2015-2017 USGS Puerto Rico Lidar

Leading Edge Geomatics (LEG) collected 3451 square miles in Puerto Rico. 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-Bridges, 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 USNG tile naming convention with each tile covering an area of 1,500 meters by 1,500 meters. A total of 4,714 tiles were produced for the entire Puerto Rico project. An interim delivery was submitted to USGS in December 2016. There are 2,048 tiles in the tile grid, 1,995 LAS files, and 1,941 DEMs included in this second delivery. The discrepancy between the tile count and the LAS/DEM files is because several tiles cover only open water.

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 1 meter 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" : "Riegl 680i",

"ldrsens" : "Riegl 780",

"ldrmaxnr" : "Unlimited",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.7",

"ldrnps" : "0.65",

"ldrdens" : "2.0",

"ldrdens" : "2.4",

"ldranps" : "0.5",

"ldranps" : "0.456",

"ldradens" : "4",

"ldradens" : "4.8",

"ldrfltht" : "1100",

"ldrfltht" : "900",

"ldrfltsp" : "100",

"ldrfltsp" : "120",

"ldrscana" : "60",

"ldrscanr" : "2358",

"ldrscanr" : "4715",

"ldrpulsr" : "200",

"ldrpulsd" : "5",

"ldrpulsw" : "1.5",

"ldrwavel" : "1064",

"ldrmpia" : "0",

"ldrbmdiv" : "0.5",

"ldrbmdiv" : "0.25",

"ldrswatw" : "1270",

"ldrswatw" : "1039",

"ldrswato" : "50",

"ldrcrs" : "NAD 1983 (2011) State Plane Puerto Rico Virgin Isls FIPS 5200",

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

},

"ldraccur" : {

"ldrchacc" : "0.196",

"rawnva" : "0.190",

"rawnvan" : "125",

"clsnva" : "0.195",

"clsnvan" : "127",

"clsvva" : "0.206",

"clsvvan" : "85"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

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

"lasolap" : "The previously delivered and accepted portion of Puerto Rico used an overlap identification algorithm which flagged all points as overlap due to the greater than 50% swath overlap used during lidar acquisition. This current delivery was processed with the same algorithm to produce a consistent dataset for the entire AOI. However, there are no ground points flagged as overlap as all ground points were used in DEM generation to maintain the highest density possible (there are class 1 overlap points). The ground was reviewed to ensure no unwanted elevation variability results from using all ground points. Unusable points along the edges of flight lines have been flagged as withheld.",

"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 NOAA, the Office for Coastal Management or its partners

Data is available online for 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. Qualitative value: 21.6 cm, Test that produced the valued: 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 41 cm RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 1 meter at a 95% confidence level. Three (3) 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 = 7.9 cm and RMSEy = 9.7 cm which equates to +/- 21.6 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 212 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 (127), and vegetated terrain, including forest, brush, tall weeds, crops, and high grass (85). 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.Qualitative value:18.2 cm 20.6 cm, Test that produced the value: The 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 =9.3 cm, equating to +/- 18.2 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 +/- 20.6 cm at the 95th percentile.

The 5% outliers consisted of 5 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between -30.6 cm and 45.3 cm.

A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. There are known voids in this dataset which have been accepted by USGS. These voids are due to persistent cloud cover which prevented an area in the southeast portion of the mainland from being acquired with lidar data. A shapefile defining the full void extent is included in the deliverables.

Data covers the tile scheme provided for the second delivery.