Abstract:

This dataset contains a combined 1-meter topographic and bathymetric digital elevation model (DEM) in ASCII grid format created from Light Detection and Ranging (LiDAR) point data and echosounder bathymetric data of the Nueces River Delta located northwest of Corpus Christi, Texas, within Universal Transverse Mercator (UTM) Zone 14N. The LiDAR X, Y, and Z point data were collected between 2007-02-04 and 2007-02-06 generated by combining laser range and aircraft altitude data collected using an airborne LiDAR instrument with once-per-second data collected using geodetic quality (dual phase) Global Positioning System (GPS) airborne and ground-based receivers. The bathymetric data were collected between 2008-10-11 and 2008-11-07. This survey provided water depth data in support of the LiDAR survey flown and processed by the Bureau of Economic Geology (BEG) at the University of Texas at Austin (UT) for the Coastal Bend Bays and Estuaries Program (CBBEP). The subject site is comprised of approximately 2500 acres of the Nueces River Delta under the control of CBBEP. Bathymetric data were collected by Environmental Risk Information Services (ERIS), Environmental and Geographic Information System (GIS) Consulting.

Suggested Citation:

Gibeaut, James, Tiffany Hepner, John Andrews, and Rebecca Smyth. 2021. Nueces River Delta 1-meter Topobathy Digital Elevation Model, 2007-02-04 to 2008-11-07. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/4Q6E7FXR

Purpose:

The Bureau of Economic Geology (BEG) at the University of Texas at Austin (UT) used airborne LiDAR (light detection and ranging) and shallow-water echo sounding to provide terrain elevation data of approximately 1000 hectares of wetlands, ponds, and adjacent uplands on the Nueces River Delta, Texas. The purpose of this collaborative research effort between the University of Texas Marine Science Institute (UTMSI) and the BEG will be to develop a research-quality digital elevation model (DEM) that will be used to (1) better understand how vegetation assemblages are correlated with elevation, (2) map habitats in conjunction with aerial photography, and (3) design freshwater diversion projects.

Data Parameters and Units:

Elevation (m) and depth (m).

Methods:

GPS and XYZ-Point Data Processing: Transfer raw ALTM 1225 flight data (laser ranges with associated scan angle information and IMU data), airborne GPS data collected at 1 Hz using Ashtech receiver, and ground-based GPS data collected at 1 Hz using Ashtech Z-12 receivers to processing computer. Generate decimated LiDAR point file from the above three data sets using Optech's Realm 2.27 software. This is a 9-column ASCII data set with the following format: time tag: first pulse Easting, Northing, HAE; last pulse Easting, Northing, HAE; first pulse intensity; and last pulse intensity. View decimated lidar point file to check data coverage (i.e. sufficient overlap of flight lines and point spacing). Compute base station coordinates using National Geodetic Survey's PAGES-NT software. Compute aircraft trajectories from each base station GPS dataset using National Geodetic Survey's KINPOS software. Solutions for base stations coordinates and aircraft trajectories are in the International Terrestrial Reference Frame of 2000 (ITRF2000). The final aircraft trajectory used only the White Point tide gauge base station. Transformed trajectory solution from ITRF 2000 to North American Datum of 1983 (NAD83) using the National Geodetic Survey's Horizontal Time-Dependent Positioning software (http://www.ngs.noaa.gov/TOOLS/Htdp/Htdp.html). Input NAD83 trajectories and aircraft inertial measurement unit data into Applanix's POSProc version 2.1.4 to compute an optimal 50 Hz inertial navigation solution (INS) and smoothed the best estimate of the trajectory (SBET). Substitute the INS and SBET into Realm 2.27. Generate a set of initial LiDAR instrument calibration parameters (pitch, roll, scale) for each lidar flight, and then incrementally improve parameters by iteratively comparing a subset of the lidar output to the GPS kinematic ground control. Once the instrument calibration parameters are sufficiently accurate, create the complete lidar point file (9-column ASCII file) for the entire survey area in Universal Transverse Mercator (UTM) Zone 14 with elevations being heights above the GRS-80 reference ellipsoid (HAE). Transfer point file to UNIX workstation. Parse the 9-column LiDAR point file into 3.75-minute quarter-quadrangle components and apply bias correction to the first and last pulse. Grid the quarter-quad point files with software written by Bureau personnel. This in-house gridding software uses a weighted inverse distance algorithm to interpolate cell values. Simultaneously grid the four following data attributes: first return z, first return intensity, second return z, and second return intensity. The quarter-quad grids are merged into one single grid for the entire area. Data are then output into a raw 4-byte binary raster file. Using this format, we can generate multi-band, band interleave files containing one, two, three, or all four of the attribute data referenced above. Additionally, output a header file in ERMapper's ".ers" format for the binary file so that the data can be viewed in ERMapper or ArcView, with the appropriate ECW plug-in. These header files contain the same information as the ArcInfo-format header files (except the coordinate values are of the upper-left cell) plus datum and projection information. Bathymetric Survey: Survey control consists of the Primary Control Point (Monument number 90011-C) at White Point Tide Station that has been set into the TCOON Tide Station program by CBI (Conrad Blucher Institute). The Primary Control Point (Monument number 90011-C) with coordinates set to NAD 83 UTM14 meters was provided to ERIS by CBI. ERIS used this information (Northing: 3082700.9870, Easting: 649376.6410, Elevation:1.32M) in establishing the RTK base station for all RTK surveys of water depths. The equipment ERIS used to establish both horizontal and vertical control consisted of an RTK base unit and two RTK rover units with ruggedized field data recorders running Carlson Surv CE survey software. The bathymetric data was collected using an Odom Hydrographic unit with a ruggedized PC Tablet running HYPAC software for the data capture. Methods used for the Bathymetric survey consisted of two different types of data collection. The first method used an airboat from UTMSI (University of Texas Marine Science Institute) and a shallow water survey vessel provided by ERIS. The survey dates for these two boats started on October 11th, 2007, and continued on the 16th, 17th, 18th, 19th, 24th and November 5th. The Odom Hydrotrac collected the bathymetric data with a Navcom RT 3010S rover unit providing centimeter level reference information for the horizontal and vertical components of the HYPACK software. These two boats were used to run and collect data in waters from half a meter to 3 meters. Special mount rigging for the boats that were developed by ERIS was used to run in shallow water and allowed the RTK Rover unit to be positioned in line with the hydrographic transducer. This coupled with settings in the HYPAC software allowed the data to be collected directly in ellipsoid height so there was no need to apply a draft or tide correction in the post-processing. The transducer had to be muffled down in water less than one meter so as to maintain data integrity. A calibration process was followed at the start of each day run as well as spot checks throughout the day, using the second rover pole unit stored onboard the boat. This process consisted of setting the Hypack software to accept the RTK readings from the Navcom rover unit and output the raw data in ellipsoid height. The boat was then made stationary in approximately one meter of water, and a reading was taken on the bottom. The second rover pole unit was then lowered to the bottom at the same point where the transducer was located, and a reading was taken. These two ellipsoid height readings were checked for consistency. This rover pole unit was also calibrated to CBI’s secondary monument (Monument number 90011-F) at White Point to ensure accurate readings from the base reference unit at the start of each day. Surveys were conducted in areas according to pre-planned survey files provided by the Bureau of Economic Geology, and each day’s data collection was downloaded and electronically transmitted to them for review. The Odom echosounder acquired depth soundings at a rate of about 20 soundings per second, while the GPS system acquired position fixes at a rate of 1 time per second. The Hypac software output time-tagged soundings and GPS records to a single file that was then post-processed with a custom FORTRAN program. The soundings were processed to eliminate spikes caused by water column returns, transducer ringing, and other acoustic noise and to take advantage of and reduce redundant soundings acquired in close proximity. For each second, the speed of the boat was determined from the NMEA standard GPS string “$GPVTG”, and the amount of time for the boat to travel 0.5 m was computed. Using time tags in the data strings, the soundings that occurred within the amount of time for the boat to travel 0.5 m of a GPS position fix were averaged and the standard deviation determined. All soundings greater than 3 times the standard deviation from the average were then removed and the average recalculated. After removing the outliers, the typical standard deviation of the soundings was 0.025 m, and the typical number of soundings used to compute the average was 25, although this number varies depending on the speed of the boat. The vertical (z) position of the bottom for each GPS fix was then computed by adding the average of the depth soundings plus the distance from the transducer on one end of the survey pole to the phase center of the GPS antenna on the other end of the pole plus the ellipsoid height determined via RTK GPS of the antenna phase center as already described. The bathymetry files are output in ASCII format in 9 columns with one header line. The second method used for waters too shallow or not accessible by the boats was accomplished by a more traditional survey method of walking them and using RTK Rover poles. Most of these areas were in the upper Delta region and the two rover units were calibrated to the White Point secondary monument (number 90011-F) at the beginning of each day; both units were configured to read in the same ellipsoid height readings as the bathymetric data collected by the boats. The walking surveys were performed on 2007-10-30 and continued on 2007-10-31 and 2007-11-01. ATVs from ERIS were used to get the survey crews to each of the survey areas quickly and cost-effectively. This bathymetric file was output in ASCII format in 6 columns with one header line. Digital Elevation Model Creation: We used aerial photography to draw polygons delineating water bodies in the survey area. These polygons were then used to clip the LiDAR grid, resulting in numerous NULL-value regions throughout the grid. Many of these regions were afterwards filled in with bathymetric data, as follows. First, the polygons used for clipping were also converted to a point file with an average spacing of approximately 3 meters. Using ArcView/Spatial Analyst, elevation values for each point were extracted from the LiDAR grid and assigned to their respective points. Bathymetric data were collected by ERIS Environmental and GIS Consulting. These two point files were combined into a single file. Next, we added numerous additional points and assigned elevation values based on our interpretation of the bathymetric trends. These data were then gridded using ArcView/Spatial Analyst to generate our bathymetric grid. Finally, these two grids--the clipped lidar grid, above, and the bathymetric grid--were combined in ERMapper to create a single elevation model including both topographic and bathymetric data. The final step was to use the Geiod99 geoid model to convert z-values from the height above the GRS80 Ellipsoid to elevations with respect to the North American Vertical Datum 88 (NAVD88). An in-house program was used to convert the grids to an ASCII file format.

Instruments:

Optech Inc. ALTM 1225, Ashtech Z-12 GPS receiver, Odom Hydrotrac echosounder, Navcom RT 3010S rover unit.

Error Analysis:

Horizontal_Positional Accuracy_Report: Selected portions from each LiDAR dataset (last return only) were used to generate a 1m x 1m digital elevation model (DEM). Data estimated to have a horizontal accuracy of 0.01-0.03m from ground surveys using kinematic GPS techniques were superimposed on the LiDAR DEM and examined for any mismatch between the horizontal position of the ground GPS and the corresponding feature on the LiDAR DEM. Horizontal agreement between the ground kinematic GPS and the LiDAR was within the resolution of the 1m x 1m DEM. Vertical_Positional_Accuracy_Report: Ground GPS surveys were conducted within the LiDAR survey area to acquire ground "truth" information. The ground survey points are estimated to have a vertical accuracy of 0.01-0.05m. Roads, which are open areas with an unambiguous surface, were surveyed using kinematic GPS techniques. A LiDAR dataset was sorted to find data points that fell within 0.5m of a ground GPS survey point. The mean elevation difference between the LiDAR and the ground GPS was used to estimate and remove an elevation bias from the LiDAR. The standard deviation of these elevation differences provides estimates of the LiDAR precision. The February 2007 Nueces River Delta LiDAR dataset was determined to have an average elevation bias of 0.06m (TIM1) and 0.05m (TIM2) when compared to ground truth. Vertical biases were determined for and removed from each flight (numbered by Julian day). Over the calibration target, average RMS for first return is 0.041m and second return is 0.063m.

Provenance and Historical References:

Wehr, A., & Lohr, U. (1999). Airborne laser scanning—an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2-3), 68–82. doi:10.1016/s0924-2716(99)00011-8

Individual Files: