Stochastic Modelling of Seafloor Morphology

Abstract

At scale lengths less than 100 km or so, statistical descriptions of seafloor morphology can be usefully employed to characterize processes which form and reshape abyssal hills, including ridge crest volcanism, off-axis tectonics and volcanism, mass wasting, sedimentation, and post-depositional transport. The objectives of this thesis are threefold: (1) to identify stochastic parameterizations of small-scale topography that are geologically useful, (2) to implement procedures for estimating these parameters from multibeam and side-scan sonar surveys that take into account the finite precision, resolution, and sampling of real data sets, and (3) to apply these techniques to the study of marine geological problems. The seafloor is initially modeled as a stationary, zero-mean, Gaussian random field completely specified by its two-point covariance function. An anisotropic two-point covariance function is introduced that has five free parameters describing the amplitude, orientation, characteristic width and length, and Hausdorff (fractal) dimension of seafloor topography. The general forward problem is then formulated relating this model to the statistics of an ideal multibeam echo sounder, in particular the along-track autocovariance functions of individual beams and the cross- covariance functions between beams of arbitrary separation.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1990
Accession Number
ADA237063

Entities

People

  • John A. Goff

Organizations

  • Woods Hole Oceanographic Institution

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Data Mining
  • Data Science
  • Information Processing
  • Information Science
  • Oceanography
  • Probabilistic Models
  • Ridges
  • Seabed
  • Side Looking Sonar
  • Sonar
  • Statistical Algorithms
  • Statistical Analysis
  • Stochastic Processes
  • Surveys
  • Terrain
  • Topography
  • Two Dimensional

Readers

  • Acoustical Oceanography.
  • Coastal Oceanography
  • Statistical inference.