2018 TWDB Lidar DEM: Coastal Texas

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Information on the NOAA Office for Coastal Management (OCM)

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.

This graphic displays the footprint for this lidar data set.

Data report by AECOM.

Link to custom download, from the Data Access Viewer (DAV), the lidar point data from which these raster Digital Elevation Model (DEM) data were created.

Link to the hydro breaklines.

Link to the survey report.

All surveying activities were performed by Fugro USA Land, Inc. A total of ground control points to support the lidar collection were collected in the Urban and Coastal AOIs; the points were a combination of gravel, dirt, asphalt, and concrete all in open terrain. The horizontal Datum was the North American Datum of 1983 (NAD83, 2011). The vertical datum was the North American Datum of 1988 (NAVD88). The geoid model, GEOID12B, was used to obtain the NAVD88 orthometric heights from the GRS 1980 ellipsoidal heights.

Fugro collected Riegl-derived lidar over the Coastal Texas project AOI with a 0.5 meter Nominal Pulse Spacing (NPS). Data was collected when environmental conditions met the specified criteria: leaf-off and no significant snow cover or flood conditions; cloud, smoke, dust, and fog-free between the aircraft and ground. The collection for the Urban and Coastal AOIs was accomplished on January 13, 14, 15, 17, 18, 22, 23, 24, 25, 28, 29, 30, and 31, February 2, 8, 19, 23, and 26, and March 1, 2, 3, 6, 7, 8, 11, 12, 13, 14, 19, 20, 21, and 22 2018; 982 flight lines were acquired in 117 lifts. The lines were flown at an average of 3,250 feet above mean terrain. The collection was performed using the Riegl LMS-Q680i and Riegl LMS-Q780i lidar systems, serial numbers 163, 165, 421, and 961.

All acquired lidar data went through a preliminary review to assure that complete coverage had been obtained and that there were no gaps between flight lines before the flight crew left the project site. Once back in the office, the data was run through a complete iteration of processing to ensure that it is complete, uncorrupted, and that the entire project area has been covered without gaps between flight lines. There are essentially three steps to this processing: 1) GPS/IMU Processing - Airborne GPS and IMU data was processed using the airport GPS base station data. 2) Raw Lidar Data Processing - Technicians processed the raw data to LAS format flight lines with full resolution output before performing QC. A starting configuration file is used in this process, which contains the latest calibration parameters for the sensor. The technicians also generated flight line trajectories for each of the flight lines during this process. 3) Verification of Coverage and Data Quality - Technicians checked the trajectory files to ensure completeness of acquisition for the flight lines, calibration lines, and cross flight lines. The intensity images were generated for the entire lift at the required 0.5 meter NPS. Visual checks of the intensity images against the project boundary were performed to ensure full coverage to the 300 meter buffer beyond the project boundary. The intensity histogram was analyzed to ensure the quality of the intensity values. The technician also thoroughly reviewed the data for any gaps in project area. The technician generated a sample TIN surface to ensure no anomalies were present in the data. Turbulence was inspected for each flight line; if any adverse quality issues were discovered, the flight line was rejected and re-flown. The technician also evaluated the achieved post spacing against project specified 0.5 meter NPS as well as making sure no clustering in point distribution.

The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technicians first used Fugro proprietary and commercial software to calculate initial boresight adjustment angles based on sample areas within the lift. These areas cover calibration flight lines collected in the lift, cross tie and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technician then analyzed the results and made any necessary additional adjustment until it is acceptable for the selected areas. 3) Once the boresight angle calculation was completed for the selected areas, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technicians utilized commercial and proprietary software packages to analyze the matching between flight line overlaps for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once all lifts were completed with individual boresight adjustment, the technicians checked and corrected the vertical misalignment of all flight lines and also the matching between data and ground truth. The relative accuracy was ? 3 cm RMSDz within swath overlap (between adjacent swaths) with a maximum difference of ± 17 cm. 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed ground control points after the z correction to ensure the requirement of RMSEz (non-vegetated) ? 10 cm, NVA ? 19.6 cm 95% Confidence Level was met.

Once boresighting was completed, the project was set up for automatic classification. First, the lidar data was cut into production tiles and the flight line overlap points, noise points, ground points, and building points were classified automatically. Fugro utilized commercial software, as well as proprietary, in-house developed software for automatic filtering. The parameters used in the process were customized for each terrain type to obtain optimum results. These parameters were also customized to capture multiple categories of vegetation based on height (low, medium, and high vegetation). After all “low” points are classified, points remaining are reclassified automatically based on height from the ground. Once the automated filtering was completed, the files were run through a visual inspection to ensure that the filtering was not too aggressive or not aggressive enough. In cases where the filtering was too aggressive and important terrain were filtered out, the data was either run through a different filter within local area or was corrected during the manual filtering process. Bridge deck points and culvert points were classified as well during the interactive editing process. Interactive editing was completed in visualization software that provides manual and automatic point classification tools. Fugro utilized commercial and proprietary software for this process. All manually inspected tiles went through a peer review to ensure proper editing and consistency. After the manual editing and peer review, all tiles went through another final automated classification routine. This process ensures only the required classifications are used in the final product (all points classified into any temporary classes during manual editing will be re-classified into the project specified classifications). Once manual inspection, QC and final autofilter is complete for the lidar tiles, the LAS data was packaged to the project specified tiling scheme, cut to the approved tile layout, and formatted to LAS v1.4. It was also re-projected to UTM Zone 15 north; NAD83(2011), meters; NAVD88(GEOID12B), meters. The file header was formatted to meet the project specification. This Classified Point Cloud product was used for the generation of derived products. This product was delivered in fully compliant LAS v1.4, Point Record Format 6 with Adjusted Standard GPS Time. Georeferencing information is included in all LAS file headers. Each tile has File Source ID assigned to zero. The Point Source ID matches to the flight line ID in the flight trajectory files. Intensity values are included for each point, normalized to 16-bit. The following classifications are included: Class 1 – Processed, but unclassified; Class 2 – Bare earth ground; Class 3 – Low Vegetation (0.01m to 1.00m above ground); Class 4 – Medium Vegetation (1.01m to 3.00m above ground); Class 5 – High Vegetation (greater than 3.01m above ground); Class 6 – Building; Class 7 – Low Point (Noise); Class 9 – Water; Class 10 – Ignored Ground; Class 14 – Culverts; and Class 17 – Bridge Decks. The classified point cloud data was delivered in tiles without overlap using the project tiling scheme.

Hydro linework is produced by heads-up digitizing using classified lidar datasets. Additionally, products created from lidar including intensity images, shaded-relief TIN surfaces, and contours are used. Hydrographic features were collected as separate feature classes: 1) Inland Ponds and Lakes nominally larger than 2 acres in area (Ponds_and_Lakes) and 2) Inland Streams and Rivers nominally larger than 15.25 meters (Stream_and_River)(1_Acre_Islands). After initial collection, features were combined into working regions based on watershed sub-basins. Linework was then checked for the following topological and attribution rules: 1) Lines must be attributed with the correct feature code and 2) Lake and stream banklines must form closed polygons. Hydro features were collected as vector linework using lidar and its derived products listed above. This linework is initially 2D, meaning that it does not have elevation values assigned to individual line vertices. Vertex elevation values were assigned using a distance weighted distribution of lidar points closest to each vertex. This is similar to draping the 2D linework to a surface modeled from the lidar points. After the initial ‘drape’, the linework elevation values were further adjusted based on the following rules: 1) Lake feature vertices were re-assigned (flattened) to lowest draped vertex value, and 2) Double stream bankline vertices were re-assigned based on the vertices of the closest adjusted double stream connector line. Fugro proprietary software was used to create profiles to ensure bank to bank flatness, monotonicity check, and lake flatness. The hydro breaklines were delivered as polygons in Esri ArcGIS version 10.3 geodatabase format.

The hydro-flattened bare earth DEM was generated using the lidar bare earth points and 3D hydro breaklines to a resolution of 1 meter. The bare earth points that fell within 1*NPS along the hydro breaklines (points in class 10) were excluded from the DEM generation process. This is analogous to the removal of mass points for the same reason in a traditional photogrammetrically compiled DTM. This process was done in batch using proprietary software. The technicians then used Fugro proprietary software for the production of the lidar-derived hydro-flattened bare earth DEM surface in initial grid format at 1 meter GSD. Water bodies (inland ponds and lakes), inland streams and rivers, and island holes were hydro-flattened within the DEM. Hydro-flattening was applied to all water impoundments, natural or man-made, nominally larger than 2 acres in area and to all streams nominally wider than 15.25 meters. This process was done in batch. Once the initial, hydro-flattened bare earth DEM was generated, the technicians checked the tiles to ensure that the grid spacing met specifications. The technicians also checked the surface to ensure proper hydro-flattening. The entire data set was checked for complete project coverage. Once the data was checked, the tiles were then converted to .IMG format. Georeference information is included in the raster files.

The NOAA Office for Coastal Management (OCM) downloaded 9071 raster DEM files in img format from TNRIS at this site: https://data.tnris.org/collection/b5bd2b96-8ba5-4dc6-ba88-d88133eb6643. The data were in UTM14 (913 files) and UTM15 (8158 files) NAD83(2011), meters coordinates and NAVD88 (Geoid12b) elevations in meters. The bare earth raster files were at a 1 meter grid spacing.

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. Used internal script to assign the EPSG codes and convert to GeoTiff format.

2. Copied to the files to https.