Quantitative characteristics of the Indian Ocean seafloor relief using fractal dimension

Abstract

152-161In this paper spectral technique has been applied for seafloor topographic data analyses from three seafloor provinces of the Indian Ocean. Study sites include West of the Andaman Island (WAI), Western Continental Margins of India (WCMI) and Central Indian Ocean Basin (CIOB). The analyses involved application of suitable gridding techniques to bathymetric data of the multi-beam-Hydrosweep from these sites. Total eleven profiles i.e., three from two sites (A and B) and five from site C were used from varying physiographic provinces. Segmentation method is employed to non-stationary profile into homogenous or stationary segments. Thereafter, estimation of spectral parameters (β) is carried out for thirty-five segmented profiles and amplitude parameter (S) is computed. Also, computation of Fractal Dimension (D) using spectral exponent parameter was carried out and analyses is presented. Current investigation also includes presentation of scatter plot between the β and S value for each site. The computed Fractal Dimension (D) from sedimentary area of the trench side of WAI site revealed very high D values i.e., higher roughness, whereas varying fractal dimension values from remaining areas of this site are indicative of moderate to lower seafloor roughness. Similarly, results form WCMI (site B) area showed variable physiographic provinces from shelf (higher D) to slope morphology which appears to have modified by presence of physiographic highs and slump related features. Highest ‘D’ values for summit of the highs indicate sub-aerial erosion and lower ‘D’ values for flanks across the highs were also observed. Fractal Dimension (D) values from site C (CIOB) also indicated moderate ‘D’ values for E-W and N-S profiles. However, scatter plot between the β and S values for E-W and N-S profiles show interesting demarcation in terms of clustering. In this work, application of Fractal Dimension is demonstrated for quantitative characterization of the Indian Ocean seafloor roughness

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    Last time updated on 11/04/2020