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A novel algorithm for ocean chlorophyll-a concentration using MODIS Aqua data
ISPRS Journal of Photogrammetry and Remote Sensing ( IF 12.7 ) Pub Date : 2024-03-25 , DOI: 10.1016/j.isprsjprs.2024.03.014
Julian Merder , Gang Zhao , Nima Pahlevan , Robert A. Rigby , Dimitrios M. Stasinopoulos , Anna M. Michalak

The ability to infer ocean chlorophyll- concentrations (Chl) from spaceborne instruments is key to assessments of global ocean productivity and monitoring of water quality. Here, we present a novel parametric algorithm, OCG, trained on a set of global high-performance liquid chromatography (HPLC) data that leverages Level-3 remote sensing reflectance () products from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. The OCG algorithm leverages more bands than existing algorithms and also provides pixel-wise uncertainty assessments that enable the calculation of the probability of exceeding specific Chl thresholds. This feature has significant implications for water quality management, particularly in monitoring harmful algal blooms. The OCG surpasses existing algorithms in bias and accuracy without overfitting, especially in coastal areas, where it outperforms the current standard product (CI OC3) by 20 % in median symmetric accuracy. Moreover, the OCG reduces the signed symmetric percentage bias (SSPB) in coastal regions from 41 % (CI OC3) to below 5 %. Globally, the OCG algorithm yields lower Chl in coastal regions, the Southern Ocean and the Mediterranean Sea, and higher values in the open ocean, particularly in ocean gyres and polar regions. For the Chesapeake Bay and the Baltic Sea, for example, daily OCG estimates for 2002 to 2021 are, on average, 2.9 g/L and 3.7 g/L lower than CI OC3 estimates, respectively. The presented approach also shows great potential for other existing and upcoming sensors, enabling widespread application in remote sensing.

中文翻译:

使用 MODIS Aqua 数据计算海洋叶绿素 a 浓度的新算法

通过星载仪器推断海洋叶绿素浓度 (Chl) 的能力是评估全球海洋生产力和监测水质的关键。在这里,我们提出了一种新颖的参数算法 OCG,该算法在一组全球高性能液相色谱 (HPLC) 数据上进行训练,该数据利用 Aqua 卫星上的中分辨率成像光谱辐射计 (MODIS) 的 3 级遥感反射率 () 产品。 OCG 算法比现有算法利用更多波段,并且还提供逐像素不确定性评估,从而能够计算超过特定 Chl 阈值的概率。这一特征对水质管理具有重要意义,特别是在监测有害藻华方面。 OCG 在偏差和准确性方面超越了现有算法,且没有过度拟合,特别是在沿海地区,其中值对称精度比当前标准产品(CI OC3)高出 20%。此外,OCG 将沿海地区的符号对称百分比偏差 (SSPB) 从 41% (CI OC3) 降低到 5% 以下。在全球范围内,OCG 算法在沿海地区、南大洋和地中海产生较低的叶绿素值,而在公海,特别是在洋环和极地地区产生较高的值。例如,对于切萨皮克湾和波罗的海,2002 年至 2021 年每日 OCG 估计值平均分别比 CI OC3 估计值低 2.9 g/L 和 3.7 g/L。所提出的方法还显示了其他现有和即将推出的传感器的巨大潜力,可在遥感领域得到广泛应用。
更新日期:2024-03-25
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