The objective of this paper was to compare the limits of three image-based atmospheric correction models (top of the atmosphere (ToA), dark object subtraction (DOS), and cosine of the sun zenith angle (COST)), and three physical models (atmospheric correction for flat terrain (ATCOR), fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH)), and ACOLITE) for retrieving suspended particulate matter (SPM) concentrations in inland water bodies using Landsat imagery. For SPM concentration estimates, all possible combinations of 2-band normalized ratios ($2b_{NR}$) were computed, and a stepwise regression was applied. The correlation analysis allowed highlighting that the red/blue $2b_{NR}$ was the best spectral index to retrieve SPM concentrations in the case of image-based models, while the red/green $2b_{NR}$ was the best in the case of physical models. Contrary to expectations, image-based atmospheric models outperformed the accuracy of physical models. The cross-validation results underlined the good performance of the DOS and COST models, with R² > 0.83, NASH-criterion (Nash) > 0.83, bias = −0.01 mg/L, and RMSE < 0.27 mg/L. This outperformance was confirmed using blind test validation data, with an R² > 0.86 and Nash > 0.58 for the DOS and COST models. The challenges and limitations involved in the remote monitoring of SPM spatial distribution in turbid productive waters using satellite data are discussed at the end of the paper.

中文翻译：

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内陆水域悬浮颗粒物的远程检索：基于图像还是物理大气校正模型？

本文的目的是比较三种基于图像的大气校正模型（大气顶 (ToA)、暗天体减法 (DOS) 和太阳天顶角余弦 (COST)）和三种物理模型的局限性（平坦地形的大气校正 (ATCOR)、光谱超立方体的快速视线大气分析 (FLAASH)）和 ACOLITE），用于使用 Landsat 图像检索内陆水体中的悬浮颗粒物 (SPM) 浓度。对于 SPM 浓度估计，2 波段归一化比率的所有可能组合（$2{乙}_{N\mathrm{电阻}}$) 进行计算，并应用逐步回归。相关性分析允许突出显示红色/蓝色$2{乙}_{N\mathrm{电阻}}$ 在基于图像的模型的情况下，是检索 SPM 浓度的最佳光谱指数，而红色/绿色 $2{乙}_{N\mathrm{电阻}}$在物理模型的情况下是最好的。与预期相反，基于图像的大气模型优于物理模型的准确性。交叉验证结果强调了 DOS 和 COST 模型的良好性能，R ² > 0.83，NASH 标准 (Nash) > 0.83，偏差 = -0.01 mg/L，RMSE < 0.27 mg/L。使用盲测验证数据证实了这种优异性能，DOS 和 COST 模型的 R ² > 0.86 和 Nash > 0.58。本文末尾讨论了使用卫星数据远程监测混浊生产水域中 SPM 空间分布的挑战和局限性。