Automatic Statistical Processing of Multibeam Echosounder Data

Citation data:

International Hydrographic Review, Vol: 4

Publication Year:
2003
Usage 259
Downloads 250
Abstract Views 9
Repository URL:
https://scholars.unh.edu/ccom/980
Author(s):
Calder, Brian R.
Publisher(s):
International Hydrographic Organization
Tags:
Oceanography and Atmospheric Sciences and Meteorology
article description
This paper presents the CUBE (Combined Uncertainty and Bathymetry Estimator) algorithm. Our aim is to take advantage of statistical redundancy in dense Multibeam Echosounder data to identify outliers while tracking the uncertainty associated with the estimates that we make of the true depth in the survey area. We recognise that a completely automatic system is improbable, but propose that significant benefits can still be had if we can automatically process good quality data, and highlight areas that probably need further attention. We outline CUBE and its associated support structures, and apply it to a dataset from Woods Hole, MA, USA. We illustrate CUBE'S output surfaces, show that the algorithm faithfully maintains significant bathymetric detail, and how the algorithm's auxiliary outputs can be used in the decision-making process. Comparison with a selected sounding set shows that CUBE’S outputs agree very well with traditional approaches.