carbon Counties, Wyoming: U.S. Geological Survey, Miscellaneous Investigations Series Map I-2280, scale 1:50,000, https://doi.org/10.3133/i2280. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A sta ...

The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=2284

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information.

This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and nonsoil areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=176

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Public Web map showing voting precincts and polling locations in Carbon County Montana

Preliminary geologic map of the Fort Steele quadrangle, Carbon County, Wyoming
WSGS PubID: OFR-2017-5

FIA Modeled Abundance:�This dataset portrays the live tree mean basal area (square feet per acre) of the species across the contiguous United States. The underlying data publication contains raster maps of live tree basal area for each tree species along with corresponding assessment data. An efficient approach for mapping multiple individual tree species over large spatial domains was used to develop these raster datasets. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-meter (m) pixel size for the contiguous United States. The approach uses the modeling techniques of k-nearest neighbors and canonical correspondence analysis, where model predictions are calculated using a weighting of nearest neighbors based on proximity in a feature space derived from the model. The approach also utilizes a stratification derived from the 2001 National Land-Cover Database tree canopy cover layer.�This data depicts current species abundance and distribution across the contiguous United States, modeled by using FIA field plot data. Although the absolute values associated with the maps differ from species to species, the highest values within each map are always associated with darker colors. The Little's Range Boundaries show the historical tree species ranges across North America. This is a digital representation of maps by Elbert L. Little, Jr., published between 1971 and 1977. These maps were based on botanical lists, forest surveys, field notes and herbarium specimens.Forest-type Groups:This dataset portrays the forest type group. Each group is a subset of the National Forest Type dataset which portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data.Harvest Growth:This data shows the percentage of timber that is harvested when compared to the total live volume, at a county-by-county level. Timber volume in forests is constantly in flux, and harvest plays an important role in shaping forests. While most counties have some timber harvest, harvest volumes represent low percentages of standing timber volume.Carbon Harvest:The Carbon Harvest raster dataset represents Mg of annual pulpwood harvested (carbon) by county, derived from the Forest Inventory Analysis in 2016.

This data package contains mapped trait estimates and their uncertainties, and conifer map, for the National Ecological Observatory Network's Airborne Observation Platform survey data acquired over the Upper East River, Colorado in 2018. For full details, please see associated reference. in brief, trait models were developed independently for needle and non-needle leaf species using partial least squares regression (PLSR) using ground data from additional datasets: doi:10.15485/1618130, doi:10.15485/1618132, and doi:10.15485/1631278, merged with extracted spectral data from doi:10.15485/1618131. We separated vegetated pixels into needle and non-needle classes in order to generate a classification map based on the spectral differences between these leaf types (conifer.tif). We trained a deep learning model with custom architecture, detailed in Chadwick et al. In Press. The model performed with 0.998 true positive rate and 0.982 true negative rate, with ‘positives’ being non-needle identification. We then utilized PLSR to generate models of foliar traits for each leaf type. So that we could also map uncertainty in these predictions, we generated ten different models for needle and non-needle leaf species using different testing holdout sets of discrete sites. Each of these models was developed with a 100-fold cross validation procedure that utilized a 70% training set and 30% validation set with each fold, and then assessed based on the 10% of testing sites that were not included in that model’s development. The mean predicted value across the 10 models is used for the trait estimate in each pixel across the study area. The models are applied according to the leaf type designation in the conifer.tif map. The errors are the standard deviation across the 10 different models developed, with high error suggesting instability in model prediction and areas where values may not be reliable for ecological inference. These maps are only applied to areas with a NDVI > 0.5 to exclude non-vegetated areas. Shade masks could be applied to these data (doi:10.15485/1618131), but have not been for this data package. These data are also available on Google Earth Engine: https://code.earthengine.google.com/?asset=users/kdc/ER_NEON

These ArcView shapefiles contain representations of the net coal thickness in the Ferris 23, 25, 31, 50 and 65 coal zones in the Ferris coalfield, Hanna Basin, Wyoming. These datasets were created specifically for the National Coal Resource Assessment in the Northern Rocky Mountains and Great Plains Region.

The Nonattainment Area - Carbon Monoxide (CO-1971) dataset was designated on November 15, 1990 by the Environmental Protection Agency (EPA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This dataset provides detailed information about nonattainment area designations for the Carbon Monoxide (1971) National Ambient Air Quality Standards (NAAQS). These data are weekly from an OAQPS internal database. However, that does not necessarily mean the data have changed. For more information about this non-attainment area, please see the website https://www.epa.gov/green-book/green-book-carbon-monoxide-1971-area-information. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529062

Water samples have predominantly been collected by the G-BASE (Geochemical Baseline Survey of the Environment) project at an average sampling density of one sample per 1.5 km square. Samples have been collected from approximately 85% of Great Britain but it is only from Wales and Humber-Trent southwards that a wide range of analytes have been determined. Currently G-BASE stream water samples collected from high order streams are determined by ICP-AES for 27 elements - Sr, Cd, Ba, Si, Mn, Fe, P, S (as SO42-), B, Mg, V, Na, Mo, Al, Be, Ca, Zn, Cu, Pb, Li, Zr, Co, Ni, Y, La, K and Cr; and by quadrupole ICP-MS for 24 trace elements - Li, Be, Al, V, Cr, Co, Ni, Cu, As, Rb, Y, Zr, Mo, Ag, Cd, Sn, Sb, Ba, La, Ce, Tl, Pb, Th and U. Automated colorimetric methods are used to determine Cl and NO3- and ion selective electrode is used to determine F. Waters are also analysed for non-purgeable organic carbon (NPOC) to determine dissolved organic carbon content. All samples have routinely been analysed for pH, conductivity and bicarbonate. Much of the UK coverage also includes uranium and fluoride analyses.

This record is maintained in the National Geologic Map Database (NGMDB). The NGMDB is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information, developed according to standards defined by the cooperators, i.e., the USGS and the Association of American State Geologists (AASG). Included in this system is a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 90,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies. For more information, please see http://ngmdb.usgs.gov/.

Last update: April 4, 2023Added the Mammoth address system in Juab county. Additional minor edits to account for annexations in Utah (Springville, Lehi) and Box Elder (Willard, Garland) counties, April 2023.Added several address grids in Beaver county (Elk Meadows, Ponderosa, Greenville, Adamsville, Sulphurdale). Made major updates to grids in Utah, Cache, Tooele, and Box Elder Counties. Renamed 'NSL' to 'North Salt Lake' and 'East Carbon City' to 'East Carbon', December 2022. Minor adjustment to quadrants in Bluff.Added Rocky Ridge address grid in northern Juab county, August 2022.Updates were made near Elsinore/Central Valley/Monroe corners due to recent Elsinore annexation and inputs from Sevier County, September 2021.Improvements were made to Brigham City, Millville, Logan, and Providence, February 2016.Improvements were made to the Heber, Hyde Park, Logan, and Woodland address system boundaries; updated the American Fork, Fielding, Payson, and Saratoga Springs address system boundaries to reflect recent annexations, January 2016Improvements were made to the Hyde Park and Logan address system boundary, November 2015Improvements were made to the Hyrum and Logan address system boundary, November 2015Updated the American Fork address system boundary to reflect recent annexations, October 2015Improvements were made to the Brigham City, Fishlake, Fremont, Garland, Loa, Lyman, Mantua, Tremonton, and Willard address system boundaries; updated the Lehi and Santa Clara address system boundaries to reflect recent annexations, August 2015Improvements were made to the Price and Wellington address system boundaries; updated the Lehi and Provo address system boundaries to reflect recent annexations, July 2015Improvements were made to the Layton and HAFB address system boundaries; updated the Provo and Spanish Fork address system boundaries to reflect recent annexations, June 2015Updated address system boundaries to reflect annexations in Lehi, Lewiston, and Snowville, May 2015Improvements were made to the Orderville address system boundary to match the municipal boundary, February 2015Updated address system boundaries to match annexations in American Fork, Farmington, Elk Ridge, Grantsville, Lehi, Mendon, Mount Pleasant, Payson, Provo, Spanish Fork, and Washington, January 2015 Improvements were made to the Elmo and Cleveland address system boundaries, December 2014Improvements were made to the Wellington address system boundaries, July 2014Improvements were made to the NSL (North Salt Lake) and Bountiful address system boundaries, June 2014.Changed address system name East Carbon-Sunnyside to East Carbon City, May 2014Updated address system boundaries to match annexations in northern Utah County; misc improvements in Davis County; adjusted Laketown/Garden City boundary, April 2014Merged East Carbon and Sunnyside to create the East Carbon-Sunnyside address system, February 2014.Improvements were made to the Iron County address system quadrant boundaries and topological errors were corrected statewide, January 2014. Improvements were made to Garfield County and Washington County address system quadrant boundaries, August 2013.More information can be found on the UGRC data page for this layer:https://gis.utah.gov/data/location/address-data/