A demarcation model for identifying fish potential zones in the Gulf of Mannar using remote sensing data

The availability of Potential Fishing Zones (PFZ) where fish tend to aggregate in the sea during specific timeframes is limited. These zones are determined based on factors such as sea surface temperature and sea surface chlorophyll levels. This research introduces an additional dimension to the study by integrating spatial data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) Satellite, along with field observations. The aim is to identify PFZs and classify different fish types within those zones. To accomplish this research objective, temporal fish type data and extracted features from remote sensing data, including chlorophyll-a (Chl-a) and Sea Surface Temperature (SST), are combined using the AdaBoost classifier. The developed system not only maps the potential zones where fish are likely to be found but also determines the specific fish types based on field data collected. The study’s findings have been presented, highlighting the promising potential of the proposed model. This research contributes to the utilization of RS data and field observations for effective PFZ identification and fish type classification. The results demonstrate the potential of the proposed demarcation model for effectively identifying and mapping Fish Potential Zones in the Gulf of Mannar using remote sensing data.