2018 USGS Lidar: Santa Barbara, CA
Data Set (DS) | OCM Partners (OCMP)GUID: gov.noaa.nmfs.inport:59332 | Updated: October 17, 2023 | Published / External
Summary
Short Citation
OCM Partners, 2025: 2018 USGS Lidar: Santa Barbara, CA, https://www.fisheries.noaa.gov/inport/item/59332.
Full Citation Examples
Geographic Extent: This dataset and derived products encompass an area covering approximately 48,766 acres of Southern California. On January 9th, 2018, heavy rains resulted in a large mudslide running down the destabilized, post-wildfire hillsides above the community of Montecito, California. In order to assist with emergency response efforts and post-landslide analysis, Quantum Spatial (QSI) utilized assets and crews in the area to rapidly collect Light Detection and Ranging (LiDAR) data on January 11th, 2018, for the Santa Barbara County Mudslide site in California. Data were collected as quickly as possible to aid in mapping the topographic and geophysical properties of the study area to support emergency response efforts, as well as future analysis of post-slide assessment.
Dataset Description: RAW flight line swaths were processed to create 236 classified LAS 1.4 files delineated in 1,000 m x 1,000 m National Grid tiles. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. Additional derived products include intensity images, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area.
Ground Conditions: Data was acquired during conditions with an absence of snow, high water, ground fog and/or clouds below the flight altitudes.
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, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.
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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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
-119.73258° W,
-119.465499° E,
34.514913° N,
34.408132° S
2018-01-11
Item Identification
Title: | 2018 USGS Lidar: Santa Barbara, CA |
---|---|
Status: | Completed |
Publication Date: | 2018-04-27 |
Abstract: |
Geographic Extent: This dataset and derived products encompass an area covering approximately 48,766 acres of Southern California. On January 9th, 2018, heavy rains resulted in a large mudslide running down the destabilized, post-wildfire hillsides above the community of Montecito, California. In order to assist with emergency response efforts and post-landslide analysis, Quantum Spatial (QSI) utilized assets and crews in the area to rapidly collect Light Detection and Ranging (LiDAR) data on January 11th, 2018, for the Santa Barbara County Mudslide site in California. Data were collected as quickly as possible to aid in mapping the topographic and geophysical properties of the study area to support emergency response efforts, as well as future analysis of post-slide assessment.
Dataset Description: RAW flight line swaths were processed to create 236 classified LAS 1.4 files delineated in 1,000 m x 1,000 m National Grid tiles. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. Additional derived products include intensity images, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area.
Ground Conditions: Data was acquired during conditions with an absence of snow, high water, ground fog and/or clouds below the flight altitudes. |
Purpose: |
The purpose of the lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the 3DEP initiative. The raw lidar point cloud data were used to create classified lidar LAS files, intensity images, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area. |
Supplemental Information: |
CONTRACTOR: Quantum Spatial, Inc. Ground Control Points were acquired and calibrated by Quantum Spatial, Inc. Data acquisition was coordinated by Quantum Spatial and all Lidar data calibration, and follow-on processing were completed by Quantum Spatial.
The following are the USGS lidar fields in JSON: {
"ldrinfo" : {
"ldrspec" : "LIDAR Base Specification, Version 1.2", "ldrsens" : "Riegl VQ-1560i", "ldrmaxnr" : "15", "ldrnps" : "0.7", "ldrdens" : "4", "ldranps" : "0.35", "ldradens" : "8", "ldrfltht" : "2100", "ldrfltsp" : "100", "ldrscana" : "58.5", "ldrscanr" : "154 lines per second", "ldrpulsr" : "500 per channel", "ldrpulsd" : "3", "ldrpulsw" : "0.899", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.18 - 0.25", "ldrswatw" : "600", "ldrswato" : "60", "ldrgeoid" : "Geoid12B" }, "ldraccur" : {
"ldrchacc" : "0.196", "rawnva" : "0.051", "rawnvan" : "22", "clsnva" : "0.087", "clsnvan" : "22", "clsvva" : "0.145", "clsvvan" : "8" }, "lasinfo" : {
"lasver" : "1.4", "lasprf" : "6", "laswheld" : "Witheld points are identified in these files using the standard LAS Witheld bits.", "lasolap" : " Swath overage points are identified in these files using the standard LAS Witheld and Overlap bits.", "lasintr" : "16", "lasclass" : {
"clascode" : "1", "clasitem" : "Processed, but Unclassified" }, "lasclass" : {
"clascode" : "2", "clasitem" : "Bare earth ground" }, "lasclass" : {
"clascode" : "7", "clasitem" : "Low Noise" }, "lasclass" : {
"clascode" : "9", "clasitem" : "Water" }, "lasclass" : {
"clascode" : "10", "clasitem" : "Ignored Ground Near Breakline" }, "lasclass" : {
"clascode" : "17", "clasitem" : "Bridge Decks" } }} |
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 |
---|---|
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 > CALIFORNIA
|
Global Change Master Directory (GCMD) Location Keywords |
VERTICAL LOCATION > LAND SURFACE
|
Instrument Keywords
Thesaurus | Keyword |
---|---|
Global Change Master Directory (GCMD) Instrument Keywords |
LIDAR > Light Detection and Ranging
|
Platform Keywords
Thesaurus | Keyword |
---|---|
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. coordinated the LiDAR acquisition and processed the data., USGS, FEMA |
Support Roles
Data Steward
Date Effective From: | 2020 |
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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: | 2020 |
---|---|
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: | 2020 |
---|---|
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: | 2020 |
---|---|
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: | -119.73258 | |
---|---|---|
E° Bound: | -119.465499 | |
N° Bound: | 34.514913 | |
S° Bound: | 34.408132 |
Extent Group 1 / Time Frame 1
Time Frame Type: | Discrete |
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Start: | 2018-01-11 |
Spatial Information
Spatial Representation
Representations Used
Grid: | No |
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Vector: | Yes |
Text / Table: | No |
TIN: | No |
Stereo Model: | No |
Video: | No |
Vector Representation 1
Point Object Present?: | Yes |
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Point Object Count: | 6816485755 |
Access Information
Security Class: | Unclassified |
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Data Access Procedure: |
Data is available online for bulk or 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: | 2020-04-20 |
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End Date: | Present |
Download URL: | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9078 |
Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2020 - 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: | 2020-04-20 |
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End Date: | Present |
Download URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/index.html |
Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2020 - Present) |
File Name: | Bulk Download |
Description: |
Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum. |
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/geoid18/9078/supplemental/extent_2018_SantaBarb_lidar_m9078.kmz |
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Name: | Browse graphic |
URL Type: |
Browse Graphic
|
File Resource Format: | KML |
Description: |
This graphic displays the footprint for this lidar data set. |
URL 3
URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/supplemental/LiDARFinalDeliveryCheck_20180502_174750.pdf |
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Name: | Dataset report |
URL Type: |
Online Resource
|
File Resource Format: | |
Description: |
Link to data set report. |
URL 4
URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/supplemental/Santa_Barbara_Mudslide_Emergency_Response_LiDAR_Technical_Data_Report_Signed.pdf |
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Name: | Dataset report |
URL Type: |
Online Resource
|
File Resource Format: | |
Description: |
Link to data set report. |
Technical Environment
Description: |
LASTools, TerraPOS, Cloudpro 1.2.4, Microstation Version 8i, TerraScan Version 17, TerraModeler Version 17, ESRI ArcGIS 10.3, Windows 7 Operating System |
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Data Quality
Vertical Positional Accuracy: |
The specifications require that Non-vegetated Vertical Accuracy (NVA) be computed from the both the raw lidar point cloud swath files and the derived DEMs. Additionally, Vegetated Vertical Accuracy (VVA) is also to be computed from the derived DEMS. The NVA was tested with 22 independent check points located in open terrain, and distributed throughout the project as feasible. These check points were not used in the calibration or post processing of the lidar point cloud data. Specifications for this project require that the NVA be 0.196 meters or better AccuracyZ at 95% confidence level. The VVA was tested with 8 independent check points located in vegetated terrain, also witheld from the calibration and post processing of the lidar point cloud data and distributed throughout the project area as feasible. Specifications for this project require that the NVA be 0.196 meters or better AccuracyZ at the 95% confidence level and that the VVA be 0.294 meters or better AccuracyZ at the 95th percentile. Quantitative value: 0.051 meters AccuracyZ at the 95 percent Confidence Interval for Raw LAS NVA. 0.087 meters AccuracyZ at the 95 percent Confidence Interval for DEM NVA., Test that produced the value: The 22 independent NVA check points were surveyed using the closed level loop technique. Elevations interpolated from the unclassified lidar surface were compared to the elevation values of the surveyed NVA check points. The RMSE was computed to be 0.026 meters resulting in an AccuracyZ at the 95% confidence level of 0.051 meters. The 22 NVA check points were also compared to the elevations of the derived bare earth DEMs. The RMSE was computed to be 0.045 meters resulting in an AccuracyZ of 0.087 meters at the 95% confidence level. NVA AccuracyZ has been tested and meets the required 0.196 meter NVA at 95% confidence level using (RMSEz * 1.9600) for both the raw lidar point cloud and derived DEMs, as defined by the National Standards for Spatial Data Accuracy (NSSDA) and herein reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines. The 8 VVA check points were also surveyed using the closed level loop technique. Elevations for these points were compared to the elevations of the derived bare earth DEMs. The RMSE was computed to be 0.091 meters resulting in an AccuracyZ of 0.145 meters at the 95th percentile. AccuracyZ has been tested on the derived bare earth DEMs and meets the required 0.294 meter VVA using the 95th percentile of the absolute value of all vertical errors in all combined vegetation classes as defined by the National Standards for Spatial Data Accuracy (NSSDA); and herein reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines. |
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Completeness Report: |
LAS files include all data points collected. No points have been removed or excluded. Shaded relief images have been visually inspected for data errors such as pits, border artifacts, and shifting. LiDAR flight lines have been examined to ensure consistent elevation values across overlapping flight lines. The raw point cloud is of good quality and data passes Vertical Accuracy specifications. |
Conceptual Consistency: |
Classified LAS files were tested by QSI for both vertical and horizontal accuracy. All data is seamless from one tile to the next, no gaps or no data areas. |
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
Sources
Base Station Control
Contact Role Type: | Originator |
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Contact Type: | Organization |
Contact Name: | Quantum Spatial |
Publish Date: | 2018-04-27 |
Extent Type: | Discrete |
Extent Start Date/Time: | 2018-04-27 |
Source Contribution: |
This data source was used (along with the airborne GPS/IMU data) to georeference the LiDAR point cloud data. |
Ground Control Quality Check Points
Contact Role Type: | Originator |
---|---|
Contact Type: | Organization |
Contact Name: | Quantum Spatial |
Publish Date: | 2018-04-27 |
Extent Type: | Discrete |
Extent Start Date/Time: | 2018-04-27 |
Source Contribution: |
This data source was used to assess the accuracy of LiDAR point cloud data. |
LiDAR RAW Data
Contact Role Type: | Originator |
---|---|
Contact Type: | Organization |
Contact Name: | Quantum Spatial |
Publish Date: | 2018-04-27 |
Extent Type: | Discrete |
Extent Start Date/Time: | 2018-01-11 |
Source Contribution: |
This data source was used to populate the LiDAR point cloud data. |
Smooth Best Estimate Trajectories
Contact Role Type: | Originator |
---|---|
Contact Type: | Organization |
Contact Name: | Quantum Spatial |
Publish Date: | 2018-04-27 |
Extent Type: | Discrete |
Extent Start Date/Time: | 2018-04-27 |
Source Contribution: |
This data source was used (along with base station control data) to georeference the LiDAR point cloud data. |
Supplemental Ground Control Points
Contact Role Type: | Originator |
---|---|
Contact Type: | Organization |
Contact Name: | Quantum Spatial |
Publish Date: | 2018-04-27 |
Extent Type: | Discrete |
Extent Start Date/Time: | 2018-04-27 |
Source Contribution: |
This data source was used to refine airborne GPS positional accuracy during the calibration process. |
Process Steps
Process Step 1
Description: |
LiDAR Pre-Processing: 1. Review flight lines and data to ensure complete coverage of the study area and positional accuracy of the laser points. 2. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. 3. 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. 4. 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 format. Convert data to orthometric elevations by applying a geoid12b correction. 5. 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. 6. 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. 7. Adjust the point cloud by comparing ground classified points to supplemental ground control points. |
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Process Date/Time: | 2018-01-11 00:00:00 |
Process Step 2
Description: |
LiDAR Post-Processing: 1. Classify data to ground and other client designated classifications using proprietary classification algorithms. 2. Manually QC data classification 3. After completion of classification and final QC approval, calculate NVA for the project using ground control quality check points and density information. |
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Process Date/Time: | 2018-04-27 00:00:00 |
Process Step 3
Description: |
Intensity Image creation: Intensity images were created for each tile from all valid first returns as 8 bit TIFFs using Quantum Spatial and ArcGIS software. |
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Process Date/Time: | 2018-01-11 00:00:00 |
Process Step 4
Description: |
Hydroflattening Breaklines and Hydroflattened DEM creation: Water boundary polygons were developed using an algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water's edge. The water's edge was then manually reviewed and edited as necessary. Elevations were assigned to the water’s edge through neighborhood statistics identifying the lowest LiDAR return from the water surface. Lakes were assigned a consistent elevation for an entire polygon while rivers were assigned consistent elevations on opposing banks and smoothed to ensure downstream flow through the entire river channel. These breaklines were incorporated into the hydro-flattened DEM by enforcing triangle edges (adjacent to the breakline) to the elevation values derived from the breakline. This implementation corrected interpolation along the hard edge. Breaklines were also used to classify all ground points within the identified water bodies to class 9 (water). |
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Process Date/Time: | 2018-01-11 00:00:00 |
Process Step 5
Description: |
NOAA OCM retrieved 236 laz files from the USGS rockyftp website for the 2018 Montecito/Santa Barbara project area. The files were in UTM Zone 11 N, NAD83(2011) coordinates in meters, and NAVD88, geoid 12B elevations in US Survey Feet. 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 Geoid 12B model, to convert to geographic coordinates, to assign the geokeys, to sort the data by gps time, and zip the data to database and to http. |
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Process Date/Time: | 2018-01-11 00:00:00 |
Process Contact: | Office for Coastal Management (OCM) |
Catalog Details
Catalog Item ID: | 59332 |
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GUID: | gov.noaa.nmfs.inport:59332 |
Metadata Record Created By: | Blake Waring |
Metadata Record Created: | 2020-04-20 08:00+0000 |
Metadata Record Last Modified By: | SysAdmin InPortAdmin |
Metadata Record Last Modified: | 2023-10-17 16:12+0000 |
Metadata Record Published: | 2022-03-16 |
Owner Org: | OCMP |
Metadata Publication Status: | Published Externally |
Do Not Publish?: | N |
Metadata Last Review Date: | 2022-03-16 |
Metadata Review Frequency: | 1 Year |
Metadata Next Review Date: | 2023-03-16 |