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Automatic Fast-Forecasting of Fishing Grounds Using Sea Surface Temperature and Chlorophyll-a Data

Yus Sholva, Benhard Sitohang, Ketut Wikantika

Abstract



The fishing grounds can be forecasted by observing the upwelling phenomenon indicated by existing of the thermal front and high concentration of chlorophyll-a in the waters area. We used pixel detection approach to detect thermal front and chlorophyll-a using the data derived from Aqua MODIS satellite. The data of sea surface temperature is processed by window masking then followed by the region growing process to evaluate the neighbor's pixels, if its meet some criteria then its will be set as thermal front pixels. The data of chlorophyll-a is processed by determining the pixels with the highest concentration values and using gradient magnitude approach to distinguish any pixels that near to the mainland or cloud. The location of fishing grounds is determined using Euclidean distance calculations from each pixel of thermal front to each pixel of chlorophyll-a, a paired pixel that has shortest Euclidean distance is defined as pixels of fishing grounds.

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