2019 WA DNR Lidar: San Juan County, WA
Data Set (DS) | OCM Partners (OCMP)GUID: gov.noaa.nmfs.inport:67199 | Updated: July 26, 2024 | Published / External
Summary
Short Citation
OCM Partners, 2024: 2019 WA DNR Lidar: San Juan County, WA, https://www.fisheries.noaa.gov/inport/item/67199.
Full Citation Examples
No metadata record was provided with the data. This record is populated with information from the Quantum Spatial, Inc. technical report downloaded from the Washington Dept. of Natural Resources Washington Lidar Portal. The technical report is available for download from the link provided in the URL section of this metadata record.
Washington Department of Natural Resources (WA DNR) contracted with Quantum Spatial, Inc. (QSI) in January 2019 to collect Light Detection and Ranging (LiDAR) data for the 2019 San Juan County LiDAR study area. A total of 128,731 acres of 8 pulses per square meter (PPSM) LiDAR data were acquired and delivered to the client. The data were collected between March 2 and March 21, 2019 and delivered to Washington DNR on June 14, 2019.
In addition to these lidar point data, the bare earth Digital Elevation Models (DEM) created from the lidar point data are also available. These data are available for custom download at the link provided in the URL section of this metadata record.
Distribution Information
-
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.
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LAS/LAZ - LASer
Bulk download of data files in LAZ format, in geographic coordinates and orthometric heights in meters.
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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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.
Controlled Theme Keywords
COASTAL ELEVATION, elevation, TERRAIN ELEVATION
Child Items
No Child Items for this record.
Contact Information
Point of Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202
https://coast.noaa.gov
Metadata Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202
https://coast.noaa.gov
Extents
-123.238792° W,
-122.740526° E,
48.790179° N,
48.413671° S
2019-03-02 - 2019-03-04
2019-03-21
Item Identification
Title: | 2019 WA DNR Lidar: San Juan County, WA |
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Status: | Completed |
Creation Date: | 2019 |
Abstract: |
No metadata record was provided with the data. This record is populated with information from the Quantum Spatial, Inc. technical report downloaded from the Washington Dept. of Natural Resources Washington Lidar Portal. The technical report is available for download from the link provided in the URL section of this metadata record. Washington Department of Natural Resources (WA DNR) contracted with Quantum Spatial, Inc. (QSI) in January 2019 to collect Light Detection and Ranging (LiDAR) data for the 2019 San Juan County LiDAR study area. A total of 128,731 acres of 8 pulses per square meter (PPSM) LiDAR data were acquired and delivered to the client. The data were collected between March 2 and March 21, 2019 and delivered to Washington DNR on June 14, 2019. In addition to these lidar point data, the bare earth Digital Elevation Models (DEM) created from the lidar point data are also available. These data are available for custom download at the link provided in the URL section of this metadata record. |
Purpose: |
LiDAR data will be used by the County and distributed by DNR. |
Keywords
Theme Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Science Keywords |
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
|
Global Change Master Directory (GCMD) Science Keywords |
EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
|
ISO 19115 Topic Category |
elevation
|
Spatial Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Location Keywords |
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
|
Global Change Master Directory (GCMD) Location Keywords |
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > WASHINGTON
|
Global Change Master Directory (GCMD) Location Keywords |
VERTICAL LOCATION > LAND SURFACE
|
Instrument Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Instrument Keywords |
LIDAR > Light Detection and Ranging
|
Platform Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Platform Keywords |
Airplane > Airplane
|
Physical Location
Organization: | Office for Coastal Management |
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City: | Charleston |
State/Province: | SC |
Data Set Information
Data Set Scope Code: | Data Set |
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Data Set Type: | Elevation |
Maintenance Frequency: | None Planned |
Data Presentation Form: | Model (digital) |
Distribution Liability: |
Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners. |
Data Set Credit: | Quantum Spatial, Inc., Washington Dept. of Natural Resources |
Support Roles
Data Steward
Date Effective From: | 2022 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Distributor
Date Effective From: | 2022 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Metadata Contact
Date Effective From: | 2022 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Point of Contact
Date Effective From: | 2022 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Extents
Currentness Reference: | Ground Condition |
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Extent Group 1
Extent Group 1 / Geographic Area 1
W° Bound: | -123.238792 | |
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E° Bound: | -122.740526 | |
N° Bound: | 48.790179 | |
S° Bound: | 48.413671 |
Extent Group 1 / Time Frame 1
Time Frame Type: | Range |
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Start: | 2019-03-02 |
End: | 2019-03-04 |
Extent Group 1 / Time Frame 2
Time Frame Type: | Discrete |
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Start: | 2019-03-21 |
Spatial Information
Spatial Representation
Representations Used
Vector: | Yes |
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Reference Systems
Reference System 1
Coordinate Reference System |
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Access Information
Security Class: | Unclassified |
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Data Access Procedure: |
Data is available online for bulk and custom downloads. |
Data Access Constraints: |
None |
Data Use Constraints: |
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. |
Distribution Information
Distribution 1
Start Date: | 2021-07-15 |
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End Date: | Present |
Download URL: | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9495/details/9495 |
Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2022 - Present) |
File Name: | Customized Download |
Description: |
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options. |
File Type (Deprecated): | Zip |
Compression: | Zip |
Distribution 2
Start Date: | 2021-07-15 |
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End Date: | Present |
Download URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9495/index.html |
Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2022 - Present) |
File Name: | Bulk Download |
Description: |
Bulk download of data files in LAZ format, in geographic coordinates and orthometric heights in meters. |
File Type (Deprecated): | LAZ |
Distribution Format: | LAS/LAZ - LASer |
Compression: | Zip |
URLs
URL 1
URL: | https://coast.noaa.gov/dataviewer/ |
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Name: | NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) |
URL Type: |
Online Resource
|
File Resource Format: | HTML |
Description: |
The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer. |
URL 2
URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9495/supplemental/wa2019_sanjuan_m9495.kmz |
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Name: | Browse graphic |
URL Type: |
Browse Graphic
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File Resource Format: | KML |
Description: |
This graphic displays the footprint for this lidar data set. |
URL 3
URL: | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9496/details/9496 |
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Name: | Custom DEM Download |
URL Type: |
Online Resource
|
File Resource Format: | Zip |
Description: |
Link to custom download, from the Data Access Viewer (DAV), the raster Digital Elevation Model (DEM) data that were created from this lidar data set. |
URL 4
URL: | https://coast.noaa.gov/lidar/viewer/v/noaapotree.html?m=9495&g=geoid18 |
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Name: | Potree 3D View |
URL Type: |
Online Resource
|
Description: |
Link to view the point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer. |
URL 5
URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/entwine/geoid18/9495/ept.json |
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Name: | Entwine Point Tiles (EPT) |
URL Type: |
Online Resource
|
File Resource Format: | json |
Description: |
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud. |
URL 6
URL: | https://lidarportal.dnr.wa.gov/download?ids=1329 |
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Name: | Lidar Report |
URL Type: |
Online Resource
|
File Resource Format: | |
Description: |
Link to the Quantum Spatial, Inc. Technical Lidar Report from the Washington Lidar Portal. |
Data Quality
Vertical Positional Accuracy: |
Vertical Accuracy reporting is designed to meet guidelines presented in the National Standard for Spatial Data Accuracy (NSSDA) (FGDC, 1998) and the ASPRS Guidelines for Vertical Accuracy Reporting for LiDAR Data v 1.0 (ASPRS, 2014). The statistical model compares known GSPs to the closest laser point. Vertical accuracy statistical analysis uses ground survey points in open areas where the LiDAR system has a very high probability that the sensor will measure the ground surface and is evaluated at the 95th percent confidence level. For the 2019 San Juan County LiDAR study area, a total of 1,528 GSPs were collected and used for calibration of the LiDAR data. An additional 81 reserved ground survey points were collected for independent verification. Reserved ground survey points were tested against final LiDAR data, resulting in an RMSE of 0.047 meters, and non-vegetated vertical accuracy (NVA) of 0.092 meters (derived according to NSSDA, using 0.047 m (RMSEz) x 1.96000). The vertical accuracy requirement for this project was 9 cm RMSE. Vegetated vertical accuracy (VVA) testing was required for the San Juan County project, though a VVA requirement was not specified. The VVA tested 0.292 m at the 95th percentile using National Digital Elevation Program (NDEP)/ASPRS Guidelines against the DEM using 9 VVA points. |
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Quality Control Procedures Employed: |
QSI has high standards and adheres to best practices in all efforts. In the laboratory, quality checks are built in throughout processing steps, and automated methodology allows for rapid data processing. QSI's innovation and adaptive culture rises to technical challenges and the needs of clients like Washington DNR. Reporting and communication to our clients are prioritized through regular updates and meetings. |
Data Management
Have Resources for Management of these Data Been Identified?: | Yes |
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Approximate Percentage of Budget for these Data Devoted to Data Management: | Unknown |
Do these Data Comply with the Data Access Directive?: | Yes |
Actual or Planned Long-Term Data Archive Location: | NCEI-CO |
How Will the Data Be Protected from Accidental or Malicious Modification or Deletion Prior to Receipt by the Archive?: |
Data is backed up to tape and to cloud storage. |
Lineage
Lineage Statement: |
The NOAA Office for Coastal Management (OCM) downloaded the LAZ files from the Washington Lidar Portal. |
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Sources
Washington Dept of Natural Resources
Contact Role Type: | Originator |
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Contact Type: | Organization |
Contact Name: | Washington Dept of Natural Resources |
Citation URL: | https://lidarportal.dnr.wa.gov/ |
Citation URL Name: | Washington Lidar Portal |
Process Steps
Process Step 1
Description: |
Planning: Flightlines were developed using Mission Pro software. Careful planning of the pulse rate, flight altitude, and ground speed ensured that data quality and coverage conditions were met while optimizing flight paths and ensuring the necessary pulse density of greater than eight points per square meter. The known factors were prepared for, such as: GPS constellation availability, acquisition windows, and resource allocation. In addition, a variety of logistical barriers were anticipated, namely private property access and acquisition personnel logistics. Finally, weather hazards and conditions affecting flight were continuously monitored due to their impact on the daily success of airborne and ground operations. |
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Process Step 2
Description: |
Geospatial Corrections of Aircraft Positional Data PP-RTX To improve precision and accuracy of the aircraft trajectory, the latest generation of Global Navigation Satellite System (GNSS) satellites and recent advances in GNSS post-processing technology have made possible trajectory processing methods that do not require conventional base support: specifically, Trimble CenterPoint Post-Processed Real-Time Extended (PP-RTX). PP-RTX using Applanix POSPac MMS software leverages near real-time atmospheric models from Trimble's extensive worldwide network of continuously operating base stations to produce highly accurate trajectories. When utilized properly and sufficiently controlled by a ground survey during post-processing, PP-RTX has the following advantages over conventional collection methods: Agility: The airborne acquisition is untethered by access constraints of the ground survey team at the time of acquisition, particularly in remote areas that lack permanent base stations. Flexibility: The airborne acquisition team can instantly shift collection priorities based on weather and client needs without waiting for a ground survey team to relocate. Accuracy: If properly controlled with a ground survey and datum adjustment during post-processing, PP-RTX produces results at least as accurate as conventional methods utilizing base stations. |
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Process Step 3
Description: |
Ground Survey Points The ground survey for the WA DNR San Juan County project was conducted between March 10 and March 19, 2019. Ground survey data were used for data calibration and accuracy assessment purposes. Ground survey points (GSPs) were collected using real time kinematic (RTK), post-processed kinematic (PPK), and Fast Static (FS) techniques. For RTK surveys, a base receiver was positioned at a nearby monument to broadcast a kinematic correction to a roving receiver; for PPK and FS surveys, however, these corrections were post-processed. RTK and PPK surveys recorded observations for a minimum of five seconds on each GCP/GSP in order to support longer baselines for post-processing; FS surveys record observations for up to fifteen minutes on each point in order to support longer baselines for postprocessing. All GSP measurements were made during periods with a Position Dilution of Precision (PDOP) no greater than 3.0 and in view of at least six satellites for both receivers. Relative errors for the position were requred to be less than 1.5 centimeters horizontal and 2.0 centimeters vertical in order to be accepted. Base Stations Base stations were utilized for collection of GSPs and selected with consideration for satellite visibility, field crew safety, and optimal location for GSP coverage. A combination of Leica SmartNet Real-Time Network (RTN) base stations, Washington State Reference Network (WSRN) RTN base stations, and QSI-established monuments were utilized for this project. New monumentation was set using magnetic survey nails. |
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Process Step 4
Description: |
Airborne Survey All data for the 2019 San Juan County project area were flown between March 2 and March 21, 2019 utilizing a Riegl LMS -Q1560 sensor mounted in a Piper Navajo twin-engine turbine aircraft. The LiDAR system for Riegl LMS-Q1560 sensor was set to acquire greater than or equal to 800,000 laser pulses per second (i.e. 800 kHz pulse rate; 400 kHz per channel) and flown at 1400 meters above ground level (AGL), capturing a 58.5 degree field of view. These settings and flight parameters are developed to yield points with an average native density of greater than or equal to 8 over terrestrial surfaces. The native pulse density is the number of pulses emitted by the LiDAR system. Some types of surfaces (e.g., 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 vary 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 60% (greater than or equal to 100% overlap) for Riegal LMS-Q1560 sensor to reduce laser shadowing and increase surface laser painting. The system allows for an unlimited number of LiDAR return measurements per pulse, and all discernible laser returns were processed for the output data set. The LiDAR sensor operators constantly monitored the data collection settings during acquisition of the data, including pulse rate, power setting, scan rate, gain, field of view, and pulse mode. For each flight the crew performed airborne calibration maneuvers designed to improve the calibration results during the data processing stage. The LiDAR coverage was completed with no data gaps or voids, barring non-reflective surfaces (e.g., open water, wet asphalt). All necessary measures were taken to acquire data under conditions (e.g., minimum cloud decks, no snow on the ground) and in a manner (e.g., adherence to flight plans) that prevented the possibility of data gaps. All QSI LiDAR systems are calibrated per the manufacturer and our own specifications, and tested by QSI for internal consistency among every mission using proprietary methods. To solve for laser point position, an accurate description of aircraft position and attitude is vital. Aircraft position is described as x, y, and z and was measured twice per second (two hertz) by an on-board differential GPS unit. Aircraft attitude is described as pitch, roll, and yaw (heading) and was measured 200 times per second (200 hertz) from an onboard inertial measurement unit (IMU). Weather conditions were constantly assessed in flight, as adverse conditions not only affect data quality, but can prove unsafe for flying. |
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Process Step 5
Description: |
Once the LiDAR data arrived in the laboratory, QSI employed a suite of automated and manual techniques for processing tasks. Processing tasks included: GPS, kinematic corrections, calculation of laser point position, relative accuracy testing, classification of ground and non-ground points, and assessments of statistical absolute accuracy. The general workflow for calibration of the LiDAR data was as follows: Resolve GNSS kinematic corrections for aircraft position data using kinematic aircraft GNSS (collected at 2Hz) and IMU (collected at 200Hz) data with Trimble CenterPoint PP-RTX methodologies. Used POSGNSS, PosPac MMS Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with attitude data. Sensor heading, position, and attitude are calculated throughout the survey. Used POSGNSS, PosPac MMS Calculate laser point position by associating SBET position to each laser point return time, with offsets relative to scan angle, intensity, etc. This process creates the raw laser point cloud data for the entire survey in *.las (ASPRS v 1.2) format, in which each point maintains the corresponding scan angle, return number (echo), intensity, and x, y, z information. These data are converted to orthometric elevation (NAVD88 & NGVD29) by applying a Geoid correction. Used RiProcess and RiWorld Test relative accuracy using ground classified points per each flight line. Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale), and GNSS/IMU drift. Calibrations are performed on ground classified points from paired flight lines. Every flight line is used for relative accuracy calibration. Used TerraMatch, TerraScan, QSI Proprietary Software Assess NVA via direct comparisons of ground classified points to ground RTK survey data. Point classifications are assigned for features of interest via a combination of QSI custom algorithms and manual inspection. Used TerraScan, TerraMatch, Trimble Business Center |
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Process Step 6
Description: |
The NOAA Office for Coastal Management (OCM) downloaded this data set from the Washington Lidar Portal. The total number of files downloaded and processed was 1374. No metadata record was provided with the data. This record is populated with information from the Quantum Spatial, Inc. technical report downloaded from the Washington Dept. of Natural Resources Washington Lidar Portal. The technical report is available for download from the Washington Lidar Portal. The link is provided in the URL section of this metadata record. The data were in Washington State Plane South (NAD83 HARN), US survey feet coordinates and NAVD88 (Geoid12B) elevations in feet. From the provided report, the data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 17 - Bridge Deck. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available in the DAV are: 1, 2, 7, 9, 17. NOAA OCM noted that there are lidar points that fall in the water along the islands coastlines that are classified as ground. OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges. 2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid12B model, to convert from Washington State Plane South (NAD83 HARN), US survey feet coordinates to geographic coordinates, to convert from elevations in feet to meters, to assign the geokeys, to sort the data by gps time and zip the data to database and to the Amazon s3 bucket. |
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Process Date/Time: | 2022-05-10 00:00:00 |
Process Contact: | Office for Coastal Management (OCM) |
Related Items
Item Type | Relationship Type | Title |
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Data Set (DS) | Cross Reference |
2019 WA DNR Lidar DEM: San Juan County, WA |
Catalog Details
Catalog Item ID: | 67199 |
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GUID: | gov.noaa.nmfs.inport:67199 |
Metadata Record Created By: | Rebecca Mataosky |
Metadata Record Created: | 2022-05-06 17:47+0000 |
Metadata Record Last Modified By: | Rebecca Mataosky |
Metadata Record Last Modified: | 2024-07-26 19:40+0000 |
Metadata Record Published: | 2022-07-21 |
Owner Org: | OCMP |
Metadata Publication Status: | Published Externally |
Do Not Publish?: | N |
Metadata Last Review Date: | 2022-07-21 |
Metadata Review Frequency: | 1 Year |
Metadata Next Review Date: | 2023-07-21 |