<![CDATA[Skipjack tuna (Katsuwonus pelamis) represents one of the most economically important pelagic fish in the eastern Indian Ocean, particularly in the southern waters of East Java. This study integrates fishers’ local ecological knowledge (LEK) with satellite-derived oceanographic data to model potential fishing zones. The objective is to improve spatial prediction of fishing grounds by combining experiential knowledge with environmental indicators. The study used a mixed-method approach involving structured interviews with fishers and analysis of sea surface temperature and chlorophyll-a derived from satellite imagery. Spatial modeling was conducted using a habitat suitability approach supported by GIS analysis. Results indicate that optimal fishing zones were consistently associated with sea surface temperatures between 26–29°C and moderate chlorophyll-a concentration. Fishers’ LEK strongly aligned with satellite-based predictions, confirming the reliability of traditional knowledge in identifying productive fishing areas. The integration of both data sources significantly improved spatial accuracy of fishing zone mapping. This study concludes that combining LEK and remote sensing enhances fisheries resource prediction and supports sustainable fishing strategies in tropical marine ecosystems.]]>
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