Data Management Plan

Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a survey of Coastal California. The project area consists of approximately 2616 square miles. The project design of the LiDAR data acquisition was developed to support a nominal post spacing of 1 meter. Fugro EarthData, Inc. acquired 1546 flight lines in 108 lifts between October 2009 and August 2011. This collection was a joint effort by the NOAA Office for Coastal Management (OCM); the California State Coastal Conservancy (SCC) Ocean Protection Council (OPC); Scripps Institution of Oceanography; and the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). The data coverage extends landward 500 m from the shoreline, along the entire California coastline. The data collection was performed with two Piper Navajo twin engine aircrafts, utilizing a Leica ALS60 MPiA sensor; collecting multiple return x, y, and z as well as intensity data. The data were classified as Unclassified (1), Ground (2), Low Point (Noise) (7), Water (9), Mudflats (10), and 12 (Overlap). Only the Unclassified (1), Ground (2), Water (9), and Overlap (12) points are available for download from the NOAA OCM Digital Coast.

Original contact information:

Contact Org: NOAA Office for Coastal Management

Phone: 843-740-1202

Email: coastal.info@noaa.gov

Process Steps:

• 2011-08-04 00:00:00 - All acquired LiDAR data went through a preliminary review to assure that complete coverage was 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 is 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 immediately processed using the airport GPS base station data, which was available to the flight crew upon landing the plane. This ensured the integrity of all the mission data. These results were also used to perform the initial LiDAR system calibration test. 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 was used in this process, which contains the latest calibration parameters for the sensor. The technician also generated flight line trajectories for each of the flight lines during this process. 3) Verification of Coverage and Data Quality - Technicians checked flight line trajectory files to ensure completeness of acquisition for project flight lines, calibration lines, and cross flight lines. The intensity images were generated for the entire lift at the required post spacing for the project. The technician visually checked the intensity images against the project boundary to ensure full coverage. 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 few sample TIN surfaces to ensure no anomalies were present in the data. Turbulence was inspected for and if it affected the quality of the data, the flight line was rejected and reflown. The technician also evaluated the achieved post spacing against project specified post spacing.
• 2011-09-19 00:00:00 - 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) Technician 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) Technician first used commercial software to calculate initial boresight adjustment angles based on sample areas selected in the lift- mini project. 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 result and made any necessary additional adjustment until it is acceptable for the mini project. 3) Once the boresight angle calculation was done for the mini project, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technician 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 the boresight adjustment was completed for each lift individually, the technician ran a routine to check the vertical misalignment of all flight lines in the project and also compared data to ground truth. The entire dataset was then adjusted to ground control points. 5) The technician ran a final vertical accuracy check between the adjusted data and surveyed ground control points after the z correction. The result was analyzed against the project specified accuracy to make sure it meets the project requirements. 6) The flight lines collected under the following programs: National Coastal Mapping Program - JALBTCX and Coastal California LiDAR and Digital Imagery for NOAA OCM in partnership with the SCC were tied together in the boresight process. Control points are shared in both projects. The overlap between flight lines from both projects was compared for matching.
• 2011-10-20 00:00:00 - Once boresighting is complete for the project, the project was set up for classification. The LiDAR data was cut to production tiles. The flight line overlap points, Noise points and Ground points were classified automatically in this process. Fugro EarthData, Inc. has developed a unique method for processing LiDAR data to identify and re-classify elevation points falling on vegetation, building, and other above ground structures into separate data layers. The steps are as follows: 1) Fugro EarthData, Inc. utilized commercial software as well as proprietary software for automatic filtering. The parameters used in the process were customized for each terrain type to obtain optimum results. 2) The Automated Process typically re-classifies 90-98% of points falling on vegetation depending on terrain type. 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 features were filtered out, the data was either run through a different filter or was corrected during the manual filtering process. 3) Interactive editing was completed in 3D visualization software which also provides manual and automatic point classification tools. Fugro EarthData, Inc. used commercial and proprietary software for this process. Vegetation and artifacts remaining after automatic data post-processing were reclassified manually through interactive editing. The hard edges of ground features that were automatically filtered out during the automatic filtering process were brought back into ground class during manual editing. Auto-filtering routines were utilized as much as possible within fenced areas during interactive editing for efficiency. The technician reviewed the LiDAR points with color shaded TINs for anomalies in ground class during interactive filtering. 4) All LAS tiles went through peer review after the first round of interactive editing was finished. This helps to catch misclassification that may have been missed by the interactive editing. 5) Upon the completion of peer review and finalization of bare earth filtering, the classified LiDAR point cloud work tiles went through a water classification routine based on the collected water polygons.
• 2011-10-20 00:00:00 - 6) Upon the completion of finalization of the classified LiDAR point cloud work tiles, the topographic LiDAR classified point cloud data that was produced under the JALBTCX and NOAA OCM programs was merged. The following methodology was used: a) due to the differences in deliverable specifications between the two projects, the technician re-projected the data covered by JALBTCX to UTM zones 10 and 11 north, NAD83 (NSRS2007), NAVD88, meters. Once complete, the JALBTCX data was reformatted to LAS 1.2 format in accordance with the NOAA OCM project requirements. The time stamps for all points that are stored in GPS Weekly Time were converted to Adjusted Standard GPS time using proprietary software developed by Fugro EarthData, Inc. The data collection date and the current GPS time stamp were used in calculating the Adjusted Standard GPS time. The technician applied the same time stamp conversion to the flight lines collected and processed for JALBTCX project that were used in NOAA OCM project; b) the technician clipped the NOAA OCM dataset to the inland 500 meter boundary line used in the JALBTCX project. There were not any gaps or overlap between the coverage from these two projects; c) once the process finished, the reformatted JALBTCX data and final NOAA OCM LiDAR classified point cloud data were packaged into NAD83 (NSRS2007), UTM zones 10 and 11 north, meters; NAVD88, meters, using GEOID09 together for delivery. The data was also cut to the approved 1500 meter by 1500 meter tile layout and clipped to the approved project boundary. The technician checked the output LAS files for coverage and format; d) the technician then QC'ed the merged dataset for quality assurance and enhanced the Bare Earth classification in the JALBTCX area for consistent data quality; e) these final LiDAR tiles were then used in the hydro flattening process. Water classification in some JALBTCX areas was modified in order to achieve the best hydro flattening result. 7) The classified LiDAR point cloud data were delivered in LAS 1.2 format: 1 unclassified, 2 ground, 7 low points, 9 water, 10 mudflats, and 12 overlap points.
• 2012-01-01 00:00:00 - The NOAA Office for Coastal Management (OCM) received the files in las format. The files contained lidar elevation and intensity measurements. The data were in UTM Zones 10 and 11 coordinates and NAVD88 Geoid 09 vertical datum. Only points classified as Unclassified (1), Ground (2), Water (9), and Overlap (12) were made available for download. OCM performed the following processing for data storage and Digital Coast provisioning purposes: 1. The data were converted from UTM coordinates to geographic coordinates. 2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid 09. 3. The data were filtered to remove outliers. 4. The LAS data were sorted by latitude and the headers were updated.

This data can be obtained on-line at the following URL:

https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=1124

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