2016 USGS West Coast El-Nino Lidar (WA, OR, CA)

Towill collected approximately 75 square miles of coast in Oregon, 486 square miles of coast in Washington and California, and an additional 44 square miles for USACE defined harbors. The data was collected in a corridor approximately 500 meters wide. The nominal pulse spacing for this project was 1 point every 0.35 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground, 7-Low Noise, 9-Water, 10-Ignored Ground due to breakline proximity, 17- Bridges, 18-High Noise, 64- Flown Outside of Low Tide Window and 65- Temporal Ground. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless DEMs for the project area. The data was formatted according to the USNG tile naming convention with each tile covering an area of 1,500 meters by 1,500 meters. A total of 2377 UTM 10 DEM and LAS tiles and 487 UTM 11 DEM and LAS tiles were produced for the project.

Original contact information:

Contact Org: USGS

Title: Program Manager

Phone: (303)202-4419

Email: kyoder@usgs.gov

The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.4 format, 3D breaklines, and 0.5 meter cell size Digital Elevation Models (DEMs). All products comply with USGS Lidar Base Specification Version 1.2.

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The USGS West Coast El-Nino Lidar Project Report may be accessed here:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/6259/supplemental/west_coast_2016_el_nino_m6259_lidar_report.pdf

The USGS West Coast El-Nino Lidar Project Survey Control Report may be accessed here: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/6259/supplemental/west_coast_2016_el_nino_m6259_survey_report.pdf

Digital Elevation Models (DEMs) created from this lidar data may be custom downloaded here: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6260

Breaklines created from the lidar point data, in either gdb or gpkg format, may be accessed here: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/6259/breaklines.

The DEM and breakline products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA, OCM, or its partners.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USGS Lidar Base Specificaion v1.2",

"ldrsens" : "Optech Orion M300",

"ldrmaxnr" : "4",

"ldrnps" : "0.3",

"ldrdens" : "12",

"ldranps" : "0.3",

"ldradens" : "12",

"ldrfltht" : "800",

"ldrfltsp" : "50",

"ldrscana" : "45",

"ldrscanr" : "44",

"ldrpulsr" : "275",

"ldrpulsd" : "4",

"ldrpulsw" : "1.1",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "730",

"ldrswato" : "NA",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"

},

"ldraccur" : {

"ldrchacc" : "0.196",

"rawnva" : "0.112",

"rawnvan" : "50",

"clsnva" : "0.114",

"clsnvan" : "50",

"clsvva" : "0.211",

"clsvvan" : "42"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Withheld points were identified in these files using the standard LAS Withheld bit",

"lasolap" : "Swath overage points were identified in these files using the standard LAS overlap bit",

"lasintr" : "Scaled to 16 bit",

"lasclass" : {

"clascode" : "0",

"clasitem" : "Calibrated, never classified"

},

"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 due to breakline proximity"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge decks"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High noise"

},

"lasclass" : {

"clascode" : "64",

"clasitem" : "Flown Outside of Low Tide Window"

},

"lasclass" : {

"clascode" : "65",

"clasitem" : "Temporal Ground"

}

}}

This data was produced for the USGS according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: U.S. Geological Survey, PO Box 25046, MS 510, Denver, CO 80225. Telephone: (303) 202-4419. Any conclusions drawn from the analysis of this information are not the responsibility of USGS, NOAA, the NOAA Office for Coastal Management or its partners.

This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6259;

None

None, however, users should be aware that temporal changes may have occurred since this data set was collected and that some parts of these data may no longer represent actual surface conditions. This data was produced for the USGS according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: U.S. Geological Survey, PO Box 25046, MS 510, Denver, CO 80225. Telephone (303) 202-4419.

Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3

Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the LiDAR. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the LiDAR. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the LiDAR cannot always be tested. Lidar vendors calibrate their lidar systems during installation of the system and then again for every project acquired. Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions.

Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only three (3) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value but the results of this testing are shown below.

Using NSSDA methodology (endorsed by the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014)), horizontal accuracy at the 95% confidence level (called ACCURACYr) is computed by the formula RMSEr * 1.7308 or RMSExy * 2.448. Actual positional accuracy of this dataset was found to be RMSEx = 4.1 cm and RMSEy = 11.5 cm which equates to +/- 21.1 cm at 95% confidence level.

The vertical accuracy of the LiDAR was tested by Dewberry with 92 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain, and urban terrain (50), and vegetated terrain, including forest, brush, tall weeds, crops, and high grass (42). The vertical accuracy is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the LiDAR ground points. Checkpoints are always compared to interpolated surfaces created from the LiDAR point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete LiDAR point.

All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). Project specifications required a NVA of 19.6 cm at the 95% confidence level based on RMSEz (10 cm) x 1.9600. All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Project specifications required a VVA of 29.4 cm based on the 95th percentile. This LiDAR dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =5.8 cm, equating to +/- 11.4 cm at 95% confidence level. This LiDAR dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual VVA accuracy was found to be +/- 21.1 cm at the 95th percentile.

The 5% outliers consisted of 3 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between -52 cm and +25.9 cm.

A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. One small void in the data impacting tile 10SGD70353892 was identified. The void was accepted by USGS. An eight mile stretch of beach flown outside of the low tide window was identified. This area has been accepted by USGS. Data passes vertical accuracy specifications. There are a total of 2390 UTM 10 tiles in the tile grid but 2377 were produced for DEMs, intensity imagery, and Classified LAS due to water only tiles located within the boundary that did not have any data. There are a total of 488 UTM 11 tiles in the tile grid but 487 were produced for DEMs, intensity imagery, and Classified LAS due to a water only tile located within the boundary that did not have any data.

Data covers the entire tile scheme provided for the project area.