To address the issue that traditional methods for inverting chlorophyll-a concentration in water bodies are not suitable for nearshore aquaculture areas with complex optical properties,we summarize several widely-used inversion methods of chlorophyll-a concentration based on their principles and data sources.These approaches include empirical statistical regression methods,semi-empirical and semi-theoretical water physical radiative transfer model methods,and machine learning methods.Furthermore,we discuss the advantages and disadvantages of these approaches,along with the current difficulties and challenges in chlorophyll-a inversion research.We also explore future trends to provide references for more accurate inversion of chlorophyll-a concentration in water bodies,supporting nearshore water quality monitoring and aquaculture management.
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