gov.noaa.nmfs.inport:54790
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
99644567309
2013 USGS Lidar: NY post-Sandy, Ulster, Dutchess, Orange Counties
Ulster_Dutchess_Orange_Counties_NY_8628.xml
2013
creation
2015-08
publication
NOAA/NMFS/EDM
54790
https://www.fisheries.noaa.gov/inport/item/54790
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/geoid18/8628/breaklines/index.html
WWW:LINK-1.0-http--link
Breaklines
Folder containing breaklines for the project.
download
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8628/supplemental/LiDAR_Project_Report_USGS_NY_TriCounty.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
The Atlantic Group (TAG) collected 2846 square miles in the New York counties of Ulster, Dutchess, and Orange. The nominal pulse spacing for this project was no greater than 0.7 meters. Dewberry used proprietary procedures to classify the LAS into an initial ground surface. Dewberry then used proprietary procedures to classify the LAS and performed manual classifications according to project specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water, and 10-Ignored Ground due to breakline proximity. 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 3465 tiles were produced for the entire project encompassing an area of approximately 2846 sq. mile.
The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.2 format, 3D breaklines, and 1 meter cell size hydro flattened Digital Elevation Models (DEMs). All products follow and comply with USGS Program Lidar Base Specification Version 1.0.
U.S. Geological Survey
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/geoid18/8628/supplemental/ny2014_usgs_ulduor_m8628.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
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
erosion
theme
Lidar - partner (no harvest)
project
InPort
otherRestrictions
Cite As: OCM Partners, [Date of Access]: 2013 USGS Lidar: NY post-Sandy, Ulster, Dutchess, Orange Counties [Data Date Range], https://www.fisheries.noaa.gov/inport/item/54790.
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: 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: USGS/NGTOC, 1400 Independence Road, Rolla, MO 65401. Telephone (573) 308-3756.
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
54790
https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/54790.pdf
WWW:LINK-1.0-http--link
NOAA Data Management Plan (DMP)
NOAA Data Management Plan for this record on InPort.
information
crossReference
.7
eng; US
elevation
Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 10.0
-74.78481
-73.483185
41.135893
42.182013
| Currentness: Ground Condition
2013-11-20
2014-06-01
A complete description of this dataset is available in the Final Project Report submitted to the USGS.
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=8628
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.
download
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8628/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.
download
dataset
Horizontal Positional Accuracy
The DEMs are derived from the source LiDAR and 3D breaklines created from the LiDAR. Horizontal accuracy is not performed on the DEMs or breaklines. Lidar source produced to meet 1 meter horizontal accuracy.
Project specifications required a horizontal accuracy of 1 m based on a RMSEr (0.578m) x 1.7308. 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. Qualitative value: 1 meter, Test that produced the valued: The DEMs are derived from the source LiDAR and 3D breaklines created from the LiDAR. Horizontal accuracy is not performed on the DEMs or breaklines. LiDAR vendors perform calibrations on the LiDAR sensor and compare data to adjoing flight lines to ensure LiDAR meets the 1 meter horizontal accuracy standard at the 95% confidence level.
However, Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only sixteen (16) checkpoints were photoidentifiable, the results are not statistically significant enough to report as a final tested value. However, the results are reported below.
Using NSSDA methodology, horizontal accuracy at the 95% confidence level (called Accuracyr) is computed by the formula RMSEr x 1.7308. The dataset for the Ulster, Dutchess, and Orange Counties NY LiDAR project satisfies the criteria:
Lidar dataset tested 0.535 m horizontal accuracy at 95% confidence level, based on RMSEr (0.309 m) x 1.7308.
Please see the final project report delivered to the U.S. Geological Survey for more details.
Vertical Positional Accuracy
The DEMs are derived from the source LiDAR and 3D breaklines created from the LiDAR. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production so that any differences identified between the source LiDAR and final DEMs can be attributed to interpolation differences. DEMs are created by averaging several LiDAR points within each pixel which may result in slightly different elevation values at a given location when compared to the source LAS, which is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the LiDAR ground points. TINs do not average several LiDAR points together but interpolate (linearly) between two or three points to derive an elevation value.
The vertical accuracy of the final bare earth DEMs was tested by Dewberry with 103 independent survey checkpoints. The same checkpoints that were used to test the source LiDAR data were used to validate the vertical accuracy of the final DEM products. The survey checkpoints were evenly distributed throughout the project area and were located in areas of bare earth and open terrain (21), tall weeds and crops (20), forested and fully grown (21), brush and small trees (20), and urban (21). The vertical accuracy is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations.
Checkpoints in open terrain will be used to compute the Fundamental Vertical Accuracy (FVA). Project specifications required a FVA of 0.18 m based on a RMSEz (0.0925m) x 1.9600. All checkpoints will be used to compute the Consolidated Vertical Accuracy (CVA). Project specifications required a CVA of 0.269 m based on the 95th percentile. Supplemental Vertical Accuracy (SVA) will be computed on each individual land cover category other than open terrain. Target specifications for SVA are 0.269 m based on the 95th percentile. NDEP and ASPRS testing methodologies allow individual SVA's to fail as long as the mandatory CVA passes project specifications.Qualitative value:0.13 m 0.26 m 0.33 m 0.25 m 0.20 m 0.25 m, Test that produced the value: Based on the vertical accuracy testing conducted by Dewberry, using NSSDA and FEMA methodology, vertical accuracy at the 95% confidence level (called Accuracyz) is computed by the formula RMSEz x 1.9600. The dataset for the Ulster, Dutchess, and Orange Counties NY LiDAR project satisfies the criteria:
DEM dataset tested 0.13 m vertical accuracy at 95% confidence level in open terrain, based on RMSEz (0.06 m) x 1.9600. Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, consolidated vertical accuracy (CVA) is computed using the 95th percentile method. The dataset for the Ulster, Dutchess, and Orange Counties NY LiDAR project satisfies the criteria:
DEM dataset tested 0.26 m consolidated vertical accuracy at 95th percentile in all land cover categories combined.
The 5% outliers consist of 6 checkpoints that are larger than the 95th percentile. The checkpoints have a DZ value range of -0.59 m to +0.32 m. Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset for the Ulster, Dutchess, and Orange Counties NY LiDAR project satisfies the criteria:
DEM dataset tested 0.33 m supplemental vertical accuracy at 95th percentile in the forested and fully grown land cover category. Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset for the Ulster, Dutchess, and Orange Counties NY LiDAR project satisfies the criteria:
DEM dataset tested 0.25 m supplemental vertical accuracy at 95th percentile in the urban land cover category. Based on the vertical accuracy
Completeness Report
A visual qualitative assessment was performed to ensure data completeness and full tiles. No void or missing data exists.
Conceptual Consistency
Data covers the tile scheme provided for the project area.
Data for the Ulster, Dutchess, and Orange Counties NY LiDAR project was acquired by The Atlantic Group (TAG) using a Partenavia S.P.A. P 68 C/TC (N775MW) and a Cessna T210L (N732JE).
The project area included approximately 2846 square miles in the New York counties of Ulster, Dutchess, and Orange. LiDAR sensor data was collected with the Leica ALS70-HP LiDAR system. No imagery was requested or delivered. The data was delivered in the UTM coordinate system, meters, zone 18, horizontal datum NAD83 (2011), vertical datum NAVD88, Geoid 12A. Deliverables for the project included a raw (unclassified) calibrated LiDAR point cloud, survey control, and a final control report.
A preliminary RMSEz error check is performed at this stage of the project life cycle in the raw LiDAR dataset against GPS static and kinematic data and compared to RMSEz project specifications. The LiDAR data is examined in open, flat areas away from breaks. Lidar ground points for each flightline generated by an automatic classification routine are used.
Overall the LiDAR data products collected by Atlantic meet or exceed the requirements set out in the Statement of Work. The quality control requirements of Atlantic's quality management program were adhered to throughout the acquisition stage fo this project to ensure product quality.
LIDAR acquisition began on November 20, 2013 (julian day 324) and was completed on June 01, 2014 (julian day 152). A total of 22 survey missions were flown to complete the project. TAG utilized a Leica ALS70-HP LiDAR system for the acquisition. The flight plan was flown as planned with no modifications. There were no unusual occurrences during the acquisition and the sensor performed within specifications. There were 499 flight lines required to complete the project.
The initial step of calibration is to verify availability and status of all needed GPS and Laser data against field notes and compile any data if not complete.
Subsequently the mission points are output using Leica's ALS Post Processor, initially with the most recent boresight values. The initial point generation for each mission calibration is verified within Microstation/Terrascan for calibration errors. If a calibration error greater than specification is observed within the mission, the roll pitch and scanner scale corrections that need to be applied are calculated. The missions with the new calibration values are regenerated and validated internally once again to ensure quality.
All missions are validated against the adjoining missions for relative vertical biases and collected GPS validation points for absolute vertical accuracy purposes.
On a project level, a supplementary coverage check is carried out to ensure no data voids unreported by Field Operations are present.
The initial points for each mission calibration are inspected for flight line errors, flight line overlap, slivers or gaps in the data, point data minimums, or issues with the LiDAR unit or GPS. Roll, pitch and scanner scale are optimized during the calibration process until the relative accuracy is met.
Relative accuracy and internal quality are checked using at least 3 regularly spaced QC blocks in which points from all lines are loaded and inspected. Vertical differences between ground surfaces of each line are displayed. Color scale is adjusted so that errors greater than the specifications are flagged. Cross sections are visually inspected across each block to validate point to point, flightline to flightline and mission to mission agreement.
For this project the specifications used are as follow:
Relative accuracy <= 7cm RMSEZ within individual swaths and <=10 cm RMSEZ or within swath overlap (between adjacent swaths).
UTM coordinate system, meters, zone 18, horizontal datum NAD83 (2011), vertical datum NAVD88, Geoid 12A
Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All LiDAR related processes begin by importing the data into the GeoCue task management software. The swath data is tiled according to project specifications (1,500 m x 1,500 m). The tiled data is then opened in Terrascan where Dewberry uses proprietary ground classification routines to remove any non-ground points and generate an accurate ground surface. The ground routine consists of three main parameters (building size, iteration angle, and iteration distance); by adjusting these parameters and running several iterations of this routine an initial ground surface is developed. The building size parameter sets a roaming window size. Each tile is loaded with neighboring points from adjacent tiles and the routine classifies the data section by section based on this roaming window size. The second most important parameter is the maximum terrain angle, which sets the highest allowed terrain angle within the model. Once the ground routine has been completed a manual quality control routine is done using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review and supervisor manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain. After the ground classification corrections were completed, the dataset was processed through a water classification routine that utilizes breaklines compiled by Dewberry to automatically classify hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. During this water classification routine, points that are within 0.3 meter of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. In addition to classes 1, 2, 9, and 10, there is a Class 7, noise points . Class 7 was only used if needed when points could manually be identified as low/high points.
The fully classified dataset is then processed through Dewberry's comprehensive quality control program.
The data was classified as follows:
Class 1 = Unclassified. This class includes vegetation, buildings, noise etc.
Class 2 = Ground
Class 7= Noise
Class 9 = Water
Class 10=Ignored
The LAS header information was verified to contain the following:
Class (Integer)
GPS Week Time (0.0001 seconds)
Easting (0.003 m)
Northing (0.003 m)
Elevation (0.003 m)
Echo Number (Integer 1 to 4)
Echo (Integer 1 to 4)
Intensity (16 bit integer)
Flight Line (Integer)
Scan Angle (Integer degree)
2014-08-01T00:00:00
All hydrographic breaklines were collected by Tuck Mapping Solutions using LP360. LP360 allows the user to view both the intensity and elevation of the dataset when placing the breaklines. The breaklines are then conflated in LP360 to match the lidar elevations. Monotonicity is enforced on linear hydrographic features during the conflate process and water bodies are assigned the lowest elevation during the conflate process so that each water body is set to one constant elevation that is below the surrounding terrain. The breaklines were collected in accordance with the Data Dictionary.
Inland Lakes and Ponds and Inland Streams and Rivers were collected according to specifications for the Ulster, Dutchess, and Orange Counties NY LiDAR Project.
2015-01-01T00:00:00
NOAA OCM obtained the data from the USGS rocky ftp site. Data were converted to geographic coordinates and ellipsoid heights for ingest into the Digital Coast Data Access Viewer. NGS Geoid12a was used for the conversion to ellipsoid height.
2018-11-13T00:00:00
Office for Coastal Management
processor
Pollpel Island in the Hudson River was found unclassified. Global Mapper was used to classify ground on the island. The continually updated shoreline product was used to then classify the water that had been classified as ground.
2020-02-20T00:00:00
NOAA Office for Coastal Management
(843) 740-1202
coastal.info@noaa.gov
processor
Classified lidar data
USGS
publisher