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.

Swath sonar bathymetry during POLARSTERN cruise ANT-XIX/5 (PS61) with links to multibeam raw data files

Multibeam data were measured during R/V Polarstern cruise ANT-XIX/5 along track lines of approximately 4000 NM total length in the Scotia Sea. Data were achieved along the Scotia Arc from Burdwood Bank to King George Island. A multibeam box survey was conducted at the southern part of the Discovery Rise, located at 50°55'S / 35°30'W and covering an area of 90 x 15 NM. A bathymetric survey of 25 x 60 NM was carried out at the eastern part of the South Shetland Trench and its intersection with the Shackleton Fracture Zone, continuing multibeam data from former expeditions. The multibeam sonar system Hydrosweep DS-2 was operated using 59 beams and 90° aperture angle. The refraction correction was achieved utilizing the system's own cross fan calibration. The quality of data might be reduced during bad weather periods or adverse sea ice conditions. The dataset contains raw data that are not processed and thus may contain errors and blunders in depth and position.