Search for fin whale calls and shipping noise in Western Ionian Sea using Distributed Acoustic Sensor

The IPANEMA project, funded under the ECCSEL-ERIC activity, aims at studying the natural emissions of carbon dioxide in the Mediterranean region via acoustic detection. In the framework of IPANEMA INFN-LNS has designed two underwater stations equipped with hydrophones and CO2 sensors: a shallow water (20 m depth) autonomous and retrievable observatory, deployed offshore the Island of Panarea (Aeolian Islands, Tyrrhenian Sea) and a cabled deep sea observatory, to be deployed in offshore the Coast of Catania at 2000 m depth (Sicily, Western Ionian Sea). Both detectors are capable to monitor the sea soundscape from a few Hz to just under 100 kHz.

In this context, INFN is investigating the possibility to use Distributed Optical Fiber sensing (DOFS) to enable the measurement of biological and anthropogenic acoustic signals along the entire length of underwater electro-optical cables. Unlike conventional sensors that measure at specific points, DOFS systems provide distributed measurements along the fiber length with high spatial sampling, allowing for dense monitoring of large structures or environments in real time. In this work, we will focus on the application of DOFS in the monitoring of biological sounds emitted by fin whales, as demonstrated by recent researches in Isfjorden Sea, Norway.

During a campaign of measurements between November 9th and 16th, 2023, IFREMER interrogated with an ASN OptoDAS two seafloor electro-optical cables of the INFN-LNS marine infrastructure in Eastern Sicily. The Distributed Acoustic Sensor (DAS) system was first connected to the LNS-INFN electro-optical cable, extending 25 km from the port of Catania to its end at approximately 2100 m water depth. Another set of measurements was carried out at the LNS-INFN Capo Passero site, using a cable extending 100 km to the shore, reaching depths of around 3500 m. In this area a research study conducted by INFN-LNS between 2012 and 2013, using hydrophones on seafloor showed the presence of fin whales.

In this work we will present the analysis of DAS signals: custom codes for data reduction, noise filtering and search for the typical fin whale calls (20 Hz intermittent pulses) will be presented and results discussed.