gov.noaa.nmfs.inport:50159
eng
UTF8
dataset
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)
NAD83(NSRS2007)
2008-11-12
publication
European Petroleum Survey Group
https://apps.epsg.org/api/v1/CoordRefSystem/4759/export/?format=gml
urn:ogc:def:crs:EPSG:4759
6.18.3
North American Vertical Datum of 1988 (NAVD88) (GEOID18) meters
North American Vertical Datum of 1988 (NAVD88) (GEOID18) meters
https://apps.epsg.org/api/v1/VerticalCoordRefSystem/5703/?api_key=gml
North American Vertical Datum of 1988 (NAVD88) (GEOID18) meters
Link to Geographic Markup Language (GML) description of reference system.
information
resourceProvider
European Petroleum Survey Group
https://www.epsg.org/
European Petroleum Survey Group Geodetic Parameter Registry
Registry that accesses the EPSG Geodetic Parameter Dataset, which is a structured dataset of Coordinate Reference Systems and Coordinate Transformations.
search
publisher
vertical
OGP
2006-11-28
false
urn:ogc:def:cs:EPSG::6499
Vertical CS. Axis: height (H). Orientation: up. UoM: meter.
Used in vertical coordinate reference systems.
urn:ogc:def:axis:EPSG::114
H
up
urn:ogc:def:crs:EPSG::5703
2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Snohomish River Estuary
wa2009_pslc_snohomishriverestuary_m2590_metadata
2013-11-14
publication
NOAA/NMFS/EDM
50159
https://www.fisheries.noaa.gov/inport/item/50159
WWW:LINK-1.0-http--link
Full Metadata Record
View the complete metadata record on InPort for more information about this dataset.
information
https://coast.noaa.gov/dataviewer
WWW:LINK-1.0-http--link
Citation URL
Online Resource
download
https://coast.noaa.gov
WWW:LINK-1.0-http--link
Citation URL
Online Resource
download
Watershed Sciences, Inc. (WS) co-acquired Light Detection and Ranging (LiDAR) data and Truecolor
Orthophotographs of the Snohomish River Estuary, WA on July 20 & 21, 2009. The
original requested survey area (26,150 acres) was expanded, at the client's request, to
include more of the valley lowland areas in the SW and SE edge of the original AOI as well as
additional creeks on the northern edge of the survey (Figure 1). The total area of delivered
LiDAR and True-color Orthophotographs, including the expansion and 100 m buffer, is 32,140 acres.
This data set is an LAZ (compressed LAS) format file containing LIDAR point cloud data.
The LAS files can be used to create DEMs and also to extract topographic data in software that
does not support raster data. Other surface features can also be extracted with custom
applications.
LiDAR data has a wide range of uses such as earthquake hazard studies, hydrologic modeling,
forestry, coastal engineering, roadway and pipeline engineering, flood plain mapping,
wetland studies, geologic studies and a variety of analytical and cartographic projects.
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.
The custom download may be cited as National Oceanic and Atmospheric Administration (NOAA) Digital Coast Data Access Viewer. Charleston, SC: NOAA Office for Coastal Management. Accessed Mar 01, 2024 at https://coast.noaa.gov/dataviewer.
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
asNeeded
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2590/supplemental/wa2009_pslc_snohomishriverestuary.KMZ
This graphic shows the lidar coverage for the 2009 Snohomish River Estuary collection area in Washington.
kmz
LAZ
theme
Lidar - partner (no harvest)
project
InPort
otherRestrictions
Cite As: OCM Partners, [Date of Access]: 2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Snohomish River Estuary [Data Date Range], https://www.fisheries.noaa.gov/inport/item/50159.
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. These data depict the heights at the time of the survey and are only accurate for that time.
otherRestrictions
Distribution Liability: 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.
unclassified
NOAA Data Management Plan (DMP)
NOAA/NMFS/EDM
50159
https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/50159.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
-122.2683624
-122.0545681
47.85093689
48.06306836
| Currentness: Ground Condition
2009-07-20
2009-07-21
A footprint of this data set may be viewed in Google Earth at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2590/supplemental/wa2009_pslc_snohomishriverestuary.KMZ
Reports explaining collection and quality assurance is available at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2590/supplemental/wa2009_pslc_snohomishriverestuary.pdf
false
eng
false
none
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=2590
WWW:LINK-1.0-http--link
Customized Download
Create custom data files by choosing data area, product type, map projection, file format, datum, etc.
download
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2590/index.html
WWW:LINK-1.0-http--link
Bulk Download
Simple download of data files.
download
dataset
Accuracy
Elevations are recorded in floating-point meters and the vertical datum is ellipsoidal (GEOID03).
Horizontal Positional Accuracy
Horizontal positional accuracy for LiDAR is dependent upon
the quality of the GPS/INS solution, sensor calibration and ground conditions at the time of
data capture. The standard system results for horizontal accuracy are less than 1 meter.
; Quantitative Value: 1.0 meters, Test that produced the value: Lidar horizontal accuracy was not reported.
Vertical Positional Accuracy
To enable assessment of LiDAR data accuracy, ground truth points were collected using GPS
based real-time kinematic (RTK) surveying. For an RTK survey, the ground crew uses a roving
unit to receive radio-relayed corrected positional coordinates for all ground points from a GPS
base station set up over a survey control monument. Instrumentation includes multiple
Trimble DGPS units (R8). RTK surveying allows for precise location measurements with an
error (s) of = 1.5 cm (0.6 in). Figure 2 below portrays a distribution of hard surface RTK point
locations used for the survey areas. Additional RTK surveys were taken by Watershed
Sciences (in low grass vegetation) and the client (in high marsh vegetation) to compare
absolute accuracy amongst land covers; this data is presented in Table 4.
To assess spatial accuracy of the orthophotographs they are compared against control points
identified from the LIDAR intensity images. The control points were collected\measured on
surface features such as painted road-lines, and boulders in the stream beds. The accuracy of
the final mosaic, expressed as root mean square error (RMSE), was calculated in relation to
the LiDAR-derived control points. Figure 3 displays the co-registration between
orthorectified photographs and LiDAR intensity images.
; Quantitative Value: 0.03 meters, Test that produced the value:
The vertical accuracy of the LiDAR data is described as the mean and standard deviation
(sigma ~ s) of divergence of LiDAR point coordinates from RTK ground survey point
coordinates. To provide a sense of the model predictive power of the dataset, the root mean
square error (RMSE) for vertical accuracy is also provided.
Completeness Report
LiDAR data has been collected and processed for all areas within the project study area.
Conceptual Consistency
LiDAR flight lines have been examined to ensure that there was at least 50% sidelap, there are no gaps between flightlines,
and overlapping flightlines have consistent elevation values.
Shaded relief images have been visually inspected for data errors such as pits, border artifacts, gaps, and shifting.
Point Generation. The points are generated as Terrascan binary Format using Terrapoint's
proprietary Laser Postprocessor Software.
This software combines the Raw Laser file and GPS/IMU information to generate a point cloud for each
individual flight. All the point cloud files encompassing the project area were then divided into
quarter quad tiles. The referencing system of these tiles is based upon the project boundary minimum
and maximums. This process is carried out in Terrascan.
The bald earth is subsequently extracted from the raw LiDAR points using Terrascan in a
Microstation environment. The automated vegetation removal process takes place by building an
iterative surface model. This surface model is generated using three main parameters:
Building size, Iteration angle and Iteration distance.
The initial model is based upon low points selected by a roaming window and are
assumed to be ground points. The size of this roaming window is determined by the
building size parameter. These low points are triangulated and the remaining points
are evaluated and subsequently added to the model if they meet the Iteration angle and
distance constraints (fig. 1). This process is repeated until no additional points are
added within an iteration.
There is also a maximum terrain angle constraint that determines the maximum
terrain angle allowed within the model.
Multiple process dates, report compiled 20050331.
Applications and Work Flow Overview
1. Resolved kinematic corrections for aircraft position data using kinematic aircraft GPS and static
ground GPS data.
Software: Waypoint GPS v.8.10, Trimble Geomatics Office v.1.62
2. Developed a smoothed best estimate of trajectory (SBET) file that blends post-processed
aircraft position with attitude data Sensor head position and attitude were calculated
throughout the survey. The SBET data were used extensively for laser point processing.
Software: IPAS v.1.4
3. Calculated laser point position by associating SBET position to each
laser point return time, scan angle, intensity, etc. Created raw laser
point cloud data for the entire survey in *.las (ASPRS v1.1) format.
Software: ALS Post Processing Software v.2.69
4. Imported raw laser points into manageable blocks (less than 500 MB) to perform manual
relative accuracy calibration and filter for pits/birds. Ground points were then classified for
individual flight lines (to be used for relative accuracy testing and calibration).
Software: TerraScan v.9.001
5. Using ground classified points per each flight line, the relative accuracy was tested.
Automated line-to-line calibrations were then performed for system attitude parameters
(pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calibrations were performed on
ground classified points from paired flight lines. Every flight line was used for relative
accuracy calibration.
Software: TerraMatch v.9.001
6. Position and attitude data were imported. Resulting data were classified as ground and nonground
points. Statistical absolute accuracy was assessed via direct comparisons of ground
classified points to ground RTK survey data. Data were then converted to orthometric
elevations (NAVD88) by applying a Geoid03 correction. Ground models were created as a
triangulated surface and exported as ArcInfo ASCII grids at a 1-meter pixel resolution.
Software: TerraScan v.9.001, ArcMap v9.3, TerraModeler v.9.001
Laser point coordinates were computed using the IPAS and ALS Post Processor software suites
based on independent data from the LiDAR system (pulse time, scan angle), and aircraft
trajectory data (SBET). Laser point returns (first through fourth) were assigned an associated
(x, y, z) coordinate along with unique intensity values (0-255). The data were output into
large LAS v. 1.2 files; each point maintains the corresponding scan angle, return number
(echo), intensity, and x, y, z (easting, northing, and elevation) information.
These initial laser point files were too large for subsequent processing. To facilitate laser
point processing, bins (polygons) were created to divide the dataset into manageable sizes
(< 500 MB). Flightlines and LiDAR data were then reviewed to ensure complete coverage of
the survey area and positional accuracy of the laser points.
Laser point data were imported into processing bins in TerraScan, and manual calibration was
performed to assess the system offsets for pitch, roll, heading and scale (mirror flex). Using a
geometric relationship developed by Watershed Sciences, each of these offsets was resolved
and corrected if necessary.
LiDAR points were then filtered for noise, pits (artificial low points) and birds (true birds as
well as erroneously high points) by screening for absolute elevation limits, isolated points and
height above ground. Each bin was then manually inspected for remaining pits and birds and
spurious points were removed. In a bin containing approximately 7.5-9.0 million points, an
average of 50-100 points are typically found to be artificially low or high. Common sources
of non-terrestrial returns are clouds, birds, vapor, haze, decks, brush piles, etc.
LiDAR Data Acquisition and Processing: Snohomish River Estuary, WA
Prepared by Watershed Sciences, Inc.
Internal calibration was refined using TerraMatch. Points from overlapping lines were tested
for internal consistency and final adjustments were made for system misalignments (i.e.,
pitch, roll, heading offsets and scale). Automated sensor attitude and scale corrections
yielded 3-5 cm improvements in the relative accuracy. Once system misalignments were
corrected, vertical GPS drift was then resolved and removed per flight line, yielding a slight
improvement (<1 cm) in relative accuracy.
The TerraScan software suite is designed specifically for classifying near-ground points
(Soininen, 2004). The processing sequence began by 'removing' all points that were not
'near' the earth based on geometric constraints used to evaluate multi-return points. The
resulting bare earth (ground) model was visually inspected and additional ground point
modeling was performed in site-specific areas to improve ground detail. This manual editing
of grounds often occurs in areas with known ground modeling deficiencies, such as: bedrock
outcrops, cliffs, deeply incised stream banks, and dense vegetation. In some cases,
automated ground point classification erroneously included known vegetation (i.e.,
understory, low/dense shrubs, etc.). These points were manually reclassified as non-grounds.
Ground surface rasters were developed from triangulated irregular networks (TINs) of ground
points.
The NOAA Office for Coastal Management (OCM) downloaded topographic files in text format from PSLC's website.
The files contained lidar easting, northing, 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 All-Return ASCII txt files were parsed to convert GPS Week Time to Adjusted Standard GPS Time.
2. The All-Return ASCII files were converted from txt format to las format using LASTools' txt2las tool and
reclassified to fit the OCM class list, N=1 (unclassified), G=2 (ground).
3. The las files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid03.
4. The las files' vertical units were converted from feet to meters, removing bad elevations.
5. The las files were converted from a Projected Coordinate System (WA SP North) to a Geographic Coordinate system (NAD83)
6. The las files' horizontal units were converted from feet to decimal degrees and converted to laz format.
7. The laz tiles containing only water areas were removed and remaining tiles were clipped to remove excess noise.
2013-11-14T00:00:00
The vertical values in this data set have been converted to reference North American Vertical Datum of 1988 (NAVD88) (GEOID18) meters, using the GEOID18 grids provided by the National Geodetic Survey.
Any datum and projection transformations were then done with the Office for Coastal Management 'datum_shift' program. Compression to an LAZ file was done with the LAStools 'laszip' program and can be unzipped with the same free program (laszip.org)
Processing notes:
2024-03-01T06:24:48
NOAA Office for Coastal Management
coastal.info@noaa.gov
processor