The overall objective of this project is to investigate methods to assess the capability of a revolutionary LiDAR technology to detect and characterize munitions found at underwater sites in waters of less than five meters depth. This project will investigate into the quality of LiDAR point clouds in terms of having sufficient resolution to discern proud, partially buried, and fouled unexploded ordnance from the surrounding environment. The degradation of the LiDAR point cloud should also be quantifiable/predictable based on turbidity, depth, wave action and any other factors that could degrade resolution. Post processing and point cloud manipulation requirements should be considered. The specific research questions and technical approach for this project include: 

  • Research Question 1: To what spatial accuracy and resolution can the unmanned aerial system (UAS)-based LiDAR technology describe submerged objects and bathymetric features under different water conditions?
  • Research Question 2: How well can the UAS-based LiDAR technology discern/classify target of interest (TOI) from the surrounding environment using target morphometry, positioning, and scatterometry?

Technical Approach

The suggested research approach is to develop uncertainty quantification and machine learning methods that can assess – Light Detection and Ranging (LiDAR)-generated three-dimensional (3D) point clouds and advance the LiDAR’s utility to accurately determine the morphometry, position, and scattering characteristics of TOIs in shallow waters. Through modelling, data analysis, and measurement, the activity will ascertain the accuracy, uncertainty, and resolution of LiDAR-generated 3D point clouds from a UAS platform to discern submerged objects and improve their feature classification.


Results from this work will provide expanded capability to cost-effectively characterize munitions response sites in the shallow underwater environment and to deploy above-water LiDAR technologies for a wide array of site conditions. This research is of great interest to the Department of Defense and scientific communities due to its ability to observe at high spatial resolution (centimeter precision) a variety of shallow-water aquatic environments that have been, up to now, inaccessible due to limited technologies. The results of the activity will provide detailed characterization of the University of Hawaii's Environmental Security Technology Certification Program (ESTCP) test site and provide the necessary tools to enable advanced use of the LiDAR at other ESTCP field sites such as Culebra, Sequim Bay, Vieques, Cape Poge, and other formerly used defense sites.