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Highly accuracy classification and mapping of seafloor hydrothermal fields provides an important addition to research into the geological background and exploration of seafloor massive sulfides (SMS). Currently, acoustic remote sensing using multibeam sounding systems (MBES) is the primary means of achieving large-scale seafloor classification. However, the characteristics of complex topography, complex seafloor distribution, and deep water depth of the hydrothermal fields make it difficult to obtain accurate high-resolution seafloor classification maps using shipboard MBES surveys. Here, a seafloor classification strategy combining shipboard MBES and autonomous underwater vehicle (AUV) sidescan sonar data is proposed. First, a downscaling model is established, which downscales the MBES backscatter mosaic (12-kHz and 10-m resolution) to a resolution of 2 m. The second step performs feature extraction of the downscaled MBES backscatter mosaic (12-kHz and 2-m resolution), the AUV sidescan sonar backscatter mosaic (150-kHz and 2-m resolution), and a seafloor digital elevation model (2-m resolution). Finally, a deep neural network model was built for training and classification. To evaluate the classification performance of the model, the method was applied to the survey of the Duanqiao hydrothermal field. Results were verified using field data (deep-tow video). The overall root mean square error and coefficient of determination ($R^{2}$) for the classification were 0.032 and 0.840, respectively. The experimental results show that the method can effectively meet the challenges to seafloor classification presented by complex seafloor distribution, and can obtain an accurate high-resolution seafloor classification map. [ABSTRACT FROM AUTHOR]

An extremely magmatic accretion could exist along an ultraslow-spreading ridge that has been approved and surveyed, but less attention has been paid to its associated hydrothermal system, as it is supposed to be similar to those of fast/medium-spreading ridges. Here using an autonomous underwater vehicle and a human-occupied vehicle, a systematic investigation was conducted on the hydrothermal system of an extremely magmatic accretion segment along the Southwest Indian Ridge (50°28′ E). A collapsed chimney, microbial mat, and diffused fluid were observed in the old Duanqiao hydrothermal field (DQF), which was earlier a weakly active hydrothermal area. Notably, evident hydrothermal anomalies, including oxidation–reduction potential (ORP), turbidity, and methane, were detected above the new DQF, which lies southwest of the old DQF. Based on this investigation, we concluded that ORP is one of the most effective parameters available to identify vent location by analyzing each type of detected hydrothermal anomaly and the near-bottom magnetic inversion can image the suspected hydrothermal fluid circulation pathways. In general, we believe that the new DQF is controlled by a magmatic chamber different from those found on fast/medium-spreading ridges, and could be a large hydrothermal system. • Obvious hydrothermal anomalies observed were earlier described as inactive by AUV. • Indicators of hydrothermal activities have their own recognition features. • Duanqiao is a large magmatic-hosted hydrothermal system compared with Lucky Strike. [ABSTRACT FROM AUTHOR]