2004 USACE Puerto Rico Lidar

This record describes Light Detection and Ranging (Lidar) data acquired for the island of Puerto Rico. The data were acquired for

USACE, St. Louis District by 3001, Inc., between January 10 and February 8, 2004. The mission was flown at a density sufficient to support

a maximum final post spacing of 6 feet for unobscured areas. The Puerto Rico LiDAR Survey was collected under the guidance of a

Professional Mapper/Surveyor.

Original contact information:

Contact Org: 3001, Inc.

Title: LiDAR Department

Phone: (985) 661- 3001

Email: lidar@3001inc.com

The Puerto Rico LiDAR dataset will support the creation of Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRM) and an

integrated ground and surface water model.

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The Puerto Rico data provided by the NOAA Office for Coastal Management via the Digital Coast Data Access Viewer has been reviewed by Center staff as well

as other outside parties. The data, as processed and provided by the OCM, have some noted quality issues and some potential accuracy problems. The

OCM has not done any further accuracy assessment, but we have received some feedback from other organizations about accuracy and datum issues. Please

note that the geoid grids for Puerto Rico, themselves, have a varying level of accuracy. The data is being provided as a 'best available' data set,

but should be used with a level of caution.

The Lidar QA/QC Quantitative and Qualitative Assessment Report for this data set may be viewed at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/560/supplemental/lidarqaqcreport_puertorico_final.pdf

A footprint of this data set may be viewed in Google Earth at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/560/supplemental/2004_USACE_Puerto_Rico_Lidar.kmz

Any conclusions drawn from the analysis of this information are not the responsibility of the Office for Coastal Management

or its partners.

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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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent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. Acknowledgement of

USACE, St. Louis District would be appreciated in products derived from these data.

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.1.0.722

The accuracy assessment was performed using a standard method to compute the root mean square error (RMSE) based on a comparison of ground

control points (GCP) and filtered LiDAR data points. Filtered LiDAR data has had vegetation and cultural features removed and by analysis

represents bare-earth elevations. Testing was performed prior to gridding of the filtered LiDAR data points and construction of the

Intergraph .dtm file format. The RMSE figure was used to compute the vertical National Standard for Spatial Data Accuracy (NSSDA). Ground control

was established by 3001, Inc. A spatial proximity analysis was used to select edited LiDAR data points contiguous to the relevant GCPs. A search

radius decision rule is applied with consideration of terrain complexity, cumulative error and adequate sample size. Cumulative error results from

the errors inherent in the various sources of horizontal measurement. These sources include the airborne GPS, GCPs and the uncertainty of the

accuracy of the LiDAR data points. This accuracy is achieved prior to the sub-sampling that occurs through integration with the inertial

measurement unit (IMU) positions that are recorded. It is unclear at this time whether the initial accuracy is maintained. The horizontal accuracy

of the GCPs is estimated to be in the range of approximately 1 to 1.6 feet. Finally, sample size was considered. The specification for the National

Standard for Spatial Data Accuracy is a minimum of 20 points to conduct a statistically significant accuracy evaluation (Minnesota Planning, 1999,

Positional Accuracy Handbook, Minnesota Planning Land Management Information Center, St. Paul, Minnesota., p.3). Most statistical texts indicate

that a minimum of 30 sample points provide a reasonable Approximation of a normal distribution. The intent of the NSSDA is to reflect the geographic

area of interest and the distribution of error in the data set (Federal Geographic Data Committee, 1998, Geospatial National Standard for Spatial

Data Accuracy, Federal Geographic Data Committee Secretariat, Reston, Virginia, p.3-4). Additional steps were taken to ensure the vertical accuracy

of the LiDAR data including: Step 1: Precision Bore sighting (Check Edge-matching) Step 2: Compare the LiDAR data to the Field Survey

(Field survey is to FEMA specifications and more stringent internal specifications) Step 3: Automated Filtering Step 4: Manual Editing (Quality

Control) Step 5: 3-D digitizing and Photogrammetric Compilation of hydrographic breaklines.

; Quantitative Value: 11.90 meters, Test that produced the value:

Based upon the result of vertical accuracy testing conducted by 3001, Inc., vertical accuracy at the 95% confidence level (Accuracyz) is computed

by the formula RMSEz x 1.9600. The overall vertical accuracy of the Puerto Rico Lidar dataset is 11.90 cm, based upon an RMSEz of 6.07 cm.

These values were derived from a comparison of Lidar data points that fell within a 1 m horizontal radius of 20 established ground control points.

They represent the overall vertical accuracy in all surface types surveyed, which include ashphalt, dirt and mowed grass.

At the end of each flight, the Lidar data was processed to check for complete coverage and to verify that there were no voids in data coverage.

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