Assessment of satellite ocean color products of MERIS, MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)
Assessment of satellite ocean color products of MERIS, MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)
复制标题
我国东部沿海（黄海、东海）MERIS、MODIS、SeaWiFS卫星海洋颜色产品评估
DOI：
10.1016/j.isprsjprs.2013.10.013
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发表时间：
2014-01-01
影响因子：
12.7
通讯作者：
Song, Qingjun
中科院分区：
文献类型：
--
作者：
Cui, Tingwei;Zhang, Jie;Song, Qingjun
卫星海洋色彩产品的验证是海洋色彩任务的一项重要任务。这些产品的不确定性在黄海 (YS) 和东海 (ECS) 中很难量化，这些区域以其海洋和大气光学特性的光学复杂性和浑浊度而闻名。本文的目的是评估三颗主要海洋颜色卫星的主要海洋颜色产品，即中分辨率成像光谱仪（MODIS）、中分辨率成像光谱仪（MERIS）和海景宽视场传感器（SeaWiFS）。通过与现场数据的匹配分析发现，MERIS、MODIS和SeaWiFS卫星反演蓝绿和绿波段光谱遥感反射率R-rs(lambda)的不确定度最低，绝对差异百分比中值(APD(m))为15-27%，均方根误差(RMS)为0.0021-0.0039 sr(-1)，而412 nm处的R-rs(lambda)不确定度最高(APD(m) 47-62%，RMS 0.0027-0.0041 sr(-1))。还量化了气溶胶光学厚度（AOT）tau（a）、490 nm K-d（490）处向下辐照度的漫反射衰减系数、悬浮颗粒沉积物浓度（SPM）和叶绿素a（Chl-a）的不确定性。结果表明，采用专门针对浑浊水域开发的适当水下算法，而不是在运行卫星数据处理链中采用的标准算法，K-d(490)、SPM和Chl-a的卫星衍生特性的不确定性可能会显着降低至20-30%的水平，这对于大多数研究区域来说都是如此。该验证活动主张（1）利用区域气溶胶光学模型改进大气校正算法，（2）在浑浊的沿海水域切换到区域水内算法，以及（3）持续支持验证任务的专用现场数据收集工作。 (C) 2013 年国际摄影测量与遥感协会 (ISPRS) 由 Elsevier B.V 出版。保留所有权利。
The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance R-rs(lambda) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APD(m)) of 15-27% and root-mean-square-error (RMS) of 0.0021-0.0039 sr(-1), whereas the R-rs(lambda) uncertainty at 412 nm is the highest (APD(m) 47-62%, RMS 0.0027-0.0041 sr(-1)). The uncertainties of the aerosol optical thickness (AOT) tau(a), diffuse attenuation coefficient for downward irradiance at 490 nm K-d(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of K-d(490), SPM, and Chl-a may decrease significantly to the level of 20-30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task. (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.