Using Semantic Trajectories for Spatio-temporal Characterisation of Underwater Noise

Underwater noise pollution from human activities, particularly shipping, has been recognised as a serious threat to marine life. The sound generated by vessels can have various adverse effects on fish and aquatic ecosystems in general. In this setting, the estimation and analysis of the underwater noise produced by vessels is an important challenge for the preservation of the marine environment. In this paper, we propose a model for the spatio-temporal characterisation of the underwater noise generated by the fishing vessels in the Northern Adriatic Sea. The approach is based on the reconstruction of the vessels’ trajectories from AIS data. Trajectories are enriched with semantic information like the acoustic characteristics of the vessels’ engines or the activity performed by the vessels. This is then used to infer how noise propagates in the area of interest. The conceptual framework has been implemented using MobilityDB, an open source geospatial trajectory data management and analysis platform. We present some preliminary analyses obtained by applying the developed tool.