gov.noaa.nmfs.inport:62726
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
5627050598
EPSG::6319
2016 USGS Lidar: Osceola, FL
fl2016_osceola_m9167_metadata
2016-10
publication
NOAA/NMFS/EDM
62726
https://www.fisheries.noaa.gov/inport/item/62726
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/geoid18/9167/breaklines/
WWW:LINK-1.0-http--link
Breaklines
Link to the data set breaklines.
download
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9167/supplemental/OsceolaProject_Report_20161021.pdf
WWW:LINK-1.0-http--link
Project Report
Link to the 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
Aerial Cartographics of America Inc. (ACA) collected 1,535 square miles in the Florida counties of Osceola, Polk and Orange. The nominal pulse spacing for this project was 1 point every 0.5 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- Bridge Decks, 18-High Noise. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened DEMs for the project area. The data was formatted according to the tile naming convention as stated in the project SOW with each tile covering an area of 2,500 feet by 2,500 ft. A total of 7,292 LAS and DEM tiles were produced for the entire project.
The NOAA Office for Coastal Management (OCM) downloaded the laz files from this USGS site ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_Osceola_2015_LAS_2017/ and processed the data to the Data Access Viewer (DAV) and to https. The total number of files downloaded and processed was 7292.
The hydro breaklines were also downloaded and are available at the link provided in the URL section of this metadata record. Please note that these 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 or OCM.
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 2.5 foot cell size hydro flattened Digital Elevation Models (DEMs) . All products follow and comply with USGS Lidar Base Specification Version 1.2.
USGS
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/geoid18/9167/supplemental/fl2016_osceola_m9167.kmz
This graphic displays the footprint for this lidar data set.
KML
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN 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 > FLORIDA
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
Contours
Low Confidence Areas
erosion
theme
Continent > North America > United States Of America > Florida > Orange County
Continent > North America > United States Of America > Florida > Osceola County
Continent > North America > United States Of America > Florida > Polk County
place
Lidar - partner (no harvest)
project
InPort
otherRestrictions
Cite As: OCM Partners, [Date of Access]: 2016 USGS Lidar: Osceola, FL [Data Date Range], https://www.fisheries.noaa.gov/inport/item/62726.
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 USGS, NOAA, the Office for Coastal Management or its partners.
unclassified
NOAA Data Management Plan (DMP)
NOAA/NMFS/EDM
62726
https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/62726.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
Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3
-81.65928
-80.860139
27.639546
28.43458
| Currentness: Ground Condition
2016-01-21
2016-04-13
A complete description of this dataset is available in the Final Project Report that was submitted to the U.S. Geological Survey.
The following are the USGS lidar fields in JSON:
{
"ldrinfo" : {
"ldrspec" : "USGS-NGP Lidar Base Specification V1.2",
"ldrsens" : "Riegl LMS-Q680i",
"ldrmaxnr" : "7",
"ldrnps" : "0.45",
"ldrdens" : "4.94",
"ldranps" : "0.45",
"ldradens" : "4.94",
"ldrfltht" : "700",
"ldrfltsp" : "110",
"ldrscana" : "60",
"ldrscanr" : "120",
"ldrpulsr" : "280",
"ldrpulsd" : "5.5",
"ldrpulsw" : "0.351",
"ldrwavel" : "1550",
"ldrmpia" : "1",
"ldrbmdiv" : "0.5",
"ldrswatw" : "809.49",
"ldrswato" : "55",
"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"
},
"ldraccur" : {
"ldrchacc" : "0.196",
"rawnva" : "0.171",
"rawnvan" : "91",
"clsnva" : "0.082",
"clsnvan" : "91",
"clsvva" : "0.137",
"clsvvan" : "73"
},
"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" : "16",
"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"
}
}}
false
eng
false
none
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=9167/details/9167
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/geoid18/9167/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
Horizontal Positional Accuracy
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. Twenty-eight (28) checkpoints were tested and the results 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 = 0.66 ft (20 cm) and RMSEy = 0.84 ft (25.6 cm) which equates to +/- 1.85 ft (56.4 cm) at 95% confidence level.
Vertical Positional Accuracy
The vertical accuracy of the source LiDAR and classified LAS was tested by Dewberry with 164 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain (91 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (73 checkpoints), including forest, brush, tall weeds, crops, and high grass. The vertical accuracy of the LiDAR 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 0.64 ft (19.6 cm) at the 95% confidence level based on RMSEz (0.33 ft/10 cm) x 1.9600. All checkpoints located in vegetated terrain will be used to compute the Vegetated Vertical Accuracy (VVA). Project specifications required a VVA of 0.96 ft (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 0.33 ft (10 cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =0.14 ft (4.26cm), equating to +/- 0.27 ft (8.23 cm) at 95% confidence level. This LiDAR dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.33 ft (10 cm) RMSEz Vertical Accuracy Class. Actual VVA accuracy was found to be +/- 0.45ft (13.7 cm) at the 95th percentile.
The 5% outliers consisted of 4 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between -0.52 ft (-15.8 cm) and 0.71 ft (21.6 cm).
Completeness Report
A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. No void or missing data and data passes vertical accuracy specifications.
Conceptual Consistency
Data covers the entire tile scheme provided for the project area.
Data for the Osceola County Florida QL2 LiDAR project was acquired by Aerial Cartographics of America Inc. (ACA).
The project area included approximately 1535 contiguous square miles or 2470 square kilometers for the counties of Osceola, Polk and Orange in Florida. LiDAR sensor data were collected with the Riegl LMS-Q680i LiDAR system. The data was delivered in the State Plane coordinate system, feet, Florida East, horizontal datum NAD83 (2011), vertical datum NAVD88, Geoid 12B. Deliverables for the project included a raw (unclassified) calibrated LiDAR point cloud, survey control, and a final acquisition/calibration report.
The calibration process considered all errors inherent with the equipment including errors in GPS, IMU, and sensor specific parameters. Adjustments were made to achieve a flight line to flight line data match (relative calibration) and subsequently adjusted to control for absolute accuracy. Process steps to achieve this are as follows:
Rigorous LiDAR calibration: all sources of error such as the sensor's ranging and torsion parameters, atmospheric variables, GPS conditions, and IMU offsets were analyzed and removed to the highest level possible. This method addresses all errors, both vertical and horizontal in nature. Ranging, atmospheric variables, and GPS conditions affect the vertical position of the surface, whereas IMU offsets and torsion parameters affect the data horizontally. The horizontal accuracy is proven through repeatability: when the position of features remains constant no matter what direction the plane was flying and no matter where the feature is positioned within the swath, relative horizontal accuracy is achieved.
Absolute horizontal accuracy is achieved through the use of differential GPS with base lines shorter than 25 miles. The base station is set at a temporary monument that is 'tied-in' to the CORS network. The same position is used for every lift, ensuring that any errors in its position will affect all data equally and can therefore be removed equally.
Vertical accuracy is achieved through the adjustment to ground control survey points within the finished product. Although the base station has absolute vertical accuracy, adjustments to sensor parameters introduces vertical error that must be normalized in the final (mean) adjustment.
A copy of the final calibrated swaths are maintained in LAS format 1.2 for production utilizing Terrascan software. A second, identical version of final calibrated swaths are converted from v1.2 to v1.4 using GeoCue software. The withheld and overlap bits are set and all headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools.
2016-05-01T00:00:00
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 (2,500 ft x 2,500 ft). The tiled data is then opened in Terrascan where Dewberry classifies edge of flight line points that may be geometrically unusable to a separate class. These points are separated from the main point cloud so that they are not used in the ground algorithms. Dewberry then 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. As part of the ground routine, low noise points are classified to class 7 and high noise points are classified to class 18. Once the ground routine has been completed, bridge decks are classified to class 17 using bridge breaklines compiled by Dewberry. A manual quality control routine is then performed using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review is performed on all tiles and a 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 and bridge deck corrections are completed, the dataset is 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 1x NPS or less of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. Overage points are then identified in Terrascan and GeoCue is used to set the overlap bit for the overage points and the withheld bit is set on the withheld points previously identified in Terrascan before the ground classification routine was performed. A final QC is performed on the data. The LAS files are then converted from v1.2 to v1.4 using GeoCue software. At this time, all headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools.
The data was classified as follows:
Class 1 = Unclassified. This class includes vegetation, buildings, noise etc.
Class 2 = Ground
Class 7 = Low Noise
Class 9 = Water
Class 10 = Ignored Ground due to breakline proximity
Class 17 = Bridge Decks
Class 18 = High Noise
The LAS header information was verified to contain the following:
Class (Integer)
Adjusted GPS Time (0.0001 seconds)
Easting (0.003 m)
Northing (0.003 m)
Elevation (0.003 m)
Echo Number (Integer)
Echo (Integer)
Intensity (16 bit integer)
Flight Line (Integer)
Scan Angle (degree)
2016-05-01T00:00:00
The NOAA Office for Coastal Management (OCM) downloaded the laz files from this USGS site:ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_Osceola_2015_LAS_2017/
These files were processed to the Data Access Viewer (DAV) and https. The total number of files downloaded and processed was 7292.
The data were in FL State Plane East (0901) (NAD83 2011), US survey feet coordinates and NAVD88 (Geoid12B) elevations in feet. The data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 10 - Ignored Ground, 17 - Bridge Decks, 18 - High Noise. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 7, 9, 10, 17, 18.
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. A small number of points were classified as 6, 14, and 255. These points were not defined in the project metadata or report. They remain in the data set, but are not listed as available classes for download.
2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid12B model, to convert from FL State Plane East (0901) (NAD83 2011) coordinates in US survey feet, to geographic coordinates, to convert from vertical units of feet to meters, to assign the geokeys, to sort the data by gps time and zip the data to database and to http.
2020-08-10T00:00:00
Office for Coastal Management
processor
NOAA Office for Coastal Management found that all of the points that were not marked as withheld were marked as overlap. This made the overlap bit flag of no use and potentially detrimental to processes that drop points with the overlap flag. The overlap bit flag was removed from all points using the las2las program with the -set_overlap _flag 0 argument.
2022-09-21T00:00:00
NOAA Office for Coastal Management
(843) 740-1202
coastal.info@noaa.gov
processor
USGS
USGS