Atmospheric correction of geostationary satellite ocean color data under high solar zenith angles in open oceans
Atmospheric correction of geostationary satellite ocean color data under high solar zenith angles in open oceans
复制标题
公海高太阳天顶角下对地静止卫星海洋颜色数据的大气校正
DOI：
10.1016/j.rse.2020.112022
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发表时间：
2020-11
影响因子：
13.5
通讯作者：
Haiqing Huang
中科院分区：
文献类型：
--
作者：
Hao Li;Xianqiang He;Yan Bai;Palanisamy Shanmugam;Young-Je Park;Jia Liu;Qiankun Zhu;Fang Gong;Difeng Wang;Haiqing Huang
地球同步海洋水色成像仪（GOCI）具有1 h重访时间、500 m空间分辨率和高辐射灵敏度等特点，被广泛应用于海洋现象的日动态监测。然而，GOCI数据的大气校正（AC）与高太阳天顶角（>70°）仍然是传统算法的挑战。在这里，我们提出了一种新的神经网络（NN）AC算法GOCI数据下高太阳天顶角。与传统的神经网络AC算法训练的辐射传输模拟数据集，我们的新AC算法是由GOCI观测的瑞利校正的辐射在早上和晚上和GOCI检索的高质量中午遥感反射率（Rrs）之间的大量匹配训练。当使用每小时的GOCI数据进行验证时，新的NN AC算法在开放的海洋沃茨从早上到晚上产生了日稳定的RRS。此外，当验证从三个气溶胶机器人网络-海洋颜色（AERONET-OC）站（Socheongcho，Gageocho和Ieodo）的原位数据，GOCI检索Rrs在可见光波段使用新的AC算法获得的一致，以及与原位值，即使在高太阳天顶角。新算法的实际应用，进一步检查使用白天的GOCI观测数据在明确的开放海洋沃茨。实验结果表明，该算法成功地检索了早晨和傍晚GOCI数据的Rrs。此外，新算法检索的Rrs数据量远高于SeaDAS中标准AC算法检索的Rrs数据量。我们提出的NN AC算法不仅可以应用于处理GOCI数据在早上和晚上，但也有可能被应用于处理极轨卫星海洋水色数据在高纬度海洋，也包括卫星观测与高太阳天顶角。
With a revisit time of 1 h, spatial resolution of 500 m, and high radiometric sensitivity, the Geostationary Ocean Color Imager (GOCI) is widely used to monitor diurnal dynamics of oceanic phenomena. However, atmospheric correction (AC) of GOCI data with high solar zenith angle (>70°) is still a challenge for traditional algorithms. Here, we propose a novel neural network (NN) AC algorithm for GOCI data under high solar zenith angles. Unlike traditional NN AC algorithms trained by radiative transfer-simulated dataset, our new AC algorithm was trained by a large number of matchups between GOCI-observed Rayleigh-corrected radiance in the morning and evening and GOCI-retrieved high-quality noontime remote-sensing reflectance (Rrs). When validated using hourly GOCI data, the new NN AC algorithm yielded diurnally stable Rrs in open ocean waters from the morning to evening. Furthermore, when validated byin-situdata from three Aerosol Robotic Network-Ocean Color (AERONET-OC) stations (Socheongcho, Gageocho and Ieodo), the GOCI-retrieved Rrs at visible bands obtained using the new AC algorithm agreed well with thein-situvalues, even under high solar zenith angles. Practical application of the new algorithm was further examined using diurnal GOCI observation data acquired in clear open ocean waters. Results showed that the new algorithm successfully retrieved Rrs for the morning and evening GOCI data. Moreover, the amount of Rrs data retrieved by the new algorithm was much higher than that retrieved by the standard AC algorithm in SeaDAS. Our proposed NN AC algorithm can not only be applied to process GOCI data acquired in the morning and evening, but also has the potential to be applied to process polar-orbiting satellite ocean color data at high-latitude ocean that also include satellite observation with high solar zenith angles.
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影响因子：
2.6
作者：
J. Brajard;C. Jamet;C. Moulin;S. Thiria
通讯作者：
J. Brajard;C. Jamet;C. Moulin;S. Thiria
影响因子：
13.5
作者：
Yongzhen Fan;Wei Li;C. Gatebe;C. Jamet;G. Zibordi;T. Schroeder;K. Stamnes
通讯作者：
Yongzhen Fan;Wei Li;C. Gatebe;C. Jamet;G. Zibordi;T. Schroeder;K. Stamnes
影响因子：
1.9
作者：
N. Pahlevan;Z. Lee;Chuanmin Hu;J. Schott
通讯作者：
N. Pahlevan;Z. Lee;Chuanmin Hu;J. Schott
影响因子：
3.8
作者：
C. Goyens;Cédric Jamet;Kevin Ruddick
通讯作者：
C. Goyens;Cédric Jamet;Kevin Ruddick
影响因子：
56.9
作者：
PLATT, T;SATHYENDRANATH, S
通讯作者：
SATHYENDRANATH, S