Estimating trawler fishing effort plays a critical role in characterizing marine fisheries activities, quantifying the ecological impact of trawling, and refining regulatory frameworks and policies. Understanding trawler fishing inputs offers crucial scientific data to support the sustainable management of offshore fishery resources in China. An XGBoost algorithm was introduced and optimized through Harris Hawks Optimization (HHO), to develop a model for identifying trawler fishing behaviour. The model demonstrated exceptional performance, achieving accuracy, sensitivity, specificity, and the Matthews correlation coefficient of 0.971 3, 0.980 6, 0.963 2, and 0.942 5, respectively. Using this model to detect fishing activities, the fishing effort of trawlers from Shandong Province in the sea area between 119°E to 124°E and 32°N to 40°N in 2021 was quantified. A heatmap depicting fishing effort, generated with a spatial resolution of 1 / 8°, revealed that fishing activities were predominantly concentrated in two regions: 121.1°E to 124°E, 35.7°N to 38.7°N, and 119.8°E to 122.8°E, 33.6°N to 35.4°N. This research can provide a foundation for quantitative evaluations of fishery resources, which can offer vital data to promote the sustainable development of marine capture fisheries.