Data Management Plan

This Light Detection and Ranging (LiDAR) LAS dataset is a survey of inland Okaloosa County, Florida not

covered in the 2008 Florida Department of Emergency Management LiDAR initiative. The project area consists of

approximately 874 square miles, including a buffer of approximately 50 feet along the edges of the project. The

project design of the LiDAR data acquisition was developed to support a nominal post spacing of 4.9 feet

or 1.5 meters for un-obscured areas. Fugro EarthData, Inc. acquired 49 flight lines in three lifts on February 10, 2008.

The data was divided into 5000' by 5000' foot cells that serve as the tiling scheme. LiDAR data collection was

performed with a Cessna 310 aircraft, utilizing a Leica ALS50-II MPiA sensor, collecting multiple return x, y, and z

data as well as intensity data. LiDAR data was processed to achieve a bare ground surface. LIDAR data is remotely

sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser

range finding, GPS positioning and inertial measurement technologies, LIDAR instruments are able to make highly

detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures and vegetation. This data of

inland Okaloosa County, Florida, was collected at sufficient resolution to provide a nominal point spacing of

1.5m for collected points. Up to 5 returns were recorded for each pulse in addition to an intensity value.

Original contact information:

Contact Org: NOAA Office for Coastal Management

Phone: 843-740-1202

Email: coastal.info@noaa.gov

Process Steps:

• 2008-03-14 00:00:00 - The airborne GPS data were processed and integrated with the IMU. The results were imported into the processing system for use in the LiDAR boresight. The raw LiDAR data was downloaded onto a production server. The ground control and airport GPS base station were used in conjunction with the processed ABGPS results for the LiDAR boresight. The properly formatted processing results were used for subsequent processing.
• 2008-07-16 00:00:00 - EarthData has developed a unique method for processing LiDAR data to identify and remove elevation points falling on vegetation, buildings, and other aboveground structures. The algorithms for filtering data were utilized within EarthData's proprietary software and commercial software written by TerraSolid. This software suite of tools provides efficient processing for small to large-scale, projects and has been incorporated into ISO 9001 compliant production work flows. The following is a step-by-step breakdown of the process. 1. Using the LiDAR data set provided by EarthData Aviation, the technician performs calibrations on the data set. 2. The technician performed a visual inspection of the data to verify that the flight lines overlap correctly. The technician also verified that there were no voids, and that the data covered the project limits. The technician then selected a series of areas from the data set and inspected them where adjacent flight lines overlapped. These overlapping areas were merged and a process which utilizes 3-D Analyst and EarthData's proprietary software was run to detect and color code the differences in elevation values and profiles. The technician reviewed these plots and located the areas that contained systematic errors or distortions that were introduced by the LiDAR sensor. 3. Systematic distortions highlighted in step 2 were removed and the data was re-inspected. Corrections and adjustments can involve the application of angular deflection or compensation for curvature of the ground surface that can be introduced by crossing from one type of land cover to another. 4. The LiDAR data for each flight line was trimmed in batch for the removal of the overlap areas between flight lines. The data was checked against a control network to ensure that vertical requirements were maintained. Conversion to the client-specified datum and projections were then completed. The LiDAR flight line data sets were then segmented into adjoining tiles for batch processing and data management. 5. The initial batch-processing run removed 95% of points falling on vegetation. The algorithm also removed the points that fell on the edge of hard features such as structures, elevated roadways and bridges. 6. The operator interactively processed the data using LiDAR editing tools. During this final phase the operator generated a TIN based on a desired thematic layer to evaluate the automated classification performed in step 5. This allowed the operator to quickly re-classify points from one layer to another and recreate the TIN surface to see the effects of edits. Geo-referenced images were toggled on or off to aid the operator in identifying problem areas. The data was also examined with an automated profiling tool to aid the operator in the reclassification. 7. The point cloud data were delivered in LAS 1.1 format. 9 - points in water, 2 - ground points, and 1 - all other.
• 2008-07-16 00:00:00 - The LiDAR ground points created in Process Step 2 were loaded into a Terrascan project. The export lattice model function in Terrascan was then used to create and output the LiDAR DEM grid to the Arc ASCII Raster format. As a final step, the Arc ASCII Raster format grid tiles were converted to ESRI Grid format using an Arc command.
• 2008-07-21 00:00:00 - The NOAA Office for Coastal Management (OCM) received files in LAS format. The files contained LiDAR intensity and elevation measurements. OCM performed the following processing on the data to make it available within the LiDAR Data Retrieval Tool (LDART): 1. The LAS files were converted from UTM coordinates to geographic coordinates. 2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid 03. 3. The LAS header fields were sorted by latitude and updated. 4. The data was filtered to eliminate outliers.

This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer

The data set is dynamically generated based on user-specified parameters.

;