Kentucky Division of Geographic Information (DGI) & USGS09-2000Kentucky Single Zone 30ft DEMdigital raster data in ESRI GRID formatFrankfort
Commonwealth of Kentucky
Environmental and Public Protection Cabinet
Office of Information Services
GIS Branch
kyraster.SDE.KYDEM_10MA digital elevation model (DEM) contains a series of elevations ordered from south to north with the order of the columns from west to east. The DEM is formatted as one ASCII header record (A-record), followed by a series of profile records (B- records) each of which include a short B-record header followed by a series of ASCII integer elevations per each profile. The last physical record of the DEM is an accuracy record (C-record). The 7.5-minute DEM provides coverage in 7.5- by 7.5-minute blocks. Each product provides the same coverage as a standard USGS 7.5-minute quadrangle. Coverage is available for the contiguous United States, Hawaii, and Puerto Rico but is not complete.DEMs can be used as source data for digital orthophotos, and as layers in geographic information systems, for earth science analysis. DEMs can also serve as tools for volumetric analysis, for site location of towers, or for drainage basin delineation. These data were collected as part of the National Mapping Program.
This DEM dataset has been reprojected to the Kentucky NAD83 Single Zone Coordinate System using the interpolation method specified by NADCON (NGS).
7.5-minute DEMs have rows and columns that vary in length and are staggered. The bounding coordinates form a quadrilateral (no two sides are parallel to each other), rather than a rectangle. The user will need to pad out the uneven rows and columns with blanks or flagged data values if an application requires a rectangle. Some software vendors have incorporated this function into their software for input of standard formatted USGS DEMs.
enVariesground conditionIrregular-89.625-81.87539.25036.3753780465.0000006045015.0000003304005.0000004344855.000000noneimageryBaseMapsEarthCoverdigital terrain modelhypsographyaltitudeheightUSGSU.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D.C., National Institute of Standards and Technology.USKYNoneNone.
Commonwealth of Kentucky
Environmental and Public Protection Cabinet
Office of Information Services
GIS Branch
physical address
500 Mero Street
14th Fl CPT
FrankfortKY40601USA502-564-5174The original DEM dataset was provided by the U.S. Geological Survey in the NAD83 Kentucky North and South state plane coordinate zones.Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 2; ESRI ArcCatalog 8.1.2.671SDE Raster DatasetApplies to the original DEM: The attributes of a DEM are essentially the elevation values tied to the horizontal post positions. The accuracy of these attributes is recorded as a vertical root-mean-square error (RMSE) value in Record C of the DEM.The fidelity of the relationships encoded in the original data structure of the DEM is automatically verified using a USGS software program upon completion of the data production cycle. The test verifies full compliance to the DEM format specification.The original DEM was visually inspected for completeness on a DEM view and edit system for the purpose of performing a final quality control and, if necessary, edit of the DEM. The physical format of each digital elevation model is validated for content completeness and logical consistency during production quality control and prior to archiving in the National Digital Cartographic Data Base. Because the quadrilateral has a variable orientation in relation to the rectangular elevation grid, profiles that pass within the bounds of the DEM quadrilateral may be void of elevation grid points and, therefore may not be represented in the DEM. This condition occurs infrequently and is always the first or last profile of the data set. Level 2 DEM: Level 2 DEMs may contain void areas due to interruptions to contours in the source graphic or DLG. Void area elevation grid posts may be assigned the value of -32,767. In addition, suspect elevation areas may exist in the DEM but are not specifically identified. Suspect areas can be located on the source graphic as a disturbed surface, symbolized by contours overprinted with photo-revised or other surface pattern.Horizontal accuracy of the DEM is rarely tested or reported. For some Level-1 DEMs the horizontal accuracy of the DEM is expressed as an estimated root mean square error (RMSE). The estimate of the RMSE is based upon horizontal accuracy tests of the DEM source materials, which are selected as equal to or less than the intended horizontal RMSE error of the DEM. For DEMs without a recorded x/y RMSE, absolute horizontal accuracy can be considered the same as that for the source data and typically meets NMAS thresholds for 1:24,000-scale products (90% of points within 40 feet of true position.) No additional horizontal inaccuracy is introduced during the DEM interpolation process because the horizontal coordinates for the DEM elevation posts are derived at precisely calculated intervals. Only the vertical dimension may accrue error during the interpolation process.0.0Applies to the original DEM: The accuracy of a DEM is stated in the vertical dimension only. Test points used to measure DEM accuracy are well distributed, representative of the terrain, and have true elevations with accuracies well within the DEM accuracy criteria. Acceptable test points include, in order of preference, field control, aerotriangulated test points, spot elevations, or points on contours from existing source maps with appropriate contour intervals. A minimum of 28 test points per DEM is required to compute the RMSE, which is composed of a single test using 20 interior points and 8 edge points. Edge points are those located along, at, or near the quadrangle neatlines and are deemed by the editor to be useful for evaluating the accuracy of the edge of the DEM. The quality control units within the USGS collect test point data and compare the DEM with the quadrangle hypsography. There are three types of DEM vertical errors: blunder, systematic, and random. These errors are reduced in magnitude by editing but cannot be completely eliminated. Blunder errors are errors of major proportions and are easily identified and removed during interactive editing. Systematic errors follow some fixed pattern and are introduced by data collection procedures and systems. These errors may include vertical elevation shifts, misinterpretation of terrain surface because of trees, buildings and shadows, and fictitious ridges, tops, benches, or striations. Random errors result from unknown or accidental causes. DEMs are edited to correctly depict elevation surfaces that correspond to water bodies of specified size. Level 1 DEM: An RMSE of 7 meters or less is the desired accuracy standard. An RMSE of 15 meters is the maximum permitted. A 7.5-minute DEM at this level has an absolute elevation error tolerance of 50 meters (approximately three times the 15-meter RMSE) for blunder errors for any grid node when compared to the true elevation. Any array of points in the DEM cannot encompass more than 49 contiguous elevations in error by more than 21 meters (three times the 7-meter RMSE). Systematic errors that are within stated accuracy standards are tolerated. Level 2 DEM: A vertical RMSE of one-half of the contour interval, determined by the source map, is the maximum permitted. Systematic errors may not exceed one contour interval specified by the source graphic. Level 2 DEMs have been processed or smoothed for consistency and edited to remove identifiable systematic errors.VariesThe accuracy of Level 1 DEMs is dependent on the flying height of the photography from which the elevations were compiled and the compilation method/equipment. Accuracy for Level 1 DEMs is often measured against an independent source of elevation data and referenced to true ground (DEM Record C, element 2.) For most Level-2 DEMs, accuracy is measured and recorded as the error introduced during the process of interpolating grid post elevations from the surrounding source contours (DEM Record C, element 5.) The accuracy (to ground) of Level 2 DEMs is actually a function of the amount of error in the source contours and in the contour interpolation process. To determine the threshold of absolute error for any particular Level-2 DEM when only the error relative to source is listed in Record C, contour-source error must also be estimated. If the source contours meet NMAS, the maximum contour-source RMSE can be determined by dividing the contour interval by 3.29. Because the source error and interpolation error cannot be assumed to be independent, the final "ground" RMSE threshold is derived by adding the source-contour RMSE to the DEM-interpolation RMSE.U.S. Geological Survey200008Original DEM SourceReston, VAU.S. Geological Surveydiscvariesground conditionHydroDLGHydrographic data such as streams and shorelines were converted to 3D profiles and used, during the contour interpolation process, to enforce correct position and depiction of hydrographic features on the DEM surface. The hydrographic features were collected from USGS 7.5-minute maps and revised to digital orthophoto source current as of the date specified in metadata field Calendar Date. Because contours were not revised along with the hydrography, some discrepancy between the surface water feature and surrounding terrain may be evident in areas where significant terrain change has occurred
Commonwealth of Kentucky
Environmental and Public Protection Cabinet
Office of Information Services
GIS Branch
UnknownkydemFrankfort, KY
Commonwealth of Kentucky
Environmental and Public Protection Cabinet
Office of Information Services
GIS Branch
discvariesground conditionCONTOURContours digitized from the USGS 1:24,000 grpahic map.The production procedures, instrumentation, and hardware and software used in the collection of standard U.S. Geological Survey (USGS) digital elevation models (DEMs) vary depending on systems used at the contractor, cooperator, or National Mapping Division (NMD) production sites. This process step describes, in general, the process used in the production of standard USGS DEM data sets. Level 1 DEM: Level 1 DEMs are acquired photogrammetrically by manual profiling or image correlation techniques from National Aerial Photography Program (NAPP) or equivalent source photographs. Level 2 DEM: Level 2 DEMs are produced by converting 1:24,000-scale hypsography digital line graph (DLG) data to DEM format, or the DEMs are generated from vector data derived from scanned raster files of USGS 1:24.000-scale map series contour separates. Water body editing: DEM surface areas corresponding to water bodies are flattened and assigned map-specified or estimated surface elevations. Water body areas are defined as ponds, lakes, and reservoirs that exceed 0.5 inch at map scale and double line drainage that exceeds 0.25 inch at map scale. Water body shorelines are derived either from a hypsographic DLG or by interactive delineation from 1:24,000-scale USGS map series. Edge matching and edge joining: DEM data sets within a project area (consisting of a number of adjacent files) are edge-match and edge-join edited to ensure terrain surface continuity between files. Edge matching is the process of averaging adjacent elevation values along common edges within a zone of approximately 5 row or column grid posts on both edges. When edge values exceed three elevation units difference, edge joining is performed. Edge joining involves an extensive level of editing and requires editing elevation values that are internal to the DEM. This is done to create more accurate terrain representations by correcting the alignment of ridges and drains and to achieve overall topographic shaping within an approximately 25-30 row or column grid post zone on both edges. Quality control: DEMs are viewed on interactive editing systems to identify and correct blunder and systematic errors. DEMs are verified for physical format and logical consistency at the production centers using the Digital Elevation Model Verification System (DVS) software before they are archived in the National Digital Cartographic Data Base (NDCDB).200206Metadata imported.20051206Metadata imported.20051206Metadata imported.20080208Rastergrid cell1Varies30.00000030.000000321Upper LeftFALSELZ771pixel codesTRUEFGDBRrow and column30.030.0US survey feetNAD 83GRS_19806378137298.25722210088GCS_North_American_1983NAD_1983_Lambert_Conformal_ConicNorth American Vertical Datum 1988 (NAVD 88)0.1feetImplicit coordinateThe digital elevation model is composed of an array of elevation values, each implicitly linked to derivable grid post (discrete point) location. The DEM is a gridded representation of a topographic map hypsography overlay. Each grid post entity contains a 6-character integer value between -32,767 and 32,768.U.S. Department of the Interior, U.S. Geological Survey, 1992, Standards for Digital Elevation Models: Reston, Va.mailing addressDownloadable DataAlthough this data has been processed successfully on a computer system at the Kentucky NREPC-OIS-GIS, no warranty expressed or implied is made by the Kentucky NREPC-OIS-GIS regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty.ESRI GRIDUSGS standard DEM: The standard USGS DEM can be described as an ASCII formatted file of elevations preceded by a metadata header file which consists of one 1024 byte ACSII record and followed by one ASCII data quality record.Varies in7.182NOT AVAILABLE200206Commonwealth of Kentucky - Environmental and Public Protection Cabinet - Office of Information Services - GIS BranchBryan Bunchmailing address
500 Mero Street
14th Fl CPT
FrankfortKY40601USA502-564-5174bryan.bunch@ky.govContent Standard for Digital Geospatial MetadataFGDC-STD-001-1998local timeNoneUnclassifiedNonehttp://www.esri.com/metadata/esriprof80.htmlESRI Metadata Profileen2008020808385900FALSE20150803110536002015080311053600Published{E4155C36-E718-4F23-88D6-C7B726C72263}Ky_DEM_USGS_10M0023780465.0000006045015.0000003304005.0000004344855.0000001Local Area Networkfile://\\KYEGGISWIS01\E\ImageServerData\GDB\USGS_10M_TOPO_DEM.gdbProjectedGCS_North_American_1983Linear Unit: Foot_US (0.304801)NAD_1983_Lambert_Conformal_Conic<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.1'><WKT>PROJCS["NAD_1983_Lambert_Conformal_Conic",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",4921250.0],PARAMETER["False_Northing",3280833.333333333],PARAMETER["Central_Meridian",-85.75],PARAMETER["Standard_Parallel_1",37.08333333333334],PARAMETER["Standard_Parallel_2",38.66666666666666],PARAMETER["Latitude_Of_Origin",36.33333333333334],UNIT["Foot_US",0.3048006096012192]]</WKT><XOrigin>-117434800</XOrigin><YOrigin>-91579000</YOrigin><XYScale>36807330.96050825</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>2</ZTolerance><MTolerance>2</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem>CopyMultiple "E:\ImageServerData\GDB\USGS_10M_TOPO_DEM.gdb\Ky_DEM_USGS_10M RasterDataset" E:\ImageServerData\GDB\Ky_USGS_Legacy_DEM_Datasets.gdb Ky_DEM_USGS_10M "Ky_DEM_USGS_10M RasterDataset Ky_DEM_USGS_10M #"ElevationServices/Ky_DEM_USGS_10MimageKy_DEM_USGS_10M37804656045015434485533040051-89.775155-81.78482639.25523836.33195211-89.775155-81.78482639.25523836.331952Microsoft Windows Server 2008 R2 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.1.1.3143USGS 10-meter DEM for Kentucky. The surface of this DEM is no longer current and should not be used for analysis.
USGSDEMelevation10-meterlow resolutionlegacyUSGS 10-meter DEM for Kentucky. The surface of this DEM is no longer current and should not be used for analysis.
USGSNoneISO 19115 Geographic Information - MetadataDIS_ESRI1.0dataset002ArcSDE Connection7.182SDE Raster DatasetFile Geodatabase Raster DatasetNAD_1983_Lambert_Conformal_Conic21121130Foot_US1 Foot_US = 0.304801 Meter(s)152030Foot_US1 Foot_US = 0.304801 Meter(s)20150803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