2017 USGS Lidar: Suwannee River, FL

Digital Aerial Solution (DAS) collected 921 square miles over 3 Areas of Interest (AOIs) to include portions of Baker, Alachua and Levy Counties in Florida. The nominal pulse spacing for this project was 1 point every 0.7 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 Florida State Grid tile naming convention with each tile covering an area of 5,000 feet by 5,000 ft. A total of 1378 LAS tiles and 1378 DEM tiles were produced for the entire project.

The NOAA Office for Coastal Management (OCM) downloaded this data set from this USGS site:

ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_SuwanneeRiver_2017_LAS_2018

These files were processed to the Data Access Viewer (DAV) and https. The total number of laz files downloaded and processed was 1379.

The breaklines were also downloaded and are available for download at the link provided in the URL section of this metadata record. Please note that this product has 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.

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" : "Leica ALS80 HP",

"ldrmaxnr" : "8",

"ldrnps" : "0.70",

"ldrdens" : "2",

"ldranps" : "0.70",

"ldradens" : "2",

"ldrfltht" : "1129",

"ldrfltsp" : "150",

"ldrscana" : "32",

"ldrscanr" : "56.7",

"ldrpulsr" : "240.6",

"ldrpulsd" : "2.5",

"ldrpulsw" : "0.05",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "647.4",

"ldrswato" : "32.45",

"ldrcrs" : "NAD 1983 (2011) State Plane Florida North U.S. Survey Feet",

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

},

"ldraccur" : {

"ldrchacc" : "0.196",

"rawnva" : "0.104",

"rawnvan" : "93",

"clsnva" : "0.107",

"clsnvan" : "93",

"clsvva" : "0.165",

"clsvvan" : "51"

},

"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" : "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"

}

}}

Any conclusions drawn from the analysis of this information are not the responsibility of Dewberry, USGS, NOAA, the Office for Coastal Management or its partners.

Data is available online for bulk and custom downloads.

None

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.

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.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 1.35 ft (41 cm) RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 3.28 ft (1 meter) at a 95% confidence level. Nineteen (19) checkpoints were photo-identifiable but do not produce a statistically significant tested horizontal accuracy value. Using this small sample set of photo-identifiable checkpoints, positional accuracy of this dataset was found to be RMSEx = 1.34 ft (40.8 cm)) and RMSEy = 0.75 ft (22.9 cm) which equates to +/- 2.65 ft (80.8 cm) at 95% confidence level. While not statistically significant, the results of the small sample set of checkpoints are within the produced to meet horizontal accuracy.

The vertical accuracy of the lidar was tested by Dewberry with 144 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain (93 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (51 checkpoints), including forest, brush, tall weeds, crops, and high grass. 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 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 were 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 classified 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 =0.18 ft (5.5 cm), equating to +/- 0.35 ft (10.7 cm) at 95% confidence level. This classified 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 +/- 0.54 ft (16.5 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 -0.55 ft (-16.8 cm) and 0.77 ft (23.5 cm).

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.

Data covers the project boundary.

Data is backed up to tape and to cloud storage.

NOAA OCM downloaded the laz files from the USGS rockyftp site.