Pre-Processing LiDAR Data for Coastal Hazards Visualization
Various disciplines and agencies depend on highly accurate elevation data to accomplish a multitude of tasks. Engineers might utilize accurate elevation data in the construction of bridges and roads, while academics and researchers might use the elevation data to identify tree canopies or to locate various features on the earth, such as streambeds to track sediment flow. Coastal hazards researchers at RENCI at ECU have recently started using these data with complex models to identify areas that may be affected by storm surge and overwash in the event of an extreme coastal storm or hurricane.
One of the best sources of raw elevation data is LiDAR. LiDAR is an acronym for "Light Detection and Ranging" and is a method of remote sensing extensively used by the National Oceanic and Atmospheric Administration (NOAA), a federal agency focused on the conditions of the oceans, adjacent coastal land and habitats, coastal disasters, and the atmosphere. NOAA gathers this elevation data by mounting a laser to an aircraft and flying paths over the beach and recording the amount of time it takes the beam of light to travel to the earth and back. For topographic mapping, this time-value can be used to calculate the elevation of beaches, dunes, and infrastructure on the ground below.
The coastal hazards researchers and GIS analysts at RENCI at ECU received approximately 250 GB of raw LIDAR data, straight off the plane from the NOAA National Geodetic Survey (NGS) Remote Sensing Division, to research storm surge and overwash vulnerability and visualization. The data collected by the NGS-led Integrated Ocean and Coastal Mapping (IOCM) project required some preprocessing before it could be used with the models being developed for visualizations. Various issues included removal of light/telephone poles or other anomalous "artifacts" (birds) from the elevation surface. When the raw LiDAR data is interpolated into a surface, the light poles create artificial "spikes" and would inhibit the accurate representation of storm surge and over wash in the model (Figure 1).
Much work with LiDAR data and elevation surfaces seeks to remove all buildings and vegetation from their underlying surfaces to create what is called a "bare-earth" digital elevation model (DEM.) The researchers at RENCI at ECU decided that the buildings were necessary in the visualization process and opted not to remove them.
Many other steps were also involved in the clean-up process. Elevation values need to be corrected for the local area using a tool from NOAA, and a variety of data conversions are needed to get the data in the right format.
The results are an interpolated raster grid (Figure 2), which is then viewed as a 3D surface and draped with an aerial orthophotograph (Figure 3), also acquired by the IOCM project. The interpolated raster grid and the associated 3D images are now ready to be used in the storm surge models.