gov.noaa.nmfs.inport:76848 eng UTF8 dataset Elevation OCM Partners resourceProvider NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact 2026-04-30T00:00:00 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) EPSG::5703 EPSG::6343 EPSG::6344 2019 USGS Lidar DEM: Matagorda Bay, TX 2019 creation 2025 publication NOAA/NMFS/EDM 76848 https://www.fisheries.noaa.gov/inport/item/76848 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9029/supplemental/TX_Matagorda_Bay_2018_D18_Accuracy_Report_20191022.pdf WWW:LINK-1.0-http--link Accuracy Report Link to data set accuracy report. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9029/supplemental/Matagorda_TX_report.pdf WWW:LINK-1.0-http--link Dataset report Link to data set report. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9029/supplemental/TX_Matagorda%20Bay_2018_D18_2018_D18_Process_Descriptions.pdf WWW:LINK-1.0-http--link Dataset report Link to data set report. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9029/supplemental/TX_Matagorda%20Bay_2018_D18_Collection_Report.pdf WWW:LINK-1.0-http--link Dataset report Link to data set report. download https://coast.noaa.gov/dataviewer/ WWW:LINK-1.0-http--link NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) 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. download Original Product: These are Digital Elevation Model (DEM) data. Class 2 (ground) lidar points in conjunction with the hydro breaklines were used to create a 1.0 meter hydro-flattened Raster DEM. Original Geographic Extent: The entire project area covers 705 square miles in coastal Texas along Matagorda Bay. Original Dataset Description: This TX_Matagorda Bay_2018_D18 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at an aggregate nominal pulse spacing (ANPS) of 1.0 meters (4ppsm). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), Universal Transverse Mercator zone 14N and 15N, meters and vertical datum of NAVD88 (GEOID12B), meters. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 1500 m x 1500 m tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 1500 m x 1500 m schema. Ground Conditions: Lidar data was collected from January 24 through January 29, 2019 while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Terrasurv, Inc. established a total of 12 ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional 80 independent accuracy checkpoints, 45 NVA points and 35 VVA points, were used to assess the vertical accuracy of the data. One additional NVA checkpoint collected by Terrasurv in 2018 was used to assess the vertical accuracy of the raw point cloud data along with the 45 NVA points collected in 2019. These checkpoints were not used to calibrate or post process the data. This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the GeoTIFF files hosted by USGS on Amazon Web Services. This high resolution lidar data will support the Natural Resources Conservation Service (NRCS) initiatives. USGS, Fugro completed NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information custodian notPlanned https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9029/supplemental/extent_MatagordaBay2018_m9029.kmz This graphic displays the footprint for this lidar data set. KML EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM) EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION theme Global Change Master Directory (GCMD) Science Keywords 23.3 CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > TEXAS VERTICAL LOCATION > LAND SURFACE place Global Change Master Directory (GCMD) Location Keywords 23.3 LIDAR > Light Detection and Ranging instrument Global Change Master Directory (GCMD) Instrument Keywords 23.3 Airplane > Airplane platform Global Change Master Directory (GCMD) Platform Keywords 23.3 DEMs - partner (no harvest) project InPort otherRestrictions Cite As: OCM Partners, [Date of Access]: 2019 USGS Lidar DEM: Matagorda Bay, TX [Data Date Range], https://www.fisheries.noaa.gov/inport/item/76848. NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose. otherRestrictions Access Constraints: None otherRestrictions Use Constraints: 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. otherRestrictions Distribution Liability: Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners. unclassified 2019 USGS Lidar: Matagorda Bay, TX NOAA/NMFS/EDM 58921 crossReference grid 1 eng; US elevation POSGNS 5.2; POSPac 6.2; RiProcess 1.8.3; RiWorld 5.0.2; RiAnalyze 6.2; RiServer 1.99.5; Microstation CONNECT 10.00.00.25; TerraScan 017.039 and 016.013; TerraModeler 016.001; Lasedit 1.35.07; GeoCue 2014.1.21.5; ArcMap 10.3; Global Mapper 17.1.2; ERDAS Imagine 2016; PhotoShop CS8; Fugro proprietary software; Windows 7 64-bit Operating System \\server\directory path\*.las \\server\directory path\*.las \\server\directory path\*.img \\server\directory path\*.gdb \\server\directory path\*.tif/tfw 1440 GB -96.392059 -95.936004 28.358147 29.141899 Collection Dates | Currentness: Ground Condition 2019-01-24 Collection dates. | Currentness: Ground Condition 2019-01-25 Collection dates. | Currentness: Ground Condition 2019-01-27 Collection dates. | Currentness: Ground Condition 2019-01-28 Collection dates. | Currentness: Ground Condition 2019-01-29 USGS Contract No. G17PC00015 CONTRACTOR: Fugro Geospatial, Inc. SUBCONTRACTOR: Terrasurv, Inc. Ground control and checkpoints collected by Terrasurv, Inc. All processing was completed by the prime contractor. DEM Raster File Type = ERDAS IMAGINE Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 1.0 Meter Interpolation or Resampling Technique = Triangulated Irregular Network (TIN) Network Required Vertical Accuracy = 19.6 cm NVA Zip GeoTIFF GeoTIFF NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information distributor U.S. Geological Survey 12201 Sunrise Valley Drive Reston VA 20191 USA https://usgs.gov WWW:LINK-1.0-http--link USGS Home Home page for USGS information distributor https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10408/details/10408 WWW:LINK-1.0-http--link Customized Download Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base. download https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/TX_MatagordaBay_B1_2018/TIFF/ WWW:LINK-1.0-http--link Bulk Download Bulk download of data files in GeoTIFF format, in UTM Zone 14N NAD83 (2011) meters coordinates and elevations in NAVD88(GEOID12B) meters. download https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/TX_MatagordaBay_B2_2018/TIFF/ WWW:LINK-1.0-http--link Bulk Download Bulk download of data files in GeoTIFF format, in UTM Zone 15N NAD83 (2011) meters coordinates and elevations in NAVD88(GEOID12B) meters. download dataset Horizontal Positional Accuracy The horizontal errors in lidar data are largely a function of the Global Navigation Satellite System (GNSS) positional errors, the Inertial Measurement Unit (IMU) angular errors, and the flying altitude. If the accuracy of the GNSS/IMU solution is known for the specific POS system, using the flying altitude of the project the expected horizontal errors in the LiDAR data can be estimated. Following the formula in the ASPRS Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0. - November, 2014), using the specifications of the POS system used and 2774 m flying altitude above ground, the estimated horizontal accuracy is RMSEr = 0.354 m. Vertical Positional Accuracy The project specifications require that the Non-Vegetated Vertical Accuracy (NVA) be computed for raw lidar point cloud swath files. The required accuracy (ACCz) is: 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSEz of 10 cm in the open terrain and/or Urban land cover categories. This is a required accuracy. The NVA for the AOI was tested with 46 checkpoints. The project specifications also require the accuracy (ACCz) of the derived DEM be calculated and reported in three ways: 1. The required RMSEz (non-vegetated) is less than or equal to 10 cm. The RMSEz for the AOI was tested with 46 checkpoints. 2. The required NVA is: less than or equal to 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSEz of 10 cm in the open terrain and/or Urban land cover categories. This is a required accuracy. The NVA for the AOI was tested with 45 6heckpoints. The vegetated Vertical Accuracy (VVA): The required VVA is: less than or equal to 29.4 cm at a 95th percentile level, derived according to ASPRS Guidelines, Vertical Accuracy for Reporting LiDAR Data, i.e. based on the 95th percentile error in Vegetated land cover categories combined (Crops, Agriculture, Brush, Woods). This is a required accuracy. The VVA for the AOI was tested with 35 checkpoints. The checkpoints were independent and not used in the calibration or post processing of the lidar point cloud data. The surveyed checkpoints were distributed throughout the project area. UTM 14 Files The RMSEz (non-vegetated) of the DEM was calculated using 36 independent checkpoints and was tested to be 0.035 meters. The VVA was 0.25 meters at a 95th percentile level derived according to ASPRS Guidelines, Vertical Accuracy Reporting for LiDAR Data. The VVA of the DEM was calculated using 30 independent checkpoints. UTM 15 Files The RMSEz (non-vegetated) of the DEM was calculated using 10 independent checkpoints and was tested to be 0.05 meters. The VVA was 0.172 meters at a 95th percentile level derived according to ASPRS Guidelines, Vertical Accuracy Reporting for LiDAR Data. The VVA of the DEM was calculated using 5 independent checkpoints. Completeness Report A complete iteration of processing (GPS/IMU Processing, Raw Lidar Data Processing, and Verification of Coverage and Data Quality) was performed to ensure that the acquired data was complete, uncorrupted, and that the entire project area had been covered without gaps between flight lines. No void areas or missing data exist. The raw point cloud is of good quality and data passes Vertical Accuracy requirements. The Classified Point Cloud data files include all data points collected except the ones from Cross ties and Calibration lines. The points that have been removed or excluded are the points fall outside the project delivery boundary. Points are classified. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The classified point cloud is of good quality and data passes Vertical Accuracy requirements. The Intensity Image files cover the entire project delivery boundary. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The Intensity Image product is of good quality. The Hydro Breaklines cover the entire project delivery boundary and extend beyond the boundary in a few locations. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The Hydro Breakline product is of good quality. The DEM raster files cover the entire project delivery boundary. The pixels that fall outside the project delivery boundary are set to Void with a unique NODATA value. The value is identified in the file headers. There are no void pixels inside the project boundary. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The bare earth surface is of good quality and passes Vertical Accuracy requirements. Conceptual Consistency Compliance with the accuracy standard was ensured by the collection of ground control and the establishment of GPS base stations in the project area. The following checks were performed: 1) The lidar data accuracy was validated by performing a full boresight adjustment and then checking it against the ground control prior to generating a digital terrain model (DTM) or other products. 2) Lidar elevation data was validated through an inspection of edge matching and visual inspection for quality (artifact removal). The following software was used for the validation: 1) RiProcess 1.8.3, RiWorld 5.0.2, RiAnalyze 6.2, RiServer 1.99.5; and 2) Fugro proprietary software; 20180607. The NOAA Office for Coastal Management (OCM) ingested references to the USGS GeoTIFF files that are hosted on Amazon Web Services (AWS), into the Digital Coast Data Access Viewer (DAV). The DAV accesses the raster data as it resides on AWS. Flight status was communicated during data collection. 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. The following GPS base station was utilized: Fugro (FGI_8003, TXPV, TXBC, FUSAL_100, temp_LBX). 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 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 ANPS. Visual checks of the intensity images against the project boundary were performed to ensure full coverage to the 100 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 1.0 meter ANPS as well as making sure there is no clustering in point distribution. 2019-02-15T00:00:00 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 6 cm within individual swaths (smooth surface repeatability) and 8 cm RMSD within swath overlap (between adjacent swaths) with a maximum difference of ± 16 cm. 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed check points after the z correction to ensure the requirement of RMSEz (non-vegetated) 10 cm, NVA 19.6 cm 95% Confidence Level was met. 2019-03-30T00:00:00 Once boresighting was complete for the project, the project was first set up for automatic classification. The lidar data was cut to production tiles. The low noise points, high noise points and ground points were classified automatically in this process. 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. 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 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, clipped to project boundary including the 100 meter buffer and formatted to LAS v1.4. It was also re-projected to UTM Zone 14 north or 15 north; NAD83 (2011), meters; NAVD88 (GEOID12B), meters. The file header was formatted to meet the project specification with File Source ID assigned. 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 at a precision sufficient to allow unique timestamps for each pulse. Correct and properly formatted georeference information as Open Geospatial Consortium (OGC) well known text (WKT) was assigned in all LAS file headers. Each tile has unique File Source ID assigned. 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; Class 4, Medium Vegetation; Class 5, High Vegetation; Class 6, Building; Class 7 - Low Noise; Class 9 - Water; Class 10 - Ignored Ground; Class 14, Culverts; Class 17 - Bridge Decks; and Class 18 - High Noise. The classified point cloud data was delivered in tiles without overlap using the project tiling scheme. 2019-03-30T00:00:00 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 approximately 2-acre or greater surface area and approximately 1-acre islands and 2) Inland Streams and Rivers of 100 feet nominal width. Additionally, all breaklines used to enforce a logical terrain surface below a bridge were delivered as a separate shapefile. After initial collection, features were combined into working regions based on watershed sub-basins. Linework was 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, with no overlaps or anomalies. 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 used their best professional cartographic judgement in determining where the water met the ground surface. Low Confidence Area (LCA) shapefiles were provided explaining the addition of the sampling of the LCAs. 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 10.2.2 geodatabase format. 2019-05-30T00:00:00 The bare earth DEM was generated using the lidar bare earth points and 3D hydro breaklines to a resolution of 1.0 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 1.0 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, that are larger than approximately 2 acres in area and to all streams that are nominally wider than 100 feet. 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 industry-standard, GIS-compatible, 32-bit floating point raster format (ERDAS Imagine .img). Georeference information is included in the raster files. Void areas (i.e., areas outside the project boundary but within the tiling scheme) are coded using a unique NODATA value. 2019-06-15T00:00:00 The NOAA Office for Coastal Management (OCM) created references to the USGS GeoTIFF files that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the raster data as it resides on Amazon Web Services (AWS). These are the GeoTIFF files that are being accessed: https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/TX_MatagordaBay_B1_2018/TIFF/ https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/TX_MatagordaBay_B2_2018/TIFF/ 2025-08-08T00:00:00 NOAA Office for Coastal Management (843) 740-1202 coastal.info@noaa.gov processor Source Contribution: Under Fugro’s direction, all surveying activities were performed by Fugro's approved ID/IQ subcontractor Terrasurv, Inc. A total of 12 ground control points to support the lidar collection, along with 45 NVA and 35 VVA checkpoints were collected. The National Spatial Reference System (NSRS) was used to provide control for the network. Three Continuously Operating Reference Stations (CORS) were included in the network, as well as two existing NSRS benchmarks. The horizontal datum was the North American Datum of 1983 – NAD83 (2011), epoch 2010.0. The vertical datum was the North American Vertical Datum of 1988 (NAVD88), realized with GEOID12B. Matagorda, TX Report of Survey 2019-03-01 publication Terrasurv, Inc. originator 2019-01-15 2019-03-01 Source Contribution: Fugro collected ALS-derived lidar over the TX_Matagorda Bay_2018_D18 AOI with 1.0 meter ANPS. Data was collected when environmental conditions meet the criteria specified. To be specific, the following conditions existed prior to launch of the aircraft: 1) Cloud and fog-free between the aircraft and ground, 2) Snow free, 3) No unusual flooding or inundation, and 4) Leaf off. The collection for the TX_Matagorda Bay_2018_D18 AOI was accomplished on January 24, 25, 27, 28 and 29; data was acquired in 7 lifts. Lift 190124_133_33780026_01; lift 190125_130_33780026_01; lift 190125_130_33780026_02, lift 190125_133_33780026_02, lift 190127_130_33780026_03, lift 190128_130_33780026_04, and lift 190129_130_33780026_05. The collection was performed using Leica ALS80 lidar systems, serial numbers 130 and 133. TX_Matagorda Bay_2018_D18 2019-09-17 publication Fugro originator USGS AWS GeoTIFF Files - TX_MatagordaBay_B1 USGS https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/TX_MatagordaBay_B1_2018/TIFF/ WWW:LINK-1.0-http--link USGS AWS GeoTIFF Files for TX_MatagordaBay_B1 Source Citation URL information publisher USGS AWS GeoTIFF Files - TX_MatagordaBay_B2 USGS https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/TX_MatagordaBay_B2_2018/TIFF/ WWW:LINK-1.0-http--link USGS AWS GeoTIFF Files for TX_MatagordaBay_B2 Source Citation URL information publisher