使用Case-2区域海岸颜色处理器在波罗的海生成的哨兵-3A OLCI产品评估

Evaluation of Sentinel-3A OLCI Products Derived Using the Case-2 Regional CoastColour Processor over the Baltic Sea.

作者信息

Kyryliuk Dmytro, Kratzer Susanne

机构信息

Department of Ecology, Environment and Plant Sciences, Stockholm University, 10691 Stockholm, Sweden.

出版信息

Sensors (Basel). 2019 Aug 19;19(16):3609. doi: 10.3390/s19163609.

DOI:10.3390/s19163609

PMID:31430993

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6720489/

Abstract

In this study, the Level-2 products of the Ocean and Land Colour Instrument (OLCI) data on Sentinel-3A are derived using the Case-2 Regional CoastColour (C2RCC) processor for the SentiNel Application Platform (SNAP) whilst adjusting the specific scatter of Total Suspended Matter (TSM) for the Baltic Sea in order to improve TSM retrieval. The remote sensing product "kd_z90max" (i.e., the depth of the water column from which 90% of the water-leaving irradiance are derived) from C2RCC-SNAP showed a good correlation with in situ Secchi depth (SD). Additionally, a regional in-water algorithm was applied to derive SD from the attenuation coefficient (489) using a local algorithm. Furthermore, a regional in-water relationship between particle scatter and bench turbidity was applied to generate turbidity from the remote sensing product "iop_bpart" (i.e., the scattering coefficient of marine particles at 443 nm). The spectral shape of the remote sensing reflectance () data extracted from match-up stations was evaluated against reflectance data measured in situ by a tethered Attenuation Coefficient Sensor (TACCS) radiometer. The L2 products were evaluated against in situ data from several dedicated validation campaigns (2016-2018) in the NW Baltic proper. All derived L2 in-water products were statistically compared to in situ data and the results were also compared to results for MERIS validation from the literature and the current S3 Level-2 Water (L2W) standard processor from EUMETSAT. The Chl-a product showed a substantial improvement (MNB 21%, RMSE 88%, APD 96%, = 27) compared to concentrations derived from the Medium Resolution Imaging Spectrometer (MERIS), with a strong underestimation of higher values. TSM performed within an error comparable to MERIS data with a mean normalized bias (MNB) 25%, root-mean square error (RMSE) 73%, average absolute percentage difference (APD) 63% = 23). Coloured Dissolved Organic Matter (CDOM) absorption retrieval has also improved substantially when using the product "iop_adg" (i.e., the sum of organic detritus and Gelbstoff absorption at 443 nm) as a proxy (MNB 8%, RMSE 56%, APD 54%, = 18). The local SD (MNB 6%, RMSE 62%, APD 60%, = 35) and turbidity (MNB 3%, RMSE 35%, APD 34%, = 29) algorithms showed very good agreement with in situ data. We recommend the use of the SNAP C2RCC with regionally adjusted TSM-specific scatter for water product retrieval as well as the regional turbidity algorithm for Baltic Sea monitoring. Besides documenting the evaluation of the C2RCC processor, this paper may also act as a handbook on the validation of Ocean Colour data.

摘要

在本研究中，利用适用于哨兵应用平台（SNAP）的二类区域海岸颜色（C2RCC）处理器，对哨兵-3A上的海洋和陆地颜色仪器（OLCI）数据的二级产品进行了推导，同时针对波罗的海调整了总悬浮物（TSM）的特定散射，以改进TSM反演。C2RCC-SNAP的遥感产品“kd_z90max”（即90%的离水辐照度所源自的水柱深度）与现场赛氏深度（SD）显示出良好的相关性。此外，应用一种区域水中算法，使用局部算法从衰减系数（489）推导SD。此外，应用粒子散射与实验台浊度之间的区域水中关系，从遥感产品“iop_bpart”（即443nm处海洋粒子的散射系数）生成浊度。从匹配站提取的遥感反射率（）数据的光谱形状，与通过系留衰减系数传感器（TACCS）辐射计现场测量的反射率数据进行了评估。针对波罗的海西北部几次专门验证活动（2016 - 2018年）的现场数据，对二级产品进行了评估。将所有推导的二级水中产品与现场数据进行了统计比较，结果还与文献中MERIS验证结果以及欧洲气象卫星应用组织当前的S3二级水（L2W）标准处理器的结果进行了比较。与从中分辨率成像光谱仪（MERIS）得出的浓度相比，叶绿素a产品有显著改进（平均归一化偏差21%，均方根误差88%，平均绝对百分比差异96%， = 27），但对较高值有严重低估。TSM的误差与MERIS数据相当，平均归一化偏差（MNB）25%，均方根误差（RMSE）73%，平均绝对百分比差异（APD）63%（ = 23）。当使用产品“iop_adg”（即443nm处有机碎屑和黄色物质吸收之和）作为替代指标时，有色溶解有机物（CDOM）吸收反演也有显著改进（MNB 8%，RMSE 56%，APD 54%， = 18）。局部SD（MNB 6%，RMSE 62%，APD 60%， = 35）和浊度（MNB 3%，RMSE 35%，APD 34%， = 29）算法与现场数据显示出非常好的一致性。我们建议使用经区域调整的TSM特定散射的SNAP C2RCC进行水产品反演以及用于波罗的海监测的区域浊度算法。除了记录C2RCC处理器的评估外，本文还可作为海洋颜色数据验证的手册。