The suspended particulate matter (SPM) concentration (unit: mg l⁻¹) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance (R_rs(λ)) at near-infrared (NIR), red, green, and blue bands (NIR-RGB) as input. The evaluations showed that the NIR-RGB algorithm could predict SPM with the median absolute percentage difference of ∼35%–39% over a wide range from ∼0.01 to >2,000 mg l⁻¹. The uncertainty is smaller (29%–37%) for turbid waters where R_rs(671) ≥ 0.0012 sr⁻¹ and slightly higher (41%–44%) for clear waters where R_rs(671) < 0.0012 mg l⁻¹. The algorithm was implemented with the global R_rs(λ) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS-generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications.

中文翻译：

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从卫星海洋彩色图像中对悬浮颗粒物的全球估计

地表水中的悬浮颗粒物（SPM）浓度（单位：mg l ^-1）是衡量水质和透明度的重要指标。卫星遥感提供了一个强大的工具来导出具有天气和重复覆盖的 SPM。在这项研究中，我们开发了一种新的全局 SPM 算法，利用近红外 (NIR)、红、绿和蓝波段 (NIR-RGB) 的遥感反射率 ( R _rs ( λ )) 作为输入。评估表明，NIR-RGB 算法可以在从 ∼0.01 到 >2,000 mg l ^-1的宽范围内以 ∼35%–39% 的中值绝对百分比差异预测 SPM 。对于R _rs (671) ≥ 0.0012 sr ^-1的混浊水域，不确定性较小 (29%–37%)对于R _rs (671) < 0.0012 mg l ^-1的清水，略高 (41%–44%) 。该算法是用全局R _rs ( λ) 来自 Suomi 国家极地轨道合作伙伴 (SNPP) 卫星上的可见红外成像辐射计套件 (VIIRS) 的数据。我们根据月度 SPM 复合材料简要描述了 SPM 产品在全球水域中的空间分布和时间趋势。沿海和内陆水域 SPM 时间序列的案例研究表明，卫星 SPM 估计也记录了区域尺度的空间和季节变化以及偶发事件。VIIRS 生成的全球 SPM 地图为用于环境和气候应用的现有海洋颜色产品提供了有价值的补充。