绿潮生物量是精准量化海洋大型漂浮藻类的关键参数,是反映海洋生态环境变化的有效指标。卫星遥感技术是中国近海绿潮监测的有效技术支撑,光学遥感卫星能为绿潮的精细化定量监测与评估提供数据支持,能实现绿潮的精准识别与量化估算。针对中国海洋一号C/D卫星 (Haiyang-1C/D,HY-1C/D) 海岸带成像仪 (Coastal Zone Imager,CZI) 、美国中分辨率成像光谱仪 (Moderate-resolution Imaging Spectroradiometer,MODIS)、欧洲空间局哨兵2号卫星多光谱成像仪 (Multi Spectral Instrument,MSI)等光学遥感数据特点,基于绿潮生物量变化模拟与观测验证数据,本研究提出了适用于不同光学卫星数据的绿潮生物量估算模型与计算方法,实现了中国近海绿潮生物量光学遥感估算。研究表明：相较于绿潮像元面积和覆盖面积,绿潮生物量估算结果的不确定性最小,该参数能减少面积参数包含的尺度效应差异,能更准确地用于海洋生态环境的量化与评估。此外,基于CZI和MODIS数据开展2021年中国近海绿潮生物量协同监测应用,有效提高了绿潮生物量监测的精度,详细量化了2021年中国近海绿潮生物量的年内变化,展现了绿潮生物量的精细空间分布格局与变化趋势。多源光学遥感数据开展绿潮生物量遥感估算,对中国近海漂浮藻类的精准、定量、动态监测,具有重要的方法与数据支撑意义。

Green tide biomass is a key parameter for accurate quantification of floating macroalgae as well as an effective indicator to reflect the change of marine ecological environment. Optical remote sensing satellites can provide data support for the fine quantitative monitoring and evaluation of green tide, and realize the accurate detection and quantitative estimation of green tide. The Moderate Resolution Imaging Spectroradiometer (MODIS) of National Aeronautics and Space Administration (NASA) of the United States, the Multispectral Instrument (MSI) onboard Sentinel-2 satellites of the European Space Agency, and the Coastal Zone Imager (CZI) onboard China’s HaiYang-1C/D (HY-1C/D) satellites can provide the long time series and high resolution observations for quantifying green tides biomass in the Yellow Sea of China. Based on laboratory measurements of U. prolifera biomass (wet weight) per unit area and the corresponding spectral reflectance, some robust estimation relationships have been established to link biomass per area of green tide to the different optical parameters of floating algae detected from CZI, MSI, and MODIS images, and the cross validation of remote sensing estimation results among different satellite data is also realized. This study shows that this method can effectively reduce the uncertainty in remote sensing monitoring of green tide, especially in the difference of scale effect (caused by spatial resolution) in the spaceborne remotely estimation of green tide, to provide more accurate reference for quantification and assessment of marine ecological environment. Based on the CZI and MODIS data from 2021, the biomass per area (BPA) images of green tide with high temporal and spatial resolution were produced. The co-monitoring application between CZI and MODIS effectively improves the accuracy of green tide biomass monitoring, better reflects the intra-year spatio-temporal variation trend of green tide. Based on multi-source optical remote sensing data, the accurate estimation of green tide biomass has important theoretical and methodological significance for accurate, quantitative and dynamic monitoring of floating algae.