SCANDEM-Coast - open-source tool for UAV LiDAR point cloud classification in coastal environments

Remote sensing technologies, particularly Light Detection and Ranging (LiDAR) mounted on Unnamed Aerial Vehicle (UAV), are instrumental in monitoring the dynamics of coastal environments. However, the utility of raw UAV LiDAR point clouds is often constrained by their unstructured format, lack of classification, presence of noise, and multiple returns, necessitating robust filtering algorithms. The complexity of pre-processing demands specialized expertise, and automated classification methods remain largely confined to specific research domains, limiting broader scientific application. To address these limitations, we developed the SCANDEM-Coast (SCanning and ANalysis for DEM generation in Morphodynamic Coastal environments) toolkit: a simplified, open-access, automated workflow for end-to-end processing of LiDAR datasets. It comprises of Python scripts, the toolkit streamlines the pre-processing, classification, interpolation and conversion of UAV LiDAR datasets to Digital Elevation Models (DEM) using well-developed algorithms and scientific methodologies to assess accuracy of produced DEMs.