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Metadata Identifier: gov.noaa.csc.maps:2010_OR_DOGAMI_Yambo_m1077

Aggregation Info | Bands | Citations | Constraints | Coverage Descriptions | Dimensions | Extents | Formats | Geographic Bounding Box
Georectified Information | Georeferenceable Information | Identifiers | Instruments | Mediums | OnlineResources | Operations
Platforms | Process Steps | Range Elements | Reference Systems | Responsible Parties | Series | Sources | Spatial Grids | Temporal Extents

MD_DataIdentification

Count Component Title Abstract
1 2010 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Yambo Study Area The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for multiple areas within the State of Oregon. The areas for LiDAR collection have been designed as part of a collaborative effort of state, federal, and local agencies in order to meet a wide range of project goals. This LiDAR data set was collected in 7 delivery areas from January 3 through July 14, 2010 and encompasses portions of the following counties in Oregon: Lincoln, Polk, Tillamook and Yamhill. This data set consists of bare earth and unclassified points. The average point density is 9.17 points per square meter over terrestrial surfaces. In some areas of heavy vegetation or forest cover, there may be relatively few ground points in the LiDAR data. Elevation values for open water surfaces are not valid elevation values because few LiDAR points are returned from water surfaces. LiDAR intensity values were also collected. This LiDAR data set was collected on different dates and organized into 7 deliveries. To determine which delivery or deliveries are in your area of interest, download yambo_deliveries.pdf at: ftp://ftp.csc.noaa.gov/pub/crs/beachmap/qa_docs/or/yambo/yambo_deliveries.pdf The specific date of collection and total area covered for each delivery are listed below. Delivery 1: Date of Collection: 20100414 Total Area = 10,760 sq acres Delivery 2: Date of Collection: 20100301-20100605 Total Area = 62,451 sq acres Delivery 3: Date of Collection: 20100507-20100714 Total Area = 122,938 sq acres Delivery 4: Date of Collection: 20100103-20100527 Total Area = 97,317 sq acres Delivery 5: Date of Collection: 20100103-20100527 Total Area = 147,839 sq acres Delivery 6: Date of Collection: 20100305-20100515 Total Area = 84,277 sq acres Delivery 7: Date of Collection: 20100317-20100714 Total Area = 167,271 sq acres
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SV_Identification

none found
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CI_Citation

Count Component Title Date Citation Identifier
1 2010 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Yambo Study Area
  • 2011-12-01
1 Lidar Survey Final Report
    2 None
      1 North American Datum 1983
      • 2007-01-19
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      CI_Series

      none found
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      CI_ResponsibleParty

      Count Component Individual Organization Position Email Role Linkage
      1 resourceProvider http://www.epsg-registry.org/export.htm?gml=urn:ogc:def:crs:EPSG::4269
      1 Citation URL ftp://ftp.csc.noaa.gov/pub/crs/beachmap/qa_docs/or/yambo/Yambo_Report_All_Areas.doc
      1 NOAA CSC (originator) DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce csc.info@noaa.gov originator
      1 NOAA CSC (publisher) DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce csc.info@noaa.gov publisher
      1 NOAA CSC(distributor) DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce csc.info@noaa.gov distributor
      1 NOAA CSC (processor) DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce csc.info@noaa.gov processor
      1 EPSG Registry European Petroleum Survey Group publisher http://www.epsg-registry.org/
      1 Ian Madin DOGAMI ian.madin@dogami.state.or.us pointOfContact
      1 Mike Sutherland(author) Mike Sutherland DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce mike.sutherland@noaa.gov author
      1 Mike Sutherland Mike Sutherland DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce mike.sutherland@noaa.gov distributor
      1 Oregon Department of Geology and Mineral Industries (DOGAMI) originator
      1 Pamela Grothe DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce processor
      2 Watershed Sciences, Inc. watershedsciences.com processor
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      CI_OnlineResource

      Count Component Linkage Name Description Function
      1 ftp://ftp.csc.noaa.gov/pub/crs/beachmap/qa_docs/or/yambo/Yambo_Report_All_Areas.doc Lidar Survey Final Report information
      1 http://www.epsg-registry.org/ European Petroleum Survey Group Geodetic Parameter Registry Registry that accesses the EPSG Geodetic Parameter Dataset, which is a structured dataset of Coordinate Reference Systems and Coordinate Transformations. search
      1 http://www.epsg-registry.org/export.htm?gml=urn:ogc:def:crs:EPSG::4269 NAD83 Link to Geographic Markup Language (GML) description of reference system. information
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      MD_Identifier or RS_Identifier

      Count Component Code
      1 Ellipsoid in Meters
      1 urn:ogc:def:crs:EPSG::4269
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      EX_Extent

      Bounding Box Temporal Extent
      Count Component Description West East North South Start End
      1 -124.017166 -123.013066 45.428381 44.745281 2010-03-01 2010-07-14
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      EX_GeographicBoundingBox

      Count Component West East North South
      1 -124.017166 -123.013066 45.428381 44.745281
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      EX_TemporalExtent

      Count Component Start End
      1 2010-03-01 2010-07-14
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      MD_Format

      Count Component Name Version specification
      1 LAZ
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      MD_Medium

      none found
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      MD_Constraints

      Count Component Use Limitation
      1 Lidar Use Limitation These data depict the elevations at the time of the survey and are only accurate for that time. Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. Any conclusions drawn from analysis of this information are not the responsibility of NOAA or any of its partners. These data are NOT to be used for navigational purposes.
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      MD_ReferenceSystem

      Count Component Code Authority Title
      1 Ellipsoid Ellipsoid in Meters
      1 NAD83 urn:ogc:def:crs:EPSG::4269 North American Datum 1983
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      MD_GridSpatialRepresentation

      none found
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      MD_Georeferenceable or MI_Georeferenceable

      none found
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      MD_Georectified or MI_Georectified

      none found
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      MD_Dimension

      none found
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      MD_CoverageDescription or MI_CoverageDescription

      none found
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      MD_Band or MI_Band

      none found
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      MI_RangeElementDescription

      none found
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      MD_AggregateInformation

      Count Component Title Code Association Type Code
      1 Lidar Survey Final Report crossReference
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      LE_Source or LI_Source

      none found
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      LE_ProcessStep or LI_ProcessStep

      Count Component DateTime Description
      1 2010-01-01T00:00:00 The LiDAR data were collected between January 3 and July 14, 2010. The survey used Leica ALS60 and Leica ALS50 Phase II laser sensors mounted in multiple Cessna Caravans 208B. The systems were set to acquire greater than or equal to 105,000 laser pulses per second (i.e. 105 kHz pulse rate) and flown at 900 and 1300 meters above ground level (AGL), capturing a scan angle of plus or minus 14 degrees from nadir. These settings were developed to yield points with an average native density of greater than or equal to 8 points per square meter over terrestrial surfaces. The native pulse density is the number of pulses emitted by the LiDAR system. Some types of surfaces (i.e. dense vegetation or water) may return fewer pulses than the laser originally emitted. Therefore, the delivered density can be less than the native density and lightly variable according to distributions of terrain, land cover, and water bodies. The study area was surveyed with opposing flight line side-lap of greater than or equal to 50 percent (greater than or equal to 100 percent overlap) to reduce laser shadowing and increase surface laser painting. The system allows up to four range measurements per pulse, and all discernible laser returns were processed for the output dataset. During the LiDAR survey of the study area, static (1 Hz recording frequency) ground surveys were conducted over either known or set monuments. After the airborne survey, the static GPS data are processed using triangulation with CORS (continuously operating reference station) and checked against the Online Positioning User Service (OPUS) to quantify daily variance. Multiple sessions are processed over the same monument to confirm the antenna height measurements and reported position accuracy.
      1 2010-01-01T00:00:00 1. Laser point coordinates are computed using the IPAS and ALS Post Processor software suites based on independent data from the LiDAR system (pulse time, scan angle), and aircraft trajectory data (SBET). Laser point returns (first through fourth) are assigned an associated (x, y, z) coordinate along with unique intensity values (0-255). The data are output into large LAS v. 1.1 files; each point maintains the corresponding scan angle, return number (echo), intensity, and x, y, z (easting, northing, and elevation) information. 2. These initial laser point files are too large to process. To facilitate laser point processing, bins (polygons) are created to divide the dataset into manageable sizes (< 500 MB). Flightlines and LiDAR data are then reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. 3. Once the laser point data are imported into bins in TerraScan, a manual calibration is performed to assess the system offsets for pitch, roll, heading, and mirror scale. Using a geometric relationship developed by Watershed Sciences, each of these offsets is resolved and corrected if necessary. 4. The LiDAR points are then filtered for noise, pits, and birds by screening for absolute elevation limits, isolated points, and height above ground. Each bin is then inspected for pits and birds manually; spurious points are removed. For a bin containing approximately 7.5-9.0 million points, an average of 50-100 points are typically found to be artificially low or high. These spurious non-terrestrial laser points must be removed from the dataset. Common sources of non-terrestrial returns are clouds, birds, vapor, and haze. 5. The internal calibration is refined using TerraMatch. Points from overlapping lines are tested for internal consistency and final adjustments are made for system misalignments (i.e., pitch, roll, heading offsets and mirror scale). Automated sensor attitude and scale corrections yield 3-5 cm improvements in the relative accuracy. Once the system misalignments are corrected, vertical GPS drift is then resolved and removed per flight line, yielding a slight improvement (<1 cm) in relative accuracy. At this point in the workflow, data have passed a robust calibration designed to reduce inconsistencies from multiple sources (i.e. sensor attitude offsets, mirror scale, GPS drift) using a procedure that is comprehensive (i.e. uses all of the overlapping survey data). Relative accuracy screening is complete. 6. The TerraScan software suite is designed specifically for classifying near-ground points (Soininen, 2004). The processing sequence begins by ?removing? all points that are not ?near? the earth based on geometric constraints used to evaluate multi-return points. The resulting bare earth (ground) model is visually inspected and additional ground point modeling is performed in site-specific areas (over a 50-meter radius) to improve ground detail. This is only done in areas with known ground modeling deficiencies, such as: bedrock outcrops, cliffs, deeply incised stream banks, and dense vegetation. In some cases, ground point classification includes known vegetation (i.e., understory, low/dense shrubs, etc.) and these points are manually reclassified as non-grounds.
      1 2011-01-01T00:00:00 The NOAA Coastal Services Center (CSC) received the files in las format. The files contained LiDAR elevation and intensity measurements. The data were in Oregon Lambert (NAD83), International Feet coordinates and NAVD88 (Geoid 03) vertical datum. CSC performed the following processing for data storage and provisioning purposes: 1. The data were converted from Oregon Lambert (NAD83), International Feet coordinates to geographic coordinates. 2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid 03. 3. The vertical units of the data were converted from International feet to meters. 4. The data were sorted by latitude and the headers were updated. 5. The data were converted to LAZ format.
      1 2012-02-29T00:00:00 The NOAA National Geophysical Data Center (NGDC) received lidar data files via ftp transfer from the NOAA Coastal Services Center. The data are currently being served via NOAA CSC Digital Coast at http://www.csc.noaa.gov/digitalcoast/. The data can be used to re-populate the system. The data are archived in LAS or LAZ format. The LAS format is an industry standard for LiDAR data developed by the American Society of Photogrammetry and Remote Sensing (ASPRS); LAZ is a loseless compressed version of LAS developed by Martin Isenburg (http://www.laszip.org/). The data are exclusively in geographic coordinates (either NAD83 or ITRF94). The data are referenced vertically to the ellipsoid (either GRS80 or ITRF94), allowing for the ability to apply the most up to date geoid model when transforming to orthometric heights.
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      MI_Operation

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      MI_Platform

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      MI_Instrument

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