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.
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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)
U.S. Government Workshttps://www.usa.gov/government-works
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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, Pennsylvania's Zoning Districts - Each Unique Municipality has been contributed and combined distinctly to an overall layer for a Carbon County Zoning layer. - April 24, 2020
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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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.
Geospatial data about Carbon County, Utah Parcels. Export to CAD, GIS, PDF, CSV and access via API.
U.S. Government Workshttps://www.usa.gov/government-works
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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 ...
Parcels and Land Ownership dataset current as of 2002. landown.
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This layer is a high-resolution tree canopy change-detection layer for Prince Georges 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 first mapping tree canopy in 2014 using LiDAR and multispectral data and then comparing the new map directly to an existing tree-canopy map for the year 2009. 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 comprehensive manual review and correction.
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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.
description: 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 Dec. 30, 2016; abstract: 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 Dec. 30, 2016
Title | China County Data Collection of Agricultural and Geographic Datasets |
Description | The agricultural and geographic datasets included on the China County Data collection were compiled in the early 1990s for use as inputs to the DNDC (Denitrification-Decomposition) model at UNH. DNDC is a computer simulation model for predicting carbon (C) and nitrogen (N) biogeochemistry in agricultural ecosystems. The datasets were compiled from multiple Chinese sources and all are at the county scale for 1990. The datasets which comprise this collection are listed below. Each dataset has a Child DIF designated by a numerical suffix, based on the list number below, added on to the entry id. 1) Agricultural Management 2) Crops 3) N-Deposition 4) Geography and Population 5) Land Use 6) Livestock 7) Soil Properties |
Date | |
Media Type | ATOM | SRU |
Metadata | ISO 19139 | ISO 19139-2 |
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/
Road and Street Centerlines dataset current as of 2002. taneclarklane0702.
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SIS SOIL:The new Irish Soil Information System concludes a 5 year programme, supported by the Irish Environmental Protection Agency (STRIVE Research Programme 2007-2013) and Teagasc, to develop a new 1:250,000 scale national soil map (http://soils.teagasc.ie). The Irish Soil Information System adopted a unique methodology combining digital soil mapping techniques with traditional soil survey application. Developing earlier work conducted by An Foras Talúntais, the project generated soil-landscape models for previously surveyed counties. These soil-landscape (‘soilscape’) models formed the basis for training statistical ‘inference engines’ for predicting soil mapping units, checked during field survey. 213 soil series are identified, each with differing characteristics, having contrasting environmental and agronomic responses. Properties were recorded in a database able to satisfy national and EU policy requirements. The Irish soil map and related soil property data will also serve public interest, providing the means to learn online about Irish soil resources. Use the Symbology layer file 'SOIL_SISNationalSoil.lyr' based on Value Field 'Association_Unit'. SIS SOIL DRAINAGE:In Ireland, soil drainage category is considered to have a predominant influence on soil processes (Schulte et al., 2012). The maritime climate of Ireland drives wet soil conditions, such that excess soil moisture in combination with heavy textured soils is considered a key constraint in relation to achieving productivity and environmental targets. Both soil moisture content and the rate at which water drains from the soil are critical indicators of soil physical quality and the overall functional capacity of soil. Therefore, a natural extension to the Irish Soil Information System included the development of an indicative soil drainage map for Ireland. The soil subgroup map was used to develop the indicative drainage map, based on diagnostic criteria relating to the subgroup categorization. Use the Symbology layer file 'SOIL_SISSoilDrainage.lyr' based on Value Field 'Drainage'. SIS SOIL DEPTH: Soil depth is a measure of the thickness of the soil cover and reflects the relationship between parent material and length of soil forming processes. Soil depth determines the potential rooting depth of plants and any restrictions within the soil that may hinder rooting depth. Plants derive nearly 80 per cent of their water needs from the upper part of the soil solum, i.e. where the root system is denser. The rooting depths depend on plant physiology, type of soil and water availability. Generally, vegetables (beans, tomatoes, potatoes, parsnip, carrots, leek, broccoli, etc.) are shallow rooted, about 50–60 cm; fruit trees and some other plants have medium rooting depths, 70–120 cm and other crops such as barley, wheat, oats, and maize may have deeper roots. Furthermore, rooting depths vary according to the age of the plants. The exact soil depth is difficult to define accurately due to its high variability across the landscape. The effective soil depth can be reduced by the presence of bedrock or impermeable layers. Use the Symbology layer file 'SOIL_SISSoilDepth.lyr' based on Valued Field 'Depth'. SIS SOIL TEXTURE:Soil texture is an important soil characteristic that influences processes such as water infiltration rates, rootability, gas exchanges, leaching, chemical activity, susceptibility to erosion and water holding capacity. The soil textural class is determined by the percentage of sand, silt, and clay. Soil texture also influences how much water is available to the plant; clay soils have a greater water holding capacity than sandy soils. Use the Symbology layer file 'SOIL_SISSoilTexture.lyr' based on Value Field 'Texture'. SIS SOIL SOC:In the previous national soil survey conducted by An Foras Taluntais, 14 counties were described in detail with soil profile descriptions provided for the representative soil series found within a county. Soil samples were taken at each soil horizon to a depth of 1 meter and analyses performed for a range of measurements, including soil organic carbon, texture, cation exchange capacity, pH; however in most cases no bulk density measurements were taken. This meant that while soil organic carbon concentrations were available this could not be related to a stock for a given soil series. In 2012/2013, 246 profile pits were sampled and analysed as part of the Irish Soil Information System project to fill in gaps in the description of representative profile data for Ireland. Use the Symbology layer file 'SOIL_SISSoilSOC.lyr' based on Value Field 'SOC'.
Road and Street Centerlines dataset current as of 2003. roads20030509.
Road and Street Centerlines dataset current as of 2001. cedarridge0801.
Road and Street Centerlines dataset current as of 2001. pricklypear0801b.
Parcels and Land Ownership dataset current as of 2000. parcels2000-Parcels for T 14 S, R 10 E (incomplete) and Sheep Creek Grazing Allotment area..
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.