2008University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)Requires access

Detecting bedform migration in Portsmouth Harbor on relatively short time-scales from high-resolution multibeam bathymetry

Janice Felzenberg, Larry G. Ward, Yuri Rzhanov, Larry A. Mayer

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Abstract

Bedforms are common features in shallow marine environments, and their presence evokes questions regarding the spatial and temporal stability of the seafloor. Though observation of bedform dynamics from multibeam bathymetry and its derived products enhances understanding of seafloor stability, the ability to successfully detect bedform migration depends on (1) the survey resolution and positioning uncertainty, and (2) the establishment of an optimum survey-repetition rate.

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What this paper is about

Bedforms are common features in shallow marine environments, and their presence evokes questions regarding the spatial and temporal stability of the seafloor. Though observation of bedform dynamics from multibeam bathymetry and its derived products enhances understanding of seafloor stability, the ability to successfully detect bedform migration depends on (1) the survey resolution and positioning uncertainty, and (2) the establishment of an optimum survey-repetition rate.

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Available abstract

Bedforms are common features in shallow marine environments, and their presence evokes questions regarding the spatial and temporal stability of the seafloor. Though observation of bedform dynamics from multibeam bathymetry and its derived products enhances understanding of seafloor stability, the ability to successfully detect bedform migration depends on (1) the survey resolution and positioning uncertainty, and (2) the establishment of an optimum survey-repetition rate.

Key concepts: Bathymetry, Bedform, Seafloor spreading, Geology, Oceanography, Remote sensing, High resolution, Geomorphology

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Detecting bedform migration in Portsmouth Harbor on relatively short time-scales from high-resolution multibeam bathymetry — Research Paper | ScholarLens