WATER COLUMN COMPENSATION USING SUBMERSIBLE CALIBRATION TARGETS FOR 3D LIDAR BATHYMETRY

Bathymetric mapping in shallow waters is challenged by several environmental factors that reduce the signal dynamic range, resolution, and maximum detectable depth. Drone-based bathymetric LiDAR can map shallow waters at very high resolution; however, the maximum depth and measurable intensity are strongly influenced by turbidity. Rapid losses to intensity and point density as depth increases hinder detection and classification schemes of underwater objects. Presented is a scheme for water column compensation using submersible retroreflector targets to sample the attenuation profile of the water column, yielding a remotely sensed estimate of turbidity. Incorporating these estimates into an instrument performance model, a depth-dependent gain function can be derived and applied to bathymetric surface measurements to normalize intensity across shallow depths for subsequent point cloud analysis. Radiative transfer model results show expected instrument and target response functions produce sufficient signal dynamic range for estimating turbidity in shallow waters for permissible levels of turbidity.