An Automated Workflow for Detecting Coastal Cliff Change in Large Datasets
Date:
Session: EP23D-03
Authors: Connor J. Mack, Matthew Maclay, Raphael Krier-Mariani, Adam Young
Developed an automated method combining machine learning classification, M3C2 change detection, DBSCAN clustering, noise filters, and alpha shape algorithms to extract detailed coastal change measurements from large topographic datasets, enabling processing at expanded temporal and spatial scales.