POSIT: An automated tool for detecting and characterizing diverse morphological features in raster data - Application to pockmarks, mounds, and craters

Abstract

Accurate detection and characterization of seafloor morphologies are crucial for marine researchers and industries involved in underwater mapping, environmental monitoring, or resource exploration. Although their detection has relied on visual inspection of detailed bathymetries, few efforts to automate the process can be found in the literature. This study presents a novel MatLab computer code called POSIT (Feature Signature Detection) based on the convolution and correlation with a structural element containing the shape to search for. POSIT is successfully tested on both synthetic and real datasets, encompassing marine and terrestrial digital elevation models of different resolution and on a digital image. The centroids of submarine pockmarks and mounds, terrestrial volcanic craters and lunar craters are calculated with zero dispersion and perfect location, and their geometric parameters and confidence are provided.