Repeat AUV MBES Surveys for Deepwater Seafloor Change Detection

摘要

Repeated multibeam echosounder (MBES) surveys conducted using autonomous underwater vehicles (AUVs) have the potential to document the magnitude and areal extent of seafloor changes associated with both human and natural causes, including seafloor subsidence, fault or slope movements, fluid expulsion, volcanism, and biological activity. If AUV survey design does not consider the practical limits to change detection and include best practices to minimize noise, however, the results may be ambiguous or even useless. Using a series of simulations combining real bathymetric digital elevation models (DEMs) with idealized perturbations representing seafloor subsidence and faulting, this paper examines limits to seafloor change detection using repeat MBES surveys in terms of the standard deviation of the noise in the surveys. In general, the magnitude of vertical change between surveys should be greater than the standard deviation of the noise (also known as uncertainty or error) in each of the surveys compared in order reliably recognize seafloor change. Filtering can suppress noise and recover the real seafloor change, possibly even if the magnitude of the change is less than the standard deviation of the noise. Based upon the simulations in this paper, fdtering is more effective for broad features like subsidence bowls than localized features like faults even if the amount of vertical change is identical. A probabilistic threshold based upon the standard deviation of the noise appears to be less useful than filtering in the simulations undertaken for this paper.