This interactive map is part of the Carbon County Emerging Areas Plan, an initiative to identify and plan for areas that are likely to experience future growth or transition. The goal of the plan is to balance development needs with the preservation of community character, infrastructure efficiency, and environmental quality.Through this map, community members can:Review current land use, zoning, transportation corridors, and environmental features.Identify locations of interest where change is occurring or anticipated.Provide comments or suggestions on topics such as housing, transportation, economic development, recreation, and open space.Help the County understand where growth should be encouraged or managed in the coming years. All input collected through this map will help shape the planning team’s understanding of emerging development patterns, infrastructure priorities, and community values. The data will be reviewed alongside demographic, economic, and environmental analyses to inform draft recommendations in the Emerging Areas Plan.Intended Use: Public engagement and planning support for Carbon County and its partners. Used as part of the Carbon County Emerging Area Plan and contains the Carbon County Emerging Areas Survey Results data.

This map contains planned active transportation facililties for Carbon County. It is sourced from UDOT's statewide feature layers of planned local and statewide facilities updated in 2022-23 as part of the Unified Transportation Plan effort with additional updates performed in 2024. This map contains a selection of these active transportation features within Carbon County to support the 2023-2024 Carbon County Emerging Areas Study.

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.

This U.S. Geological Survey (USGS) data release provides a digital geospatial database for the Geologic map of Precambrian rocks of the Sierra Madre, Carbon County, Wyoming, and Jackson and Routt Counties, Colorado (Houston and Graff, 1994). Attribute tables and geospatial features (points, lines and polygons) conform to the Geologic Map Schema (USGS NCGMP, 2020) and represent the geologic map as published in USGS Miscellaneous Investigations Series Map I-2452. The 890,172-acre map area represents the geology at a publication scale of 1:50,000. References: Houston, R.S., and Graff, P.J., 1994, Geologic map of Precambrian rocks of the Sierra Madre, Carbon County, Wyoming, and Jackson and Routt counties, Colorado: U.S. Geological Survey Miscellaneous Investigations Series Map I-2452, scale 1:50,000, https://doi.org/10.3133/i2452. 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.

This map displays planned highway projects for Carbon County. Highway project data is sourced from the UDOT 2023 Unified Transportation Planning effort. The map was developed to support the 2023-2024 Carbon County Emerging Areas Study.This map is a component of the Carbon County All Projects Map and All Projects Dashboard, supporting the Carbon County Emerging Area Plan Story Map.For more information please contact Andrea Moser at amoser@bio-west.com.

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 (USGS NCGMP, 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 ...

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 map displays transit study routes for Carbon County. The map supports the Carbon County All Projects Dashboard application and Carbon County Emerging Areas Story Map. Transit data is sourced from a transit study conducted on behalf of the Southeast Utah Association of Local Governments (SEUALG). The map was developed to support the 2023-2024 Carbon County Emerging Areas Study.This map is a component of the All Projects Dashboard, supporting the Carbon County Emerging Area Plan Story Map.For more information please contact Andrea Moser at amoser@bio-west.com.

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 (USGS NCGMP, 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) ...

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

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

The Web Map Service called Carbon Monoxide Stations (CO) – Annual Limit Value (VLA) allows the visualisation and consultation of the cartography containing the fixed air quality stations that have been used to carry out the assessment in accordance with Directive 2088/50/EC and RD 102/2011 on the improvement of air quality. The Annual Limit Value for Carbon Monoxide is 10 mg/m³. The URL of the WMS Carbon Monoxide (CO) Service – Annual Limit Value (VLA) is: https://wms.mapama.gob.es/sig/EvaluacionAmbiental/CalidadAire/Estaciones_VLA_CO/wms.aspx The reference systems offered by this service are: —For geographical coordinates: CRS: 84, EPSG:4230 (ED50), EPSG:4326 (WGS 84), EPSG:4258 (ETRS 89). —For U.T.M coordinates: EPSG:32628 (WGS 84/UTM zone 28N), EPSG:32629 (WGS 84/UTM zone 29N), EPSG:32630 (WGS 84/UTM zone 30N), EPSG:32631 (WGS 84/UTM zone 31N), EPSG:25828 (ETRS 89/UTM zone 28N), EPSG:25829 (ETRS 89/UTM zone 29N), EPSG:25830 (ETRS 89/UTM zone 30N), EPSG:25830 (ETRS 89/UTM zone 31N), EPSG:25830 (ED50/UTM zone 28N), EPSG:25830 (ED50/UTM zone 29N), EPSG:25830 (ED50/UTM zone 30N), EPSG:25830 (ED50/UTM zone 31N).

These data were created for planimetric display and tax area analysis.Procedures_Used:The principal method of data entry used coordinate geometry software.Digitizing from paper maps and use of digital planimetric data were supplemental. Conversions, filling of gaps, georeferencing, reconciliations, and reformatting were often necessary to create a coherent database. Boundary updates are occasionally accepted from local GIS departments when the USTC has not received all relevant boundary change information through required channels. Updates have been made in this manner to Sandy, some Cache, Washington, Utah, Wasatch, and Carbon County cities.Revisions: Municipal boundaries are revised as documents are filed with the Lt. Governor's Office.Reviews_Applied_to_Data:Digital sources were visually compared with planimetric data. Digitized data were overlaid with source material and visually compared. Technical errors were also identified and corrected with ArcGIS Software.Notes: This metadata document contains a composite of information for alltiles in the library.Current thru April 29, 2015

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.

A feasibility study was conducted to identify a suitable location for a new port of entry along US-6 in Carbon County. Five design concepts were developed and assessed in two phases. This map contains the conceptual design for The Tunnel Site as well as wetlands, streams, available utilities, and property parcel lines near the potential site.Purpose:This map contains the conceptual design for the Tunnel Site as well as wetlands, streams, available utilities, and property parcel lines near the potential site. This map suppors the Corral and Tunnel Sites storymap which is embedded within the of the Potential Sites for Port of Entry Relocation for the US-6 Port of Entry Relocation Concept project. Go Live Date:8/18/2017 Project PIN: 15224 ePM Project Name:US-6; Port of Entry Relocation Concept Owner: Bracken Davis (udotgisr4@utah.gov) Update Interval:Data was created for study and is not updated. Data Input Method:Manual data creation. Support Layers:US_6_Port_of_Entry feature layer Associated Apps:US-6 Port of Entry Relocation Concept storymapCorral and Tunnel Sites storymap Expected Life of Data:Study is complete and is being maintained as a reference.

The Nonattainment Area - Carbon Monoxide (CO-1971) dataset was updated on September 30, 2025 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

This polygon dataset shows the outlines of states, counties, and county equivalents (Louisiana parishes, Alaska boroughs, Puerto Rico municipalities, and U.S. Virgin Islands districts). The data were provided by the U.S. Census Bureau. EPA joined these boundaries with a forest carbon data set to create a map of forest carbon trends by county.

The Long Valley Caldera GIS Database provides an overview of the studies being conducted by the Long Valley Observatory in eastern California from 1975 to 2001. The database includes geologic, monitoring, and topographic datasets related to Long Valley caldera. The CD-ROM contains a scan of the original geologic map of the Long Valley region by R. Bailey. Real-time data of the current activity of the caldera (including earthquakes, ground deformation and the release of volcanic gas), information about volcanic hazards and the USGS response plan are available online at the Long Valley observatory web page (http://lvo.wr.usgs.gov). If you have any comments or questions about this database, please contact the Scientist in Charge of the Long Valley observatory.

[Summary provided by the USGS.]

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, CO 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

This layer is a high-resolution tree canopy change-detection layer for Montgomery County, Maryland. It contains three tree-canopy classes for the period 2009-2014: (1) No Change; (2) Gain; and (3) Loss. It was created by extracting tree canopy from an existing high-resolution land-cover map for 2009 and a high resolution tree canopy map for 2014 and then comparing the mapped trees directly. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed by development, storms, or disease were assigned to the Loss class. Trees planted during the interval were assigned to the Gain category, as were the edges of existing trees that expanded noticeably. Direct comparison was possible because both the 2009 and 2014 maps were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). No accuracy assessment was conducted, but the dataset was subjected to thorough manual review and correction.