22 Jan 2024

Amphibious Uncrewed Ground Vehicle for Coastal Surfzone Survey

Abstract: The capability of a commercial off-the-shelf amphibious bottom crawling robot is explored for surveying seamless topography and bathymetry across the beachface, surfzone, and very nearshore. A real-time-kinematic (RTK) antenna on a mast was added to the robotic platform, a Bayonet-350 (previously the C2i SeaOx). Data collected from the robot were compared with those collected by the Coastal Research Amphibious Buggy (CRAB) and the Lighter Amphibious Resupply Cargo (LARC), unique amphibious vessels capable of collecting seamless topography and bathymetry in use for decades at the US Army Engineer Research and Development Center’s Field Research Facility (FRF). Data were compared on five different days in a range of wave conditions (Hs < 1 m in 8-m depth) resulting in a root-mean square difference of 8.7 cm and bias of 2 cm for 24 different cross-shore profile comparisons. Additionally, a repeatability test was performed to assess measurement uncertainty. The repeatability test indicated a total vertical uncertainty (TVU) of 5.8 cm, with the highest spatial error at the shoreline.

8 Sep 2023

Applicability of CoastSnap, a Crowd-Sourced Coastal Monitoring Approach for US Army Corps of Engineers District Use

Abstract: This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details the pilot deployment, accuracy evaluation, and best practices of the citizen-science, coastal-image monitoring program CoastSnap. Despite the need for regular observational data, many coastlines are monitored infrequently due to cost and personnel, and this cell phone-image-based approach represents a new potential data source to districts in addition to providing an outreach opportunity for the public. Requiring minimal hardware and signage, the system is simple to install but requires user-image processing. Analysis shows the CoastSnap-derived shorelines compare well to real-time kinematic and lidar-derived shorelines during low-to-moderate wave conditions (root mean square errors [RMSEs] <10 m). During high-wave conditions, errors are higher (RMSE up to 18 m) but are improved when incorporating wave run-up. Beyond shoreline quantification, images provide other qualitative information such as storm-impact characteristics and timing of the formation of beach scarps. Ultimately, the citizen-science tool is a viable low-cost option to districts for monitoring shorelines and tracking the evolution of coastal projects such as beach nourishments.