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Manganese crusts (Mn-crusts) are a type of mineral deposit that exists on the surface of seamounts and guyots at depths of >800 m. We have developed a method to efficiently map their distribution using data collected by autonomous underwater vehicles and remotely operated vehicles. Volumetric measurements of Mn-crusts are made using a high-frequency subsurface sonar and a 3-D visual mapping instrument mounted on these vehicles. We developed an algorithm to estimate Mn-crust distribution by combining continuous subsurface thickness measurements with the exposed surface area identified in 3-D maps. This is applied to data collected from three expeditions at Takuyo Daigo seamount at depths of ∼1400 m. The transects add to ∼11 km in length with 12 510 m 2 mapped. The results show that 52% of the surveyed area is covered by Mn-crusts with a mean thickness of 69.6 mm. The mean Mn-crust occurrence is 69.6 kg/m 2 with a maximum of 204 kg/m 2 in the mapped region. The results are consistent with estimates made from samples retrieved from the area, showing more detailed distribution patterns and having significantly lower uncertainty bounds for regional-scale Mn-crust inventory estimation.

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There are several approaches for 3 dimensional mapping of the seafloor in the actual colours, many of which require multiple cameras, elaborate algorithms and specially designed vehicles. In this paper a method is presented, which uses minimal equipment and simple algorithms for this task, while treating the data in a fully 3 dimensional way from input to output. Because of the reduced hardware demands, it is well suited for combined missions, where the underwater vehicle records some other data as primary task and the map created with the proposed method acts as a support for visualising that data and the environment where it was collected. I. INTRODUCTIONPhotographing and filming of the seafloor has been performed already for many years, with attempts of using a TV camera for survey dating back to 1964 [1]. As visibility is limited underwater, an image can cover only a few square metres, and so the idea of merging several photos into a mosaic emerged as a practical solution for wide area seafloor imaging. These days reconstruction of the seafloor has been taken to a new level thanks to the use of computers and digital photography. For 2D reconstruction, photos are arranged next to each others, corrected for difference in lighting and the transitions are smoothed [2], [3]. By overlaying such a mosaic on the topography of the seafloor, a 3D model can be generated. If the seafloor topography doesn't have any sudden changes in height, this method yields good results. However, pronounced vertical reliefs lead to geometrical distortions due to the perspective effect, producing artefacts in the mosaic and an inherently incorrect 3D reconstruction.Places of interest underwater often include areas with pronounced reliefs, such as areas where mineral resources are found, hydrothermal vents, manmade underwater installations, shipwrecks, coral reefs or archaeological sites. In these cases a method that handles the images in a fully three dimensional way from input to output is required to produce better results. High resolution 3D reconstruction using stereo photography has been shown by Pizarro, Williams and Mahon [4]. Much effort went into the implementation of the algorithm and an AUV that is perfectly suited for recording the images has been developed.While the above mentioned methods are used for mapping of the seafloor as a main task, we argue that generating a 3D map of the region where a vehicle was deployed while carrying