50173 wa2013_pslc_saddlemountain_m3675_metadata Data Set Published / External 49401 Lidar - partner (no harvest) Project Completed 2014-03-25 In October 2013, WSI, a Quantum Spatial Company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data in the fall of 2013 for the Saddle Mountain site in south-central Washington. 172,093 acres collected. Data were collected to aid the PSLC in providing complete coverage of the Saddle Mountain fault system for earthquake hazard assessment and mapping. The Saddle Mountain study area is a continuation of data collection within the greater Hanford area, and is of key importance due to its proximity to critical infrastructure and development. 10817 A footprint of this data set may be viewed in Google Earth at: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/3675/supplemental/wa2013_pslc_saddlemountain_m3675.kmz The final report for this project can be viewed at: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/3675/supplemental/wa2013_pslc_saddlemountain_m3675_surveyreport.pdf Theme ISO 19115 Topic Category elevation Theme LAZ Theme Saddle Mountain Fault Office for Coastal Management Charleston SC Data Set As Needed las LiDAR points in LAZ format (ASPRS Classes 1,2) none Any conclusions drawn from the analysis of this information are not the responsibility of Terrapoint, PSLC, NOAA, the Office for Coastal Management or its partners. Please credit the Puget Sound LiDAR Consortium (PSLC) for these data. The PSLC is supported by the Puget Sound Regional Council, the National Aeronautical and Space Administration (NASA), the United States Geological Survey (USGS) and numerous partners in local, state, and tribal government. Data Steward 2014-03-25 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Distributor 2014-03-25 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Metadata Contact 2014-03-25 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Point of Contact 2014-03-25 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Ground Condition -119.984536 -119.176177 46.8621929 46.6979498 Range 2013-11-19 2013-12-03 Yes Unclassified This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=3675 ; None 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. These data depict the heights at the time of the survey and are only accurate for that time. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=3675 Customized Download Create custom data files by choosing data area, product type, map projection, file format, datum, etc. https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/3675/index.html Bulk Download Simple download of data files. https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/3675/supplemental/wa2013_pslc_saddlemountain_m3675.kmz Browse Graphic Browse Graphic kmz This graphic shows the lidar coverage for the delivery of the 2013 Saddle Mountain lidar project. https://coast.noaa.gov Online Resource https://coast.noaa.gov/dataviewer Online Resource 2016-05-23 Date that the source FGDC record was last modified. 2017-11-14 Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details. 2018-02-08 Partial upload of Positional Accuracy fields only. 2018-03-13 Partial upload to move data access links to Distribution Info. All discernible laser returns were processed for the output dataset. The discrepancy between native and delivered density will vary depending on terrain, land cover, and the prevalence of water bodies. When collecting RTK and PPK data, the rover records data while stationary for five seconds, then calculates the pseudorange position using at least three one-second epochs. Relative errors for the position must be less than 1.5 cm horizontal and 2.0 cm vertical in order to be accepted.; Quantitative Value: 0.015 meters, Test that produced the value: GSP were collected in areas where good satellite visibility was achieved on paved roads and other hard surfaces such as gravel or packed dirt roads The mean and standard deviation (sigma) of divergence of the ground surface model from ground survey point coordinates are also considered during accuracy assessment. These statistics assume the error for x, y and z is normally distributed, and therefore the skew and kurtosis of distributions are also considered when evaluating error statistics. For the Cedar Watershed LiDAR survey, 2,345 ground survey points were collected in total resulting in an average accuracy of -0.012 feet (-0.004 meters).; Quantitative Value: 0.05 meters, Test that produced the value: FVA (1.96 * RMSE) of 0.165 ft (~5.0 cm), RMSE calculated to be 0.085 ft (~2.6 cm) LiDAR data has been collected and processed for all areas within the project study area. All areas were surveyed with an opposing flight line side-lap of more than 50 percent (more than 100 percent overlap) in order to reduce laser shadowing and increase surface laser painting. To accurately solve for laser point position (geographic coordinates x, y and z), the positional coordinates of the airborne sensor and the attitude of the aircraft were recorded continuously throughout the LiDAR data collection mission. Position of the aircraft was measured twice per second (2 Hz) by an onboard differential GPS unit, and aircraft attitude was measured 200 times per second (200 Hz) as pitch, roll and yaw (heading) from an onboard inertial measurement unit (IMU). To allow for post-processing correction and calibration, aircraft and sensor position and attitude data are indexed by GPS time. 1 The LiDAR survey was accomplished with a Leica ALS60 system mounted in a Cessna Caravan, and a Leica ALS70 system mounted in a Partenavia aircraft, yielding an average pulse density of more than 8 pulses per sq. meter over the Saddle Mountain terrain. It is not uncommon for some types of surfaces (e.g. dense vegetation or water) to return fewer pulses to the LiDAR sensor than the laser originally emitted. The discrepancy between native and delivered density will vary depending on terrain, land cover, and the prevalence of water bodies. The LiDAR data arrived to the office then QSI processing staff initiates a suite of automated and manual techniques to process the data into the requested deliverables. Processing tasks include GPS control computations, smoothed best estimate trajectory (SBET) calculations, kinematic corrections, calculation of laser point position, sensor and data calibration for optimal relative and absolute accuracy, and LiDAR point classification. 2014-03-01T00:00:00 2 1. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. 2. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with sensor head position and attitude recorded throughout the survey. 3. Calculate laser point position by associating SBET position to each laser point return time, scan angle, intensity, etc. Create raw laser point cloud data for the entire survey in *.las (ASPRS v. 1.2) format. Convert data to orthometric elevations by applying a geoid03 correction. 4. Import raw laser points into manageable blocks (less than 500 MB) to perform manual relative accuracy calibration and filter erroneous points. Classify ground points for individual flight lines 5. Using ground classified points per each flight line, test the relative accuracy. Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calculate calibrations on ground classified points from paired flight lines and apply results to all points in a flight line. Use every flight line for relative accuracy calibration. 6. Classify resulting data to ground and other client designated ASPRS classifications. Assess statistical absolute accuracy via direct comparisons of ground classified points to ground control survey data. 7. Generate bare earth models as triangulated surfaces. Generate highest hit models as a surface expression of all classified points. 2014-03-01T00:00:00 3 The NOAA Office for Coastal Management (OCM) downloaded topographic files in .txt format from PSLC's FTP site. The files contained lidar elevation, intensity, return number, class, scan angle and GPS time measurements. The data were received in Washington State Plane North Zone 4601, NAD83 coordinates and were vertically referenced to NAVD88 using the Geoid03 model. The vertical units of the data were feet. OCM performed the following processing for data storage and Digital Coast provisioning purposes: 1. The las files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid03, and from feet to meters. 2. The las files were converted from a Projected Coordinate System (WA SP South) to a Geographic Coordinate system (NAD83), converting from feet to decimal degrees. 2014-08-20T00:00:00 gov.noaa.nmfs.inport:50173 Anne Ball 2017-11-15T15:24:42 SysAdmin InPortAdmin 2022-08-09T17:11:38 2022-03-16 OCM Partners OCMP 1002 Public No No 2022-03-16 1 Year 2023-03-16