Lead: Shane Daiek
Counselor: Jorge Lorenzo-Trueba

Shane Daiek, assisted by Viet Bui, is conducting drone surveys to quantify the role of vegetation cover on berm-dune geometry and sedimentation patterns in Long Branch, New Jersey. By developing a machine learning–based mapping tool that uses drone-based imagery, including standard color photos (RGB) and LiDAR (a laser-based method that maps surface elevation in detail), they are able to generate high-resolution, species-specific vegetation datasets. This data is critical for quantifying current conditions and for calibrating and validating a model that links barrier island change with habitat suitability metrics. Within MACH, the vegetation datasets are directly used by the Barrier Island and Habitat Modeling for Conservation Management project that is assessing habitat suitability for shorebirds, specifically piping plovers. Together, these efforts support the U.S. Fish and Wildlife Service and other stakeholders in making informed decisions about habitat conservation, land acquisition, and long-term coastal adaptation.

This project is led by a MACH research affiliate who does not receive direct financial support from NSF award ICER-2103754.