Annual mean biomass of Ulva prolifera in the Yellow Sea from 2007 to 2024 (V 1.0)

Recurrent blooms of Ulva prolifera (the dominant algal species responsible for green tides) in the Yellow Sea have become one of the most significant marine ecological hazards worldwide, posing persistent threats to coastal ecosystems, aquaculture, tourism, and regional economies. Since 2007, large-scale green tide events have occurred almost annually. Satellite remote sensing provides a feasible means for large-scale and long-term monitoring of Ulva prolifera. MODIS imagery, with its high temporal resolution and long observational continuity, has been widely used for this purpose. However, traditional index-based approaches (e.g., Floating Algae Index, FAI) rely on manually selected thresholds and are highly sensitive to observation conditions, limiting their robustness and scalability for long-term applications. To address these limitations, this dataset was generated using GTD-Net (Green Tide Detection Network), a knowledge-guided deep learning model specifically designed for Ulva prolifera detection under complex marine environments. GTD-Net integrates a heterogeneous, multi-dimensional training dataset with architectural enhancements to improve cross-scenario generalization. Based on GTD-Net extraction results, Ulva prolifera biomass was estimated using a physically based BPA-FAI relationship that accounts for both horizontal and vertical spectral mixing effects. This dataset provides a long-term record of annual mean biomass per unit area (BPA, kt km⁻²) of Ulva prolifera in the Yellow Sea from 2007 to 2024. It is intended to support studies on green tide dynamics, environmental drivers, climate variability, and ecosystem risk assessment.