Geology, geochemistry, and mineralogy of sediments from the Trans Indian Ocean Geotraverse

The monograph is devoted to the main results of research on the Trans Indian Ocean Geotraverse from the Maskarene Basin to the north-western margin of Australia. These results were obtained by Russian specialists and together with Indian specialists during 15 years of cooperation in investigation of geological structure and mineral resources of the Indian Ocean. The monograph includes materials on information support of marine geological and geophysical studies, composition and structure of information resources on the Indian Ocean, bathymetry and geomorphology, structure and geological nature of the magnetic field, gravity field, plate tectonics, crustal structure and sedimentary cover, seismic stratigraphy, perspectives for detecting oil and gas, solid minerals, sediment composition, composition and properties of clay minerals, stratigraphy and sediment age, chemical composition of sediments, composition of and prospects for solid minerals.

Composition of Cape Leeuwin Manganese nodule deposit off Western Australia

In 1970 a large deposit of ferromanganese nodules was discovered on the floor of the Indian Ocean southwest of Cape Leeuwin by the research vessel USNS Eltanin. This discovery, which was based largely on bottom photographs from about 20 stations, was discussed by Frakes (1975) and Kennett and Watkins (1975, 1976). The photographs suggest that the deposit spreads, nearly continuously, over 900 000km^2, and cores showed that the nodules are essentially confined to the sediment surface. Kennett and Watkins (op. cit.) pointed to the abundance of ripple and scour marks and current-formed lineations on the present surface, and of extensive disconformities in the cores, as evidence of strong present and past bottom currents in the region. They suggested that the current action had resulted in very low sedimentation rates, which had allowed the nodule field, named by them (1976) the 'Southeast Indian Ocean Manganese Pavement', to develop. In early 1976 the authors used the research vessel HMAS Diamantina for a 10-day cruise in the region to sample the nodules in order to study their chemistry and mineralogy. During the cruise 9 stations were occupied, 8 of them successfully (Figure 1), and about 2000 nodules were recovered from the sea bed. The apparatus used was a light box dredge on the ships hydrowire, which had a breaking strain of about one tonne. Although an attempt was made to reoccupy Eltanin photographic stations, it should be noted that positioning was by celestial navigation, so errors of up to 10 km are possible.

Bathymetric map of Heron Reef, Australia, derived from airborne hyperspectral data at 1 m resolution

A simple method for efficient inversion of arbitrary radiative transfer models for image analysis is presented. The method operates by representing the shape of the function that maps model parameters to spectral reflectance by an adaptive look-up tree (ALUT) that evenly distributes the discretization error of tabulated reflectances in spectral space. A post-processing step organizes the data into a binary space partitioning tree that facilitates an efficient inversion search algorithm. In an example shallow water remote sensing application, the method performs faster than an implementation of previously published methodology and has the same accuracy in bathymetric retrievals. The method has no user configuration parameters requiring expert knowledge and minimizes the number of forward model runs required, making it highly suitable for routine operational implementation of image analysis methods. For the research community, straightforward and robust inversion allows research to focus on improving the radiative transfer models themselves without the added complication of devising an inversion strategy.

Composite of coastal seagrass meadows in Queensland, Australia - November 1984 to June 2010

Approximately 18,400 km**2 of seagrass habitat has been mapped within the coastal waters (<15 m) of Queensland (Australia) between November 1984 and June 2010. The total seagrass meadow distribution was calculated by merging maps from 115 separate mapping surveys (varying locations and dates). Due to tropical seagrass dynamism, meadow distribution can change seasonally and between years, and as a consequence, the composite represents the maximum area of seabed where seagrass has been observed/recorded. Mapping survey methodologies followed standardised global seagrass research methods (McKenzie et al. 2001) where the presence of seagrass was determined from in situ visual assessment of the seabed by either divers or drop cameras at GPS marked positions. Seagrass meadow boundaries were determined based on the positions of survey sites and the presence of seagrass, coupled with depth contours and remote sensing (e.g. aerial photography) where available. The merged meadow boundary accuracy was dependent on the original survey maps and varied from 10-100 m. The resulting composite seagrass distribution was saved as an ArcMap polygon shapefile, and projected to Geocentric Datum of Australia GDA94.

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.

Benthic and substrate cover data derived from a time series of photo-transect surveys for the Eastern Banks, Moreton Bay Australia, 2004-2015

This paper describes seagrass species and percentage cover point-based field data sets derived from georeferenced photo transects. Annually or biannually over a ten year period (2004-2015) data sets were collected using 30-50 transects, 500-800 m in length distributed across a 142 km**2 shallow, clear water seagrass habitat, the Eastern Banks, Moreton Bay, Australia. Each of the eight data sets include seagrass property information derived from approximately 3000 georeferenced, downward looking photographs captured at 2-4 m intervals along the transects. Photographs were manually interpreted to estimate seagrass species composition and percentage cover (Coral Point Count excel; CPCe). Understanding seagrass biology, ecology and dynamics for scientific and management purposes requires point-based data on species composition and cover. This data set, and the methods used to derive it are a globally unique example for seagrass ecological applications. It provides the basis for multiple further studies at this site, regional to global comparative studies, and, for the design of similar monitoring programs elsewhere.