Assessing the distribution and abundance of seabed minerals from seafloor photographic data in the Central Indian Ocean Basin

• Published in: International journal of remote sensing Vol. 34; no. 5; pp. 1691 - 1706
• Main Authors: Sharma, Rahul, Khadge, N.H, Jai Sankar, S
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01-01-2013
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; correlation; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Metal geology; Metallic and non-metallic deposits; mineral resources; minerals; physical properties; sediments; Teledetection and vegetation maps; Indian Ocean; mineral resources; thickness; Estimation; sampling; nodules; topography; Empirical relation; surface features; distribution; undulation; sounding; ocean basins; Characteristics; ocean floors; bathymetry; deep-water environment; sediments; Ferromanganese
• ISSN: 1366-5901; 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2012.725485

Distribution characteristics of deep-sea mineral resources such as polymetallic nodules and ferromanganese crusts are often influenced by local seafloor features such as the topographic undulations and sediment thickness. Qualitative as well as semi-quantitative estimation of these resources have been attempted earlier by using seafloor photographic data. This study analyses the distribution of these minerals in relation to their associated seafloor surface features and develops empirical formulae for abundance estimation of a deposit from photographic data in conjunction with sounding and sampling data in the Central Indian Ocean Basin. Data from >20,000 photos were analysed and correlated with geological features such as bathymetry, sediment thickness, and sediment physical properties. The study shows that nodule populations are negatively correlated with the thickness of the acoustically transparent layer (ATL), which in turn is controlled by the topographic undulations. The variable burial of nodules under the ATL, as indicated by sampling data, leads to underestimation of nodules from photographs. In order to improve the accuracy of such estimations, different constant factors (C-factor) are proposed for use in empirical formulae depending upon the distribution characteristics of the deposits.