19 datasets found
  1. d

    GIS Data for Geologic Map of the Lake Owen Quadrangle, Albany County,...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). GIS Data for Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming [Dataset]. https://catalog.data.gov/dataset/gis-data-for-geologic-map-of-the-lake-owen-quadrangle-albany-county-wyoming
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Wyoming, Lake Owen, Albany County
    Description

    This U.S. Geological Survey (USGS) data release presents a digital database of geospatially enabled vector layers and tabular data transcribed from the geologic map of the Lake Owen quadrangle, Albany County, Wyoming, which was originally published as U.S. Geological Survey Geologic Quadrangle Map GQ-1304 (Houston and Orback, 1976). The 7.5-minute Lake Owen quadrangle is located in southeastern Wyoming approximately 25 miles (40 kilometers) southwest of Laramie in the west-central interior of southern Albany County, and covers most of the southern extent of Sheep Mountain, the southeastern extent of Centennial Valley, and a portion of the eastern Medicine Bow Mountains. This relational geodatabase, with georeferenced data layers digitized at the publication scale of 1:24,000, organizes and describes the geologic and structural data covering the quadrangle's approximately 35,954 acres and enables the data for use in spatial analyses and computer cartography. The data types presented in this release include geospatial features (points, lines, and polygons) with matching attribute tables, nonspatial descriptive and reference tables, and ancillary resource files for correct symbolization, in formats that conform to the Geologic Map Schema (GeMS) developed and released by the U.S. Geological Survey's National Cooperative Geologic Mapping Program (GeMS, 2020). When reconstructed from the geodatabase's vector layers and tabular data that has been symbolized according to specifications encoded in the accompanying style file, and using the supplied Federal Geographic Data Committee (FGDC) GeoAge font for labeling formations and GeoSym fonts for structural line decorations and orientation measurement symbols, this data release presents the Geologic Map as shown on the published GQ-1304 map sheet. These GIS data augment but do not supersede the information presented on GQ-1304. References: Houston, R.S., and Orback, C.J., 1976, Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming: U.S. Geological Survey Geologic Quadrangle Map GQ-1304, scale 1:24,000, https://doi.org/10.3133/gq1304. 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.

  2. U

    GIS Data for Geologic Map of Precambrian Metasedimentary Rocks of The...

    • data.usgs.gov
    • gimi9.com
    • +2more
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    John Horton, GIS Data for Geologic Map of Precambrian Metasedimentary Rocks of The Medicine Bow Mountains, Albany and Carbon Counties, Wyoming [Dataset]. http://doi.org/10.5066/P9WR0WYI
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    John Horton
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Jan 6, 2023
    Area covered
    Medicine Bow Mountains, Wyoming
    Description

    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 ...

  3. StateBoundaries

    • anrgeodata.vermont.gov
    Updated May 18, 2018
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    Esri Training Services (2018). StateBoundaries [Dataset]. https://anrgeodata.vermont.gov/maps/f742fb8f6fde4cf9b8d407e3808542cf_0/about
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    Dataset updated
    May 18, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Training Services
    Area covered
    Description

    This map layer portrays the State boundaries of the United States, Puerto Rico, and the U.S. Virgin Islands. The map layer was created by extracting county polygon features from the CENSUS 2006 TIGER/Line files produced by the U.S. Census Bureau. These files were then merged into a single file and county boundaries within States were removed. This is a revised version of the July 2012 map layer.

  4. d

    Snake River, Wyoming

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    • +5more
    Updated Nov 12, 2020
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    Teton County, Wyoming Road & Levy Department, Planning & Development (Originator); Sanborn Map Company (Originator); Grand Teton National Park (Originator); Bridger-Teton National Forest (Originator); U.S. Geological Survey, Northern Rocky Mountain Science Center (Originator); Teton Conservation District (Originator); null (Originator); USDA Forest Service Remote Sensing Application Center (Originator) (2020). Snake River, Wyoming [Dataset]. https://catalog.data.gov/dataset/snake-river-wyoming
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    Dataset updated
    Nov 12, 2020
    Dataset provided by
    Teton County, Wyoming Road & Levy Department, Planning & Development (Originator); Sanborn Map Company (Originator); Grand Teton National Park (Originator); Bridger-Teton National Forest (Originator); U.S. Geological Survey, Northern Rocky Mountain Science Center (Originator); Teton Conservation District (Originator); null (Originator); USDA Forest Service Remote Sensing Application Center (Originator)
    Area covered
    Snake River, Wyoming
    Description

    In 2008, Sanborn was contracted by Teton Conservation District to execute a LiDAR (Light Detection and Ranging) survey campaign in Teton County, Wyoming. LiDAR data in the form of 3-dimensional positions of a dense set of mass points was collected for the 141 square miles of area within the Snake River and Teton Ranges and Bridger-Teton National Forest. This data was used in the development of the bare-earth-classified elevation point data sets. This project was designed to provide a highly detailed ground surface dataset to be used for the development of topographic, contour mapping, and hydraulic monitoring.

  5. s

    Global Map: 1:1,000,000-Scale Political Boundary Lines of the United States,...

    • searchworks.stanford.edu
    zip
    Updated Sep 17, 2018
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    (2018). Global Map: 1:1,000,000-Scale Political Boundary Lines of the United States, 2014 [Dataset]. https://searchworks.stanford.edu/view/vm820jh8767
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    zipAvailable download formats
    Dataset updated
    Sep 17, 2018
    Area covered
    United States
    Description

    Global Map data are part of a cooperative effort among national mapping organizations around the world to produce and maintain a standard set of basic cartographic data that supports global investigations of natural and human-built environments. Participating nations prepare data using a common data structure and description to ensure compatibility and to tangibly promote the tenets of the Global Spatial Data Infrastructure. These data are intended for geographic display and analysis at the national level, and for large regional areas. The data should be displayed and analyzed at scales appropriate for 1:1,000,000-scale data. No responsibility is assumed by the National Atlas of the United States in the use of these data.

  6. Flood Hazard Areas (DFIRM) - Maui County

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +2more
    Updated Sep 18, 2021
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    Office of Planning (2021). Flood Hazard Areas (DFIRM) - Maui County [Dataset]. https://opendata.hawaii.gov/dataset/flood-hazard-areas-dfirm-maui-county
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    pdf, arcgis geoservices rest api, csv, zip, geojson, ogc wfs, html, ogc wms, kmlAvailable download formats
    Dataset updated
    Sep 18, 2021
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    Office of Planning
    Area covered
    Maui County
    Description

    [Metadata] Flood Hazard Areas for the County of Maui - downloaded from FEMA Flood Map Service Center, May 1, 2021. 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 Datum of 1983.

    For additional information, please summary metadata https://files.hawaii.gov/dbedt/op/gis/data/s_fld_haz_ar_state.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  7. Fayl:Map of Wyoming highlighting Albany County.svg

    • wikimedia.az-az.nina.az
    Updated Mar 27, 2025
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    www.wikimedia.az-az.nina.az (2025). Fayl:Map of Wyoming highlighting Albany County.svg [Dataset]. https://www.wikimedia.az-az.nina.az/Fayl:Map_of_Wyoming_highlighting_Albany_County.svg.html
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    Dataset updated
    Mar 27, 2025
    Dataset provided by
    Vikimedia Fonduhttp://www.wikimedia.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Vayominq, Albany County
    Description

    Fayl Faylın tarixçəsi Faylın istifadəsi Faylın qlobal istifadəsi MetaməlumatlarBu SVG faylın PNG formatındakı bu görünüş

  8. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
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    U.S. Geological Survey, ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/311fa126c6f240669940fe249f384aa6/html
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  9. s

    ScienceBase Item Summary Page

    • cinergi.sdsc.edu
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    U.S. Geological Survey, ScienceBase Item Summary Page [Dataset]. http://cinergi.sdsc.edu/geoportal/rest/metadata/item/33e3b15b763d4f0c8e7715a58dc5d877/html
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  10. S

    wyoming county

    • health.data.ny.gov
    Updated Mar 4, 2025
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    New York State Department of Health (2025). wyoming county [Dataset]. https://health.data.ny.gov/widgets/79c9-zfer
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    csv, xml, application/rssxml, application/geo+json, application/rdfxml, kml, kmz, tsvAvailable download formats
    Dataset updated
    Mar 4, 2025
    Authors
    New York State Department of Health
    Description

    The point map shows violations found during the last inspection of the food service establishments. The initial view of the map is broken up into large geographic areas and displays the number of violations in each area. To drill down to a smaller geographic area, click directly on the area of the map or click the plus sign to zoom in on the map. The map can be filtered by facility, city, and county by changing these options under the Filter tab. Last inspection data is the most recently submitted and available data.

    This map excludes inspections conducted in New York City (https://nycopendata.socrata.com/), Suffolk County (http://apps.suffolkcountyny.gov/health/Restaurant/intro.html) and Erie County (http://www.healthspace.com/erieny). Inspections are a “snapshot” in time and are not always reflective of the day-to-day operations and overall condition of an establishment. This map is currently updated monthly. Occasionally, remediation may not appear until the following month due to the timing of the updates. Some counties provide this information on their own websites and information found there may be more frequently updated.

    For more information check out http://www.health.ny.gov/regulations/nycrr/title_10/part_14/subpart_14-1.htm, or go to the "About" section.

  11. d

    EnviroAtlas - Duck Operations by County

    • datasets.ai
    • catalog.data.gov
    0, 23
    Updated Aug 28, 2024
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    U.S. Environmental Protection Agency (2024). EnviroAtlas - Duck Operations by County [Dataset]. https://datasets.ai/datasets/enviroatlas-duck-operations-by-county1
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    0, 23Available download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    U.S. Environmental Protection Agency
    Description

    This EnviroAtlas dataset summarizes by county the number of farm operations with ducks and the number of heads they manage. The data come from the Census of Agriculture, which is administered every five years by the US Department of Agriculture (USDA), and include the years 2002, 2007, 2012, and 2017. For each county and Census year, the dataset reports the number of farm operations that manage ducks and the number of heads on their property at the end of the Census year. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  12. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
    + more versions
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    ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/532206a3bf0148ac901fe8cfcfca116e/html
    Explore at:
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  13. BLM Natl WesternUS GRSG Biologically Significant Units October 2017 Update

    • colorado-river-portal.usgs.gov
    • gimi9.com
    • +2more
    Updated Jun 27, 2022
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    Bureau of Land Management (2022). BLM Natl WesternUS GRSG Biologically Significant Units October 2017 Update [Dataset]. https://colorado-river-portal.usgs.gov/datasets/BLM-EGIS::blm-natl-westernus-grsg-biologically-significant-units-october-2017-update/about
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    Dataset updated
    Jun 27, 2022
    Dataset authored and provided by
    Bureau of Land Managementhttp://www.blm.gov/
    Area covered
    Description

    The Sheeprocks (UT) was revised to resync with the UT habitat change as reflected in the Oct 2017 habitat data, creating the most up-to-date version of this dataset. Data submitted by Wyoming in February 2018 and by Montana and Oregon in May 2016 were used to update earlier versions of this feature class. The biologically significant unit (BSU) is a geographical/spatial area within Greater Sage-Grouse habitat that contains relevant and important habitats which is used as the basis for comparative calculations to support evaluation of changes to habitat. This BSU unit, or subset of this unit is used in the calculation of the anthropogenic disturbance threshold and in the adaptive management habitat trigger. BSU feature classes were submitted by individual states/EISs and consolidated by the Wildlife Spatial Analysis Lab. They are sometimes referred to as core areas/core habitat areas in the explanations below, which were consolidated from metadata submitted with BSU feature classes. These data provide a biological tool for planning in the event of human development in sage-grouse habitats. The intended use of all data in the BLM's GIS library is to support diverse activities including planning, management, maintenance, research, and interpretation. While the BSU defines the geographic extent and scale of these two measures, how they are calculated differs based on the specific measures to reflect appropriate assessment and evaluation as supported by scientific literature.There are 10 BSUs for the Idaho and Southwestern Montana GRSG EIS sub-region. For the Idaho and Southwestern Montana Greater Sage-Grouse Plan Amendment FEIS the biologically significant unit is defined as: a geographical/spatial area within greater sage-grouse habitat that contains relevant and important habitats which is used as the basis for comparative calculations to support evaluation of changes to habitat. Idaho: BSUs include all of the Idaho Fish and Game modeled nesting and delineated winter habitat, based on 2011 inventories within Priority and/or Important Habitat Management Area (Alternative G) within a Conservation Area. There are eight BSUs for Idaho identified by Conservation Area and Habitat Management Area: Idaho Desert Conservation Area - Priority, Idaho Desert Conservation Area - Important, Idaho Mountain Valleys Conservation Area - Priority, Idaho Mountain Valleys Conservation Area - Important, Idaho Southern Conservation Area - Priority, Idaho Southern Conservation Area - Important, Idaho West Owyhee Conservation Area - Priority, and Idaho West Owyhee Conservation Area - Important. Raft River : Utah portion of the Sawtooth National Forest, 1 BSU. All of this areas was defined as Priority habitat in Alternative G. Raft River - Priority. Montana: All of the Priority Habitat Management Area. 1 BSU. SW Montana Conservation Area - Priority. Montana BSUs were revised in May 2016 by the MT State Office. They are grouped together and named by the Population in which they are located: Northern Montana, Powder River Basin, Wyoming Basin, and Yellowstone Watershed. North and South Dakota BSUs have been grouped together also. California and Nevada's BSUs were developed by Nevada Department of Wildlife's Greater Sage-Grouse Wildlife Staff Specialist and Sagebrush Ecosystem Technical Team Representative in January 2015. Nevada's Biologically Significant Units (BSUs) were delineated by merging associated PMUs to provide a broader scale management option that reflects sage grouse populations at a higher scale. PMU boundarys were then modified to incorporate Core Management Areas (August 2014; Coates et al. 2014) for management purposes. (Does not include Bi-State DPS.) Within Colorado, a Greater Sage-Grouse GIS data set identifying Preliminary Priority Habitat (PPH) and Preliminary General Habitat (PGH) was developed by Colorado Parks and Wildlife. This data is a combination of mapped grouse occupied range, production areas, and modeled habitat (summer, winter, and breeding). PPH is defined as areas of high probability of use (summer or winter, or breeding models) within a 4 mile buffer around leks that have been active within the last 10 years. Isolated areas with low activity were designated as general habitat. PGH is defined as Greater sage-grouse Occupied Range outside of PPH. Datasets used to create PPH and PGH: Summer, winter, and breeding habitat models. Rice, M. B., T. D. Apa, B. L. Walker, M. L. Phillips, J. H. Gammonly, B. Petch, and K. Eichhoff. 2012. Analysis of regional species distribution models based on combined radio-telemetry datasets from multiple small-scale studies. Journal of Applied Ecology in review. Production Areas are defined as 4 mile buffers around leks which have been active within the last 10 years (leks active between 2002-2011). Occupied range was created by mapping efforts of the Colorado Division of Wildlife (now Colorado Parks and Wildlife –CPW) biologists and district officers during the spring of 2004, and further refined in early 2012. Occupied Habitat is defined as areas of suitable habitat known to be used by sage-grouse within the last 10 years from the date of mapping. Areas of suitable habitat contiguous with areas of known use, which do not have effective barriers to sage-grouse movement from known use areas, are mapped as occupied habitat unless specific information exists that documents the lack of sage-grouse use. Mapped from any combination of telemetry locations, sightings of sage grouse or sage grouse sign, local biological expertise, GIS analysis, or other data sources. This information was derived from field personnel. A variety of data capture techniques were used including the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing atvarious scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35). Update August 2012: This dataset was modified by the Bureau of Land Management as requested by CPW GIS Specialist, Karin Eichhoff. Eichhoff requested that this dataset, along with the GrSG managment zones (population range zones) dataset, be snapped to county boundaries along the UT-CO border and WY-CO border. The county boundaries dataset was provided by Karin Eichhoff. In addition, a few minor topology errors were corrected where PPH and PGH were overlapping. Update October 10, 2012: NHD water bodies greater than 100 acres were removed from GrSG habitat, as requested by Jim Cagney, BLM CO Northwest District Manager. 6 water bodies in total were removed (Hog Lake, South Delaney, Williams Fork Reservoir, North Delaney, Wolford Mountain Reservoir (2 polygons)). There were two “SwampMarsh” polygons that resulted when selecting polygons greater than 100 acres; these polygons were not included. Only polygons with the attribute “LakePond” were removed from GrSG habitat. Colorado Greater Sage Grouse managment zones based on CDOW GrSG_PopRangeZones20120609.shp. Modified and renumbered by BLM 06/09/2012. The zones were modified again by the BLM in August 2012. The BLM discovered areas where PPH and PGH were not included within the zones. Several discrepancies between the zones and PPH and PGH dataset were discovered, and were corrected by the BLM. Zones 18-21 are linkages added as zones by the BLM. In addition to these changes, the zones were adjusted along the UT-CO boundary and WY-CO boundary to be coincident with the county boundaries dataset. This was requested by Karin Eichhoff, GIS Specialist at the CPW. She provided the county boundaries dataset to the BLM. Greater sage grouse GIS data set identifying occupied, potential and vacant/unknown habitats in Colorado. The data set was created by mapping efforts of the Colorado Division of Wildlife biologist and district officers during the spring of 2004, and further refined in the winter of 2005. Occupied Habitat: Areas of suitable habitat known to be used by sage-grouse within the last 10 years from the date of mapping. Areas of suitable habitat contiguous with areas of known use, which do not have effective barriers to sage-grouse movement from known use areas, are mapped as occupied habitat unless specific information exists that documents the lack of sage-grouse use. Mapped from any combination of telemetry locations, sightings of sage grouse or sage grouse sign, local biological expertise, GIS analysis, or other data sources. Vacant or Unknown Habitat: Suitable habitat for sage-grouse that is separated (not contiguous) from occupied habitats that either: 1) Has not been adequately inventoried, or 2) Has not had documentation of grouse presence in the past 10 years Potentially Suitable Habitat: Unoccupied habitats that could be suitable for occupation of sage-grouse if practical restoration were applied. Soils or other historic information (photos, maps, reports, etc.) indicate sagebrush communities occupied these areas. As examples, these sites could include areas overtaken by pinyon-juniper invasions or converted rangelandsUpdate October 10, 2012: NHD water bodies greater than 100 acres were removed from GrSG habitat and management zones, as requested by Jim Cagney, BLM CO Northwest District Manager. 6 water bodies in total were removed (Hog Lake, South Delaney, Williams Fork Reservoir, North Delaney, Wolford Mountain Reservoir (2 polygons)). There were two “SwampMarsh” polygons that resulted when selecting polygons greater than 100 acres; these polygons were not included. Only polygons with the attribute “LakePond” were removed from GrSG habitat. Oregon submitted updated BSU boundaries in May 2016 and again in October 2016, which were incorporated into this latest version. In Oregon, the Core Area maps and data were developed as one component of the Conservation Strategy for sage-grouse. Specifically, these data provide a tool in planning and identifying appropriate mitigation in the event of human development in sage-grouse habitats. These maps will assist in making

  14. Flood Hazard Areas (DFIRM) - Kauai County

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +2more
    Updated Sep 18, 2021
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    Office of Planning (2021). Flood Hazard Areas (DFIRM) - Kauai County [Dataset]. https://opendata.hawaii.gov/dataset/flood-hazard-areas-dfirm-kauai-county
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    html, csv, geojson, kml, ogc wms, arcgis geoservices rest api, pdf, ogc wfs, zipAvailable download formats
    Dataset updated
    Sep 18, 2021
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    Office of Planning
    Area covered
    Kauai County
    Description

    [Metadata] Flood Hazard Areas for the County of Kauai - downloaded from FEMA Flood Map Service Center, May 1, 2021. 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 Datum of 1983.

    For additional information, please summary metadata https://files.hawaii.gov/dbedt/op/gis/data/s_fld_haz_ar_state.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  15. i15 Crop Mapping 2022 Provisional

    • data.cnra.ca.gov
    • data.ca.gov
    • +3more
    Updated Jan 8, 2024
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    California Department of Water Resources (2024). i15 Crop Mapping 2022 Provisional [Dataset]. https://data.cnra.ca.gov/dataset/i15-crop-mapping-2022-provisional
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    html, csv, geojson, kml, zip, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Jan 8, 2024
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    2022 STATEWIDE CROP MAPPING - PROVISIONAL

    Land use data is critically important to the work of the Department of Water Resources (DWR) and other California agencies. Understanding the impacts of land use, crop location, acreage, and management practices on environmental attributes and resource management is an integral step in the ability of Groundwater Sustainability Agencies (GSAs) to produce Groundwater Sustainability Plans (GSPs) and implement projects to attain sustainability. Land IQ was contracted by DWR to develop a comprehensive and accurate spatial land use database for the 2022 water year (WY 2022). The primary objective of this effort was to produce a spatial land use database with accuracies exceeding 95% using remote sensing, statistical, and temporal analysis methods. This project is an extension of the 2014, 2016, 2018, 2019, 2020 and 2021 land use mapping, which classified over 14 million acres of land into irrigated agriculture and urban area. Unlike the 2014 and 2016 datasets, the WY 2018, 2019, 2020, 2021 and 2022 datasets include multi-cropping and incorporates DWR ground-truth data from Siskiyou, Modoc, Lassen and Shasta counties. Land IQ integrated crop production knowledge with detailed ground truth information and multiple satellite and aerial image resources to conduct remote sensing land use analysis at the field scale. Individual fields (boundaries of homogeneous crop types representing cropped area, rather than legal parcel boundaries) were classified using a crop category legend and a more specific crop type legend. A supervised classification method using a random forest approach was used to classify delineated fields and was carried out county by county where training samples were available. Random forest approaches are currently some of the highest performing methods for data classification and regression. To determine frequency and seasonality of multiple-cropped fields, peak growth dates were determined for annual crops. Fields were attributed with DWR crop categories and included citrus/subtropical, deciduous fruits and nuts, field crops, grain and hay, idle, pasture, rice, truck crops, urban, vineyards, and young perennials. These categories represent aggregated groups of specific crop types in the Land IQ dataset. Accuracy was calculated for the crop mapping using both DWR and Land IQ crop legends. The overall accuracy result for the crop mapping statewide was 98.1% at the DWR Class level and 96.7% at the DWR Subclass level. Accuracy and error results varied among crop types. In particular, some less extensive crops that have very few validation samples may have a skewed accuracy result depending on the number and nature of validation sample points. DWR revised crops and conditions from the Land IQ classification were encoded using standard DWR land use codes added to feature attributes, and each modified classification is indicated by the value 'r' in the ‘DWR_REVISE' data field. Polygons drawn by DWR, not included in Land IQ dataset receive the 'n' code for new. Boundary change (i.e. DWR changed the boundary that LIQ delivered could be split boundary) indicated by 'b'. Each polygon classification is consistent with DWR attribute standards, however some of DWR's traditional attribute definitions are modified and extended to accommodate unavoidable constraints within remote-sensing classifications, or to make data more specific for DWR's water balance computation needs. The original Land IQ classifications reported for each polygon are preserved for comparison, and are also expressed as DWR standard attributes. Comments, problems, improvements, updates, or suggestions about local conditions or revisions in the final data set should be forwarded to the appropriate Regional Office Senior Land Use Supervisor. Revisions were made if: - DWR corrected the original crop classification based on local knowledge and analysis, -PARTIALLY IRRIGATED CROPS Crops irrigated for only part of their normal irrigation season were given the special condition of ‘X’, -In certain areas, DWR changed the irrigation status to irrigated or non-irrigated. Among those areas the special condition may have been changed to 'Partially Irrigated' based on image analysis and local knowledge, - young versus mature stages of perennial orchards and vineyards were identified (DWR added ‘Young’ to Special Condition attributes), - DWR determined that a field originally classified ‘Idle’ was actually cropped one or more times during the year, - the percent of cropped area was changed from the original acres reported by Land IQ (values indicated in DWR ‘Percent’ column), - DWR determined that the field boundary should have been split to better reflect separate crops within the same polygon and identified by a 'b' in the DWR_REVISED column, - The ‘Mixed’ was added to the MULTIUSE column refers to no boundary change, but percent of field is changed where more than one crop is found, - DWR identified a distinct early or late crop on the field before the main season crop (‘Double’ was added to the MULTIUSE column); if the 1st and 2nd sequential crops occupied different portions of the total field acreage, the area percentages were indicated for each crop). This dataset includes multicropped fields. If the field was determined to have more than one crop during the course of the water year, the order of the crops is sequential, beginning with Class 1. All single cropped fields will be placed in Class 2, so every polygon will have a crop in the Class 2 and CropType2 columns. In the case that a permanent crop was removed during the water year, the Class 2 crop will be the permanent crop followed by ‘X’ – Unclassified fallow in the Class 3 column. In the case of Intercropping, the main crop will be placed in the Class 2 column with the partial crop in the Class 3 column. The column 'MAIN_CROP' was added in 2019 and has been continued through the 2022 dataset. This column indicates which field Land IQ identified as the main season crop for the water year representing the crop grown during the dominant growing season for each county. The column ‘MAIN_CROP_DATE’, continued in the 2022 dataset, indicates the NDVI peak date for this main season crop. Asterisks (* or **) in attribute table indicates no data have been collected for that specific attribute.

    Prior to WY 2021 final mapping release, pasture areas that where mechanically harvested during a water year were classified as P6-Miscellaneous Grasses. Starting with the WY 2021 final mapping release and moving forward these harvested pasture areas are classified as P3-Mixed Pasture.

  16. U

    1 meter Digital Elevation Models (DEMs) - USGS National Map 3DEP...

    • data.usgs.gov
    • datadiscoverystudio.org
    • +4more
    Updated Feb 20, 2025
    + more versions
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    U.S. Geological Survey (2025). 1 meter Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection [Dataset]. https://data.usgs.gov/datacatalog/data/USGS:77ae0551-c61e-4979-aedd-d797abdcde0e
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    Dataset updated
    Feb 20, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

  17. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
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    U.S. Geological Survey, ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/da8c17bffecc4366ba839755687f164a/html
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  18. Flood Hazard Areas (DFIRM) - Honolulu County

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +3more
    Updated Sep 18, 2021
    + more versions
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    Office of Planning (2021). Flood Hazard Areas (DFIRM) - Honolulu County [Dataset]. https://opendata.hawaii.gov/dataset/flood-hazard-areas-dfirm-honolulu-county
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    geojson, zip, arcgis geoservices rest api, csv, html, kml, pdf, ogc wms, ogc wfsAvailable download formats
    Dataset updated
    Sep 18, 2021
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    Office of Planning
    Area covered
    Honolulu County
    Description

    [Metadata] Flood Hazard Areas for the County of Honolulu - downloaded from FEMA Flood Map Service Center, May 1, 2021. 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 Datum of 1983.

    For additional information, please summary metadata https://files.hawaii.gov/dbedt/op/gis/data/s_fld_haz_ar_state.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  19. a

    2020 Casper/Natrona Imagery

    • data-cityofcasper.opendata.arcgis.com
    • hub.arcgis.com
    Updated Aug 5, 2024
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    bgovernanti_CityofCasper (2024). 2020 Casper/Natrona Imagery [Dataset]. https://data-cityofcasper.opendata.arcgis.com/maps/029eb50e60c74c06881b1121c8616fcb
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    Dataset updated
    Aug 5, 2024
    Dataset authored and provided by
    bgovernanti_CityofCasper
    Area covered
    Description

    Web map of the imagery acquired by Fugro USA Land, Inc. in 2020 for both the Casper MPO and chosen areas of Natrona County, Wyoming. The imagery was acquired at 3-inch resolution for the Casper MPO, covering the area within the Casper Metropolitan Planning Organization boundary (MPO), and at 6-inch resolution for areas of Natrona County, covering areas of interest defined by Natrona County staff outside the Casper MPO flight acquisition area.

  20. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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U.S. Geological Survey (2024). GIS Data for Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming [Dataset]. https://catalog.data.gov/dataset/gis-data-for-geologic-map-of-the-lake-owen-quadrangle-albany-county-wyoming

GIS Data for Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming

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Dataset updated
Jul 6, 2024
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Area covered
Wyoming, Lake Owen, Albany County
Description

This U.S. Geological Survey (USGS) data release presents a digital database of geospatially enabled vector layers and tabular data transcribed from the geologic map of the Lake Owen quadrangle, Albany County, Wyoming, which was originally published as U.S. Geological Survey Geologic Quadrangle Map GQ-1304 (Houston and Orback, 1976). The 7.5-minute Lake Owen quadrangle is located in southeastern Wyoming approximately 25 miles (40 kilometers) southwest of Laramie in the west-central interior of southern Albany County, and covers most of the southern extent of Sheep Mountain, the southeastern extent of Centennial Valley, and a portion of the eastern Medicine Bow Mountains. This relational geodatabase, with georeferenced data layers digitized at the publication scale of 1:24,000, organizes and describes the geologic and structural data covering the quadrangle's approximately 35,954 acres and enables the data for use in spatial analyses and computer cartography. The data types presented in this release include geospatial features (points, lines, and polygons) with matching attribute tables, nonspatial descriptive and reference tables, and ancillary resource files for correct symbolization, in formats that conform to the Geologic Map Schema (GeMS) developed and released by the U.S. Geological Survey's National Cooperative Geologic Mapping Program (GeMS, 2020). When reconstructed from the geodatabase's vector layers and tabular data that has been symbolized according to specifications encoded in the accompanying style file, and using the supplied Federal Geographic Data Committee (FGDC) GeoAge font for labeling formations and GeoSym fonts for structural line decorations and orientation measurement symbols, this data release presents the Geologic Map as shown on the published GQ-1304 map sheet. These GIS data augment but do not supersede the information presented on GQ-1304. References: Houston, R.S., and Orback, C.J., 1976, Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming: U.S. Geological Survey Geologic Quadrangle Map GQ-1304, scale 1:24,000, https://doi.org/10.3133/gq1304. 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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