Marine microplastic pollution has become a global environmental issue, posing a threat to marine ecosystems and potentially impacting human health through the food chain. Due to their small size, persistence, and widespread distribution in the ocean surface, traditional monitoring methods are inadequate for capturing the spatial distribution characteristics of microplastics effectively. In recent years, satellite remote sensing has demonstrated significant potential in monitoring marine microplastics, owing to its wide coverage, real-time observation capabilities, and cost-effectiveness. Microplastic monitoring based on satellite spectral data primarily distinguishes microplastics from other suspended materials by identifying the unique spectral characteristics of water bodies. Studies have shown that specific spectral bands can reflect the presence of microplastics, and indices such as band ratios can be used to quantitatively assess their abundance. However, current research still faces challenges such as limited accuracy and poor data assimilation, which hinders its application for large-scale, high-precision monitoring.

  This study aims to develop a satellite-based microplastic abundance retrieval algorithm tailored for the South China Sea. By analyzing the reflection characteristics of microplastics across different spectral bands and integrating satellite remote sensing data with existing ocean color models, the study seeks to enhance the accuracy of microplastic abundance retrieval for this region. The method is expected to have broad applications and contribute to advancing remote sensing technology in marine pollution monitoring and management.