Fishing forecasting system in Adriatic sea — A model approach based on a normalized scalar product of the SST gradient and CHL gradient vectors

摘要

By mapping the concentration of chlorophyll-a (CHL) and the temperature of the sea surface (SST), satellite images reveal the complex dynamics of marine waters and prove to be a very powerful tool when used to detect potential fishing areas, significantly reducing the time of the search, the fuel consumption and the human effort, and simultaneously increasing the CPUE (catch per unit effort). In the present work, various techniques of multi-sensor, multi-resolution and multi-temporal data fusion are applied to multi-spectral satellite image data of MODIS-AQUA, MODIS-TERRA and VIIRS sensors, in order to detect "fronts" of chlorophyll concentration and temperature on the sea surface. According to the physical model of the phenomena, these fronts are generated by the upwelling of cold waters rich of nutrients (phytoplankton) which correspond to areas with a high concentration of pelagic fish and are characterized by high values of local gradients of SST and CHL with anti-parallel orientation. An automatic procedure has been developed to calibrate and validate the production in near-real time of daily maps of expected good fishing grounds to be provided to the FEDERPESCA fleet. The same procedure could be optimized also for other seas.