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Atmospheric and sunglint correction for retrieving chlorophyll-a in a productive tropical estuarine-lagoon system using Sentinel-2 MSI imagery
ISPRS Journal of Photogrammetry and Remote Sensing ( IF 10.6 ) Pub Date : 2021-02-27 , DOI: 10.1016/j.isprsjprs.2021.01.021
Matheus Henrique Tavares , Regina Camara Lins , Tristan Harmel , Carlos Ruberto Fragoso Jr. , Jean-Michel Martínez , David Motta-Marques

Remote monitoring of chlorophyll-a (chla) has been widely used to evaluate the trophic state of inland and coastal waters, however, there is still much uncertainty in the algorithms applied in different optical water types. The influence of different atmospheric correction (AC) processors, which can also provide correction for sunglint and adjacency effects, on the retrieved chla is poorly understood. In this study, state-of-the-art atmospheric correction and chla algorithms are evaluated using Sentinel-2 MSI imagery in the Mundaú-Manguaba Estuarine-Lagoon System (MMELS), a productive tropical system that consists of two turbid lagoons of different optical water types (OWT). We compared the performance of six AC processors, with the addition of sunglint correction for two of them, with field measured water reflectance. There was difficulty in correcting for the atmospheric effects, especially for bands 2, 3 and 8A. Overall, C2X showed the best performance over MMELS, but with sunglint correction, ACOLITE and GRS provided the most consistent water reflectance (ρw). Sunglint correction might be essential for retrieving accurate ρw in most low-latitude water bodies. We also found that in Mundaú, the dense urban area surrounding it likely caused heavy adjacency effects in the satellite-retrieved reflectance, and thus correction for it is necessary. We also compared the performance of six chla algorithms recommended for the OWTs present in MMELS in addition to a widely applied and a global chla algorithm in retrieving this variable using both field and satellite reflectance, in this case corrected with the three best performing processors. For the in situ data, most algorithms performed well in Manguaba lagoon, while in Mundaú lagoon the semi-analytical NIR-red ratio (2SAR) algorithm was the most consistent model, and in both cases the locally calibrated algorithms outperformed the global algorithm. When retrieving chla with the satellite-derived ρw, considerably poorer results were produced, especially in Mundaú lagoon. The global algorithm was found to be especially sensitive to the atmospheric effects. We also found that the quality of AC provided by the algorithms is not a general predictor of the performance of the chla models, even when analysing individual bands separately, while the relationship between chla concentration and the ratio of bands used by most algorithms can be. Despite containing distinct water characteristics, chla can be modelled using a single algorithm, 2SAR, calibrated for MMELS as a whole, with r2 of 0.77 and nRMSE of 38.7%, and we consider that 2SAR has the potential to be a global algorithm for these OWTs, provided that it is recalibrated for a large dataset of satellite-derived BOA reflectance. We recommend that further studies explore the impacts of AC, sunglint and adjacency effects on the performance of chla algorithms, in order to delineate the most suitable combinations of AC + chla algorithms for the variable OWTs, in an effort to provide the basis for global-scale retrievals of this pigment using medium-resolution sensors such as MSI and OLI.



中文翻译:

使用Sentinel-2 MSI图像在生产性热带河口泻湖系统中检索叶绿素a的大气和日照校正

叶绿素achla)的远程监测已广泛用于评估内陆和沿海水域的营养状态,但是,在不同光学水类型中应用的算法仍然存在很多不确定性。人们还不太了解不同的大气校正(AC)处理器对回收的chla的影响,这些处理器也可以对阳光和邻接效应进行校正。在这项研究中,最先进的大气校正和CHLA算法使用Mundaú-Manguaba河口-泻湖系统(MMELS)中的Sentinel-2 MSI影像进行评估,该系统是一个生产性热带系统,由两个不同光学水类型(OWT)的混浊泻湖组成。我们将六个交流处理器的性能进行了比较,并在其中两个中进行了日照校正,并通过现场测得的水反射率进行了比较。在校正大气影响方面存在困难,尤其是对于频带2、3和8A而言。总体而言,C2X的性能优于MMELS,但经过阳光直射校正后,ACOLITE和GRS提供了最一致的水反射率(ρw)。Sunglint校正对于准确检索可能必不可少ρw在大多数低纬度水体中。我们还发现,在Mundaú,它周围的人口稠密的市区很可能对卫星获取的反射率产生严重的邻接效应,因此有必要对其进行校正。我们还比较了推荐用于MMELS中OWT的六种chla算法的性能,此外还使用场反射率和卫星反射率检索了广泛应用的全局chla算法和全局chla算法,在这种情况下,使用了三个性能最佳的处理器进行了校正。对于原位数据显示,大多数算法在Manguaba泻湖中表现良好,而在Mundaú泻湖中,半解析NIR-红色比率(2SAR)算法是最一致的模型,在两种情况下,本地校准算法均优于全局算法。使用卫星衍生的chla检索时ρw,结果却很差,尤其是在蒙道泻湖。发现全局算法对大气影响特别敏感。我们还发现,即使单独分析各个频带,算法提供的交流质量也不是chla模型性能的一般预测指标,而chla浓度与大多数算法使用的频带比率之间的关系可以。尽管chla具有明显的水特征,但可以使用单一算法2SAR对MHLA整体进行校准,从而对chla进行建模。[R2个系数为0.77,nRMSE为38.7%,并且我们认为2SAR有可能成为这些OWT的全局算法,前提是它已针对来自卫星的BOA反射率的大型数据集进行了重新校准。我们建议进一步研究探索AC,阳光和邻接效应对chla算法性能的影响,以便为可变的OWT划定AC + chla算法的最合适组合, 从而为全球使用中等分辨率的传感器(例如MSI和OLI)对这种色素进行大规模检索。

更新日期:2021-02-28
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