Abstract
This paper details the collection, geo-referencing, and data processing algorithms for a fully-automated, permanently deployed terrestrial lidar system for coastal monitoring. The lidar is fixed on a 4-m structure located on a shore-backing dune in Duck, North Carolina. Each hour, the lidar collects a three-dimensional framescan of the nearshore region along with a 30-min two-dimensional linescan time series oriented directly offshore, with a linescan repetition rate of approximately 7 Hz. The data are geo-referenced each hour using a rigorous co-registration process that fits 11 fixed planes to a baseline scan to account for small platform movements, and the residual errors from the fit are used to assess the accuracy of the rectification. This process decreased the mean error (defined as the magnitude of the offset in three planes) over a two-year period by 24.41 cm relative to using a fixed rectification matrix. The automated data processing algorithm then filters and grids the data to generate a dry-beach digital elevation model (DEM) from the framescan along with hourly wave runup, hydrodynamic, and morphologic statistics from the linescan time series. The lidar has collected data semi-continuously since January 2015 (with gaps occurring while the lidar was malfunctioning or being serviced), resulting in an hourly data set spanning four years as of January 2019. Examples of data products and potential applications spanning a range of spatial and temporal scales relevant to coastal processes are discussed.