gov.noaa.nmfs.inport:59332
eng
UTF8
dataset
Elevation
OCM Partners
resourceProvider
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
pointOfContact
2024-02-29T00:00:00
ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data
ISO 19115-2:2009(E)
point
6816485755
2018 USGS Lidar: Santa Barbara, CA
2018-04-27
publication
NOAA/NMFS/EDM
59332
https://www.fisheries.noaa.gov/inport/item/59332
WWW:LINK-1.0-http--link
Full Metadata Record
View the complete metadata record on InPort for more information about this dataset.
information
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/supplemental/Santa_Barbara_Mudslide_Emergency_Response_LiDAR_Technical_Data_Report_Signed.pdf
WWW:LINK-1.0-http--link
Dataset report
Link to data set report.
download
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/supplemental/LiDARFinalDeliveryCheck_20180502_174750.pdf
WWW:LINK-1.0-http--link
Dataset report
Link to data set report.
download
https://coast.noaa.gov/dataviewer/
WWW:LINK-1.0-http--link
NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV)
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.
download
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.
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.
Quantum Spatial, Inc. coordinated the LiDAR acquisition and processed the data., USGS, FEMA
completed
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
pointOfContact
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
custodian
notPlanned
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/supplemental/extent_2018_SantaBarb_lidar_m9078.kmz
This graphic displays the footprint for this lidar data set.
KML
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
theme
Global Change Master Directory (GCMD) Science Keywords
17.0
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CALIFORNIA
VERTICAL LOCATION > LAND SURFACE
place
Global Change Master Directory (GCMD) Location Keywords
17.0
LIDAR > Light Detection and Ranging
instrument
Global Change Master Directory (GCMD) Instrument Keywords
17.2
Airplane > Airplane
platform
Global Change Master Directory (GCMD) Platform Keywords
17.2
Lidar - partner (no harvest)
project
InPort
otherRestrictions
Cite As: OCM Partners, [Date of Access]: 2018 USGS Lidar: Santa Barbara, CA [Data Date Range], https://www.fisheries.noaa.gov/inport/item/59332.
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
otherRestrictions
Access Constraints: None
otherRestrictions
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.
otherRestrictions
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
unclassified
NOAA Data Management Plan (DMP)
NOAA/NMFS/EDM
59332
https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/59332.pdf
WWW:LINK-1.0-http--link
NOAA Data Management Plan (DMP)
NOAA Data Management Plan for this record on InPort.
information
crossReference
vector
eng; US
elevation
LASTools, TerraPOS, Cloudpro 1.2.4, Microstation Version 8i, TerraScan Version 17, TerraModeler Version 17, ESRI ArcGIS 10.3, Windows 7 Operating System
-119.73258
-119.465499
34.408132
34.514913
| Currentness: Ground Condition
2018-01-11
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"
}
}}
Zip
Zip
LAS/LAZ - LASer
Zip
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
distributor
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9078
WWW:LINK-1.0-http--link
Customized Download
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.
download
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9078/index.html
WWW:LINK-1.0-http--link
Bulk Download
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.
download
dataset
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.
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.
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.
2018-01-11T00:00:00
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.
2018-04-27T00:00:00
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.
2018-01-11T00:00:00
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).
2018-01-11T00:00:00
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.
2018-01-11T00:00:00
Office for Coastal Management
processor
Source Contribution: This data source was used (along with the airborne GPS/IMU data) to georeference the LiDAR point cloud data.
Base Station Control
2018-04-27
publication
Quantum Spatial
originator
2018-04-27
Source Contribution: This data source was used to assess the accuracy of LiDAR point cloud data.
Ground Control Quality Check Points
2018-04-27
publication
Quantum Spatial
originator
2018-04-27
Source Contribution: This data source was used to populate the LiDAR point cloud data.
LiDAR RAW Data
2018-04-27
publication
Quantum Spatial
originator
2018-01-11
Source Contribution: This data source was used (along with base station control data) to georeference the LiDAR point cloud data.
Smooth Best Estimate Trajectories
2018-04-27
publication
Quantum Spatial
originator
2018-04-27
Source Contribution: This data source was used to refine airborne GPS positional accuracy during the calibration process.
Supplemental Ground Control Points
2018-04-27
publication
Quantum Spatial
originator
2018-04-27