8 datasets found
  1. d

    Vertical Land Change, Perry County, Kentucky

    • catalog.data.gov
    • data.usgs.gov
    • +4more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Vertical Land Change, Perry County, Kentucky [Dataset]. https://catalog.data.gov/dataset/vertical-land-change-perry-county-kentucky
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Perry County, Kentucky
    Description

    The vertical land change activity focuses on the detection, analysis, and explanation of topographic change. These detection techniques include both quantitative methods, for example, using difference metrics derived from multi-temporal topographic digital elevation models (DEMs), such as, light detection and ranging (lidar), National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and Interferometric Synthetic Aperture Radar (IFSAR), and qualitative methods, for example, using multi-temporal aerial photography to visualize topographic change. The geographic study area of this activity is Perry County, Kentucky. Available multi-temporal lidar, NED, SRTM, IFSAR, and other topographic elevation datasets, as well as aerial photography and multi-spectral image data were identified and downloaded for this study area county. Available mine maps and mine portal locations were obtained from the Kentucky Mine Mapping Information System, Division of Mine Safety, 300 Sower Boulevard, Frankfort, KY 40601 at http://minemaps.ky.gov/Default.aspx?Src=Downloads. These features were used to spatially locate the study areas within Perry County. Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1950-2000 date range) and SRTM/IFSAR (2000-2008 date range). The difference rasters were evaluated to exclude difference values that were below a specified vertical change threshold, which was applied spatially by National Land Cover Dataset (NLCD) 1992 and 2006 land cover type, respectively. This spatial application of the vertical change threshold values improved the overall ability to detect vertical change because threshold values in bare earth areas were distinguished from threshold values in heavily vegetated areas. Lidar high-resolution (1.5 m) DEMs were acquired for Perry County, Kentucky from U.S. Department of Agriculture, Natural Resources Conservation Service Geospatial Data Gateway at https://gdg.sc.egov.usda.gov/GDGOrder.aspx#. ESRI Mosaic Datasets were generated from lidar point-cloud data and available topographic DEMs for the specified study area. These data were analyzed to estimate volumetric changes on the land surface at three different periods with lidar acquisitions collected for Perry County, KY on 3/29/12 to 4/6/12. A recent difference raster dataset time span (2008-2012 date range) was analyzed by differencing the Perry County lidar-derived DEM and an IFSAR-derived dataset. The IFSAR-derived data were resampled to the resolution of the lidar DEM (approximately 1-m resolution) and compared with the lidar-derived DEM. Land cover based threshold values were applied spatially to detect vertical change using the lidar/IFSAR difference dataset. Perry County lidar metadata reported that the acquisition required lidar to be collected with an average of 0.68 m point spacing or better and vertical accuracy of 15 cm root mean square error (RMSE) or better. References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf.

  2. a

    Kentucky Energy Infrastructure

    • data-bgky.hub.arcgis.com
    • data.lojic.org
    Updated May 19, 2011
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    Kentucky Geological Survey (2011). Kentucky Energy Infrastructure [Dataset]. https://data-bgky.hub.arcgis.com/datasets/kygs::kentucky-energy-infrastructure
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    Dataset updated
    May 19, 2011
    Dataset authored and provided by
    Kentucky Geological Survey
    Area covered
    Description

    People interested in Kentucky energy issues will find a new web-based service invaluable for quickly finding the locations of power plants, railroads, active coal mines, and other coal processing, handling, and transportation facilities in Kentucky. The Kentucky Department for Energy Development and Independence and the Kentucky Geological Survey (KGS) have joined to develop an interactive web map titled “Kentucky Energy Infrastructure.” The map service, created with funding from the Kentucky Coal Education grant, can be found at http://kgs.uky.edu/kgsmap/KYCoal/viewer.asp.There have been earlier printed versions of this map, but with the typical limitations of a paper map, such as fixed scale and content. The new version adds dynamic characteristics available only through a web-based resource. All data shown on the map can be downloaded in both spreadsheet and GIS format for use on a local computer.The Energy Infrastructure map gives users an overview of coal mining, processing, and utilization infrastructure in Kentucky. All of the facilities in that infrastructure are important to the state’s energy needs, as Kentucky derives more than 90% of its electric power from coal.The map service includes tools which allow a user to select a defined area, choose a level of detail, and click on mapped items, such as power plants, mines and coal-related facilities, to see information on the particular feature.Updated data will be added to the service as it becomes available, and links to external Web sites to obtain other information for an area of interest adds to the value of the site.

  3. d

    Data from: Prospect- and Mine-Related Features from U.S. Geological Survey...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the United States (ver. 10.0, May 2023) [Dataset]. https://catalog.data.gov/dataset/prospect-and-mine-related-features-from-u-s-geological-survey-7-5-and-15-minute-topographi
    Explore at:
    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States
    Description

    Version 10.0 of these data are part of a larger U.S. Geological Survey (USGS) project to develop an updated geospatial database of mines, mineral deposits, and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, have been digitized from the 7.5-minute (1:24,000, 1:25,000-scale; and 1:10,000, 1:20,000 and 1:30,000-scale in Puerto Rico only) and the 15-minute (1:48,000 and 1:62,500-scale; 1:63,360-scale in Alaska only) archive of the USGS Historical Topographic Map Collection (HTMC), or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. The compilation of 725,690 point and polygon mine symbols from approximately 106,350 maps across 50 states, the Commonwealth of Puerto Rico (PR) and the District of Columbia (DC) has been completed: Alabama (AL), Alaska (AK), Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Connecticut (CT), Delaware (DE), Florida (FL), Georgia (GA), Hawaii (HI), Idaho (ID), Illinois (IL), Indiana (IN), Iowa (IA), Kansas (KS), Kentucky (KY), Louisiana (LA), Maine (ME), Maryland (MD), Massachusetts (MA), Michigan (MI), Minnesota (MN), Mississippi (MS), Missouri (MO), Montana (MT), Nebraska (NE), Nevada (NV), New Hampshire (NH), New Jersey (NJ), New Mexico (NM), New York (NY), North Carolina (NC), North Dakota (ND), Ohio (OH), Oklahoma (OK), Oregon (OR), Pennsylvania (PA), Rhode Island (RI), South Carolina (SC), South Dakota (SD), Tennessee (TN), Texas (TX), Utah (UT), Vermont (VT), Virginia (VA), Washington (WA), West Virginia (WV), Wisconsin (WI), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the U.S., but an approximate timeline of when these activities occurred. These data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. These data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.

  4. k

    500K Geologic Formations

    • opengisdata.ky.gov
    Updated Mar 4, 2021
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    KyGovMaps (2021). 500K Geologic Formations [Dataset]. https://opengisdata.ky.gov/datasets/500k-geologic-formations/explore
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    Dataset updated
    Mar 4, 2021
    Dataset authored and provided by
    KyGovMaps
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This map document displays the 1:500,000-scale geologic map of Kentucky at scales smaller than 1:100,000, and 1:24,000-scale geological quadrangle data at larger scales. The 1:500,000-scale geologic map data were derived from the 1988 Geologic Map of Kentucky, which was compiled by Martin C. Noger (KGS) from the 1981 Geologic Map of Kentucky (Scale 1:250,000) by McDowell and others (USGS). The 1:24,000-scale geologic map data and the fault data were compiled from 707 Geological Survey 7.5-minute geologic quadrangle maps (published by Kentucky Geological Survey - U.S. Geological Survey from 1960 to 1980), which were digitized during the Kentucky Geological Survey Digital Mapping Program (1996-2006).

    Karst potential and dominant lithology are map layers derived from the geologic formations layers.

    Each layer provides a more detailed description of the data origin and method for display.

    This is used for WGS84 clients.

  5. u

    USGS Topographic Mine-related Symbols

    • colorado-river-portal.usgs.gov
    • hub.arcgis.com
    • +3more
    Updated Aug 4, 2016
    + more versions
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    U.S. Geological Survey (2016). USGS Topographic Mine-related Symbols [Dataset]. https://colorado-river-portal.usgs.gov/datasets/625k-points
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    Dataset updated
    Aug 4, 2016
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    Version 10.0 (Alaska, Hawaii and Puerto Rico added) of these data are part of a larger U.S. Geological Survey (USGS) project to develop an updated geospatial database of mines, mineral deposits, and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, have been digitized from the 7.5-minute (1:24,000, 1:25,000-scale; and 1:10,000, 1:20,000 and 1:30,000-scale in Puerto Rico only) and the 15-minute (1:48,000 and 1:62,500-scale; 1:63,360-scale in Alaska only) archive of the USGS Historical Topographic Map Collection (HTMC), or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. The compilation of 725,690 point and polygon mine symbols from approximately 106,350 maps across 50 states, the Commonwealth of Puerto Rico (PR) and the District of Columbia (DC) has been completed: Alabama (AL), Alaska (AK), Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Connecticut (CT), Delaware (DE), Florida (FL), Georgia (GA), Hawaii (HI), Idaho (ID), Illinois (IL), Indiana (IN), Iowa (IA), Kansas (KS), Kentucky (KY), Louisiana (LA), Maine (ME), Maryland (MD), Massachusetts (MA), Michigan (MI), Minnesota (MN), Mississippi (MS), Missouri (MO), Montana (MT), Nebraska (NE), Nevada (NV), New Hampshire (NH), New Jersey (NJ), New Mexico (NM), New York (NY), North Carolina (NC), North Dakota (ND), Ohio (OH), Oklahoma (OK), Oregon (OR), Pennsylvania (PA), Rhode Island (RI), South Carolina (SC), South Dakota (SD), Tennessee (TN), Texas (TX), Utah (UT), Vermont (VT), Virginia (VA), Washington (WA), West Virginia (WV), Wisconsin (WI), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the U.S., but an approximate timeline of when these activities occurred. These data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. These data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.Datasets were developed by the U.S. Geological Survey Geology, Geophysics, and Geochemistry Science Center (GGGSC). Compilation work was completed by USGS National Association of Geoscience Teachers (NAGT) interns: Emma L. Boardman-Larson, Grayce M. Gibbs, William R. Gnesda, Montana E. Hauke, Jacob D. Melendez, Amanda L. Ringer, and Alex J. Schwarz; USGS student contractors: Margaret B. Hammond, Germán Schmeda, Patrick C. Scott, Tyler Reyes, Morgan Mullins, Thomas Carroll, Margaret Brantley, and Logan Barrett; and by USGS personnel Virgil S. Alfred, Damon Bickerstaff, E.G. Boyce, Madelyn E. Eysel, Stuart A. Giles, Autumn L. Helfrich, Alan A. Hurlbert, Cheryl L. Novakovich, Sophia J. Pinter, and Andrew F. Smith.USMIN project website: https://www.usgs.gov/USMIN

  6. d

    Atlas Coal Company, Atlas Mine #1

    • datadiscoverystudio.org
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    Atlas Coal Company, Atlas Mine #1 [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/32de4ebb7e844faabf9b7d941fee8221/html
    Explore at:
    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

  7. d

    Mineral Resources Data System

    • search.dataone.org
    • data.wu.ac.at
    Updated Oct 29, 2016
    + more versions
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    U.S. Geological Survey (2016). Mineral Resources Data System [Dataset]. https://search.dataone.org/view/3e55bd49-a016-4172-ad78-7292618a08c2
    Explore at:
    Dataset updated
    Oct 29, 2016
    Dataset provided by
    USGS Science Data Catalog
    Authors
    U.S. Geological Survey
    Area covered
    Variables measured
    ORE, REF, ADMIN, MODEL, STATE, COUNTY, DEP_ID, GANGUE, MAS_ID, REGION, and 29 more
    Description

    Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

  8. f

    vfillDL: A geomorphology deep learning dataset of valley fill faces...

    • figshare.com
    bin
    Updated Mar 22, 2023
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    Aaron Maxwell (2023). vfillDL: A geomorphology deep learning dataset of valley fill faces resulting from mountaintop removal coal mining (southern West Virginia, eastern Kentucky, and southwestern Virginia, USA) [Dataset]. http://doi.org/10.6084/m9.figshare.22318522.v2
    Explore at:
    binAvailable download formats
    Dataset updated
    Mar 22, 2023
    Dataset provided by
    figshare
    Authors
    Aaron Maxwell
    License

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

    Area covered
    Southern West Virginia, West Virginia, Southwest Virginia, United States
    Description

    scripts.zip

    arcgisTools.atbx: terrainDerivatives: make terrain derivatives from digital terrain model (Band 1 = TPI (50 m radius circle), Band 2 = square root of slope, Band 3 = TPI (annulus), Band 4 = hillshade, Band 5 = multidirectional hillshades, Band 6 = slopeshade). rasterizeFeatures: convert vector polygons to raster masks (1 = feature, 0 = background).

    makeChips.R: R function to break terrain derivatives and chips into image chips of a defined size. makeTerrainDerivatives.R: R function to generated 6-band terrain derivatives from digital terrain data (same as ArcGIS Pro tool). merge_logs.R: R script to merge training logs into a single file. predictToExtents.ipynb: Python notebook to use trained model to predict to new data. trainExperiments.ipynb: Python notebook used to train semantic segmentation models using PyTorch and the Segmentation Models package. assessmentExperiments.ipynb: Python code to generate assessment metrics using PyTorch and the torchmetrics library. graphs_results.R: R code to make graphs with ggplot2 to summarize results. makeChipsList.R: R code to generate lists of chips in a directory. makeMasks.R: R function to make raster masks from vector data (same as rasterizeFeatures ArcGIS Pro tool).

    vfillDL.zip

    dems: LiDAR DTM data partitioned into training, three testing, and two validation datasets. Original DTM data were obtained from 3DEP (https://www.usgs.gov/3d-elevation-program) and the WV GIS Technical Center (https://wvgis.wvu.edu/) . extents: extents of the training, testing, and validation areas. These extents were defined by the researchers. vectors: vector features representing valley fills and partitioned into separate training, testing, and validation datasets. Extents were created by the researchers.

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U.S. Geological Survey (2024). Vertical Land Change, Perry County, Kentucky [Dataset]. https://catalog.data.gov/dataset/vertical-land-change-perry-county-kentucky

Vertical Land Change, Perry County, Kentucky

Explore at:
Dataset updated
Jul 6, 2024
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Area covered
Perry County, Kentucky
Description

The vertical land change activity focuses on the detection, analysis, and explanation of topographic change. These detection techniques include both quantitative methods, for example, using difference metrics derived from multi-temporal topographic digital elevation models (DEMs), such as, light detection and ranging (lidar), National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and Interferometric Synthetic Aperture Radar (IFSAR), and qualitative methods, for example, using multi-temporal aerial photography to visualize topographic change. The geographic study area of this activity is Perry County, Kentucky. Available multi-temporal lidar, NED, SRTM, IFSAR, and other topographic elevation datasets, as well as aerial photography and multi-spectral image data were identified and downloaded for this study area county. Available mine maps and mine portal locations were obtained from the Kentucky Mine Mapping Information System, Division of Mine Safety, 300 Sower Boulevard, Frankfort, KY 40601 at http://minemaps.ky.gov/Default.aspx?Src=Downloads. These features were used to spatially locate the study areas within Perry County. Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1950-2000 date range) and SRTM/IFSAR (2000-2008 date range). The difference rasters were evaluated to exclude difference values that were below a specified vertical change threshold, which was applied spatially by National Land Cover Dataset (NLCD) 1992 and 2006 land cover type, respectively. This spatial application of the vertical change threshold values improved the overall ability to detect vertical change because threshold values in bare earth areas were distinguished from threshold values in heavily vegetated areas. Lidar high-resolution (1.5 m) DEMs were acquired for Perry County, Kentucky from U.S. Department of Agriculture, Natural Resources Conservation Service Geospatial Data Gateway at https://gdg.sc.egov.usda.gov/GDGOrder.aspx#. ESRI Mosaic Datasets were generated from lidar point-cloud data and available topographic DEMs for the specified study area. These data were analyzed to estimate volumetric changes on the land surface at three different periods with lidar acquisitions collected for Perry County, KY on 3/29/12 to 4/6/12. A recent difference raster dataset time span (2008-2012 date range) was analyzed by differencing the Perry County lidar-derived DEM and an IFSAR-derived dataset. The IFSAR-derived data were resampled to the resolution of the lidar DEM (approximately 1-m resolution) and compared with the lidar-derived DEM. Land cover based threshold values were applied spatially to detect vertical change using the lidar/IFSAR difference dataset. Perry County lidar metadata reported that the acquisition required lidar to be collected with an average of 0.68 m point spacing or better and vertical accuracy of 15 cm root mean square error (RMSE) or better. References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf.

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