Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions
Ariell Friedman · Oscar R. Pizarro · Stefan B. Williams · Matthew Johnson-Roberson
TL;DR
Seafloor rugosity, slope and aspect can be computed at many scales from stereo image 3D reconstructions, replacing slower, more invasive in-situ measurements.
BRIEF
Marine scientists measure seafloor roughness (rugosity), slope and aspect to understand habitat, but traditional methods rely on divers laying chains over the bottom. This work computes those measures from 3D reconstructions built from stereo images collected by AUVs, ROVs, submersibles and diver-held rigs. Rugosity is calculated on a triangulated mesh by projecting areas onto a best-fit plane, which separates it from slope. Results are validated against in-situ measurements, and the method works at multiple scales across surveys of thousands of square metres.
Abstract
This paper demonstrates how multi-scale measures of rugosity, slope and aspect can be derived from fine-scale bathymetric reconstructions created from geo-referenced stereo imagery. We generate three-dimensional reconstructions over large spatial scales using data collected by Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), manned submersibles and diver-held imaging systems. We propose a new method for calculating rugosity in a Delaunay triangulated surface mesh by projecting areas onto the plane of best fit using Principal Component Analysis (PCA). Slope and aspect can be calculated with very little extra effort, and fitting a plane serves to decouple rugosity from slope. We compare the results of the virtual terrain complexity calculations with experimental results using conventional in-situ measurement methods. We show that performing calculations over a digital terrain reconstruction is more flexible, robust and easily repeatable. In addition, the method is non-contact and provides much less environmental impact compared to traditional survey techniques. For diver-based surveys, the time underwater needed to collect rugosity data is significantly reduced and, being a technique based on images, it is possible to use robotic platforms that can operate beyond diver depths. Measurements can be calculated exhaustively at multiple scales for surveys with tens of thousands of images covering thousands of square metres. The technique is demonstrated on data gathered by a diver-rig and an AUV, on small single-transect surveys and on a larger, dense survey that covers over [Formula: see text]. Stereo images provide 3D structure as well as visual appearance, which could potentially feed into automated classification techniques. Our multi-scale rugosity, slope and aspect measures have already been adopted in a number of marine science studies. This paper presents a detailed description of the method and thoroughly validates it against traditional in-situ measurements.