Ships detection has positioned itself as one of the most important tasks for maritime surveillance and security applications, due to the worldwide increase in maritime traffic, environmental monitoring and illegal fishing, radar technology is one of the most effective tools to detect ships, determine maritime routes and analyze variations in maritime traffic.

Thus, a team of Spanish and Chilean researchers, led by Dr. Cristina Rodríguez-Benito, published a study in the journal Remote Sensing, using radar data from the Sentinel-1 satellite of the European Copernicus program, automatic ship detection algorithms and the global information platform Google Earth Engine, determined the maritime routes and the variation in the number of ships in three essential areas for Patagonia: the Chacao Channel, Caleta Puelche and the Magellan Strait, during the period of confinement from April-May 2020.

“The three maritime routes showed an almost total interruption of shipping and ships remained anchored in the coast of these channels. In contrast, for the same period of previous years as in 2019 and 2018, the presence of ships was counted in the three mentioned sea routes. The application is extrapolable to other purposes and places of interest for governmental and private decision-making,” explained Dr. Rodríguez-Benito.

Radar satellite technology can be used not only for maritime traffic monitoring but also, as researchers have demonstrated in other studies, for environmental monitoring in aquaculture operations, salvage after maritime accidents, oil spills and the study of ocean circulation patterns.

“This technology has a great potential in Patagonia, mainly because of its high resolution and capacity to obtain data in conditions of high cloud cover,” says the researcher.

For more information, access the study by Rodríguez-Benito C., Caballero I., Nieto K., Navarro G., “Observation of Maritime Traffic Interruption in Patagonia during the Covid-19 Lockdown Using Copernicus Sentinel-1 Data and Google Earth Engine. Remote Sensing. 2021; 13(6):1119″

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