首页> 外文期刊>ISPRS Journal of Photogrammetry and Remote Sensing >Determining switching threshold for NIR-SWIR combined atmospheric correction algorithm of ocean color remote sensing
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Determining switching threshold for NIR-SWIR combined atmospheric correction algorithm of ocean color remote sensing

机译:海洋颜色遥感的近红外-大气红外组合大气校正算法的切换阈值确定

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摘要

Accurate atmospheric correction is decisive for ocean color remote sensing applications. Near infrared (NIR)-based algorithm performs well for clear waters; while shortwave infrared (SWIR)-based algorithm can obtain good results for turbid waters, however, it tends to produce noisy patterns for clear waters. A practical strategy is to apply NIR- and SWIR-based algorithm for clear and turbid waters, respectively, which is called NIR-SWIR combined atmospheric correction algorithm. However, the currently applied switching scheme for the NIR-SWIR algorithm undermines the atmospheric correction performance. This study aimed to find an applicable switching scheme for NIR-SWIR algorithm. Four MODIS land bands were used to switch the NIR- and SWIR-based algorithms. A simulated dataset was used to evaluate atmospheric performance of NIR- and SWIR-based algorithm. The switching threshold for each MODIS land band was determined as an R-rs value at which SWIR-based algorithm performed better than NIR-based algorithm. The switching scheme was evaluated using matchups of simultaneous MODIS Aqua images and AERONET-OC data, and then tested with a MODIS Aqua image over the western Pacific Ocean. Results showed that the switching threshold for R-rs(469), R-rs(555), R-rs(645) and R-rs(859) were 0.009, 0.016, 0.009 and 0.0006 sr(-1), respectively; R-rs(645) with a threshold of 0.009 sr(-1) and R-rs(555) with a threshold of 0.016 sr(-1) worked well for NIR-SWIR algorithm, while R-rs(469) and R-rs(859) produced worse performance. Therefore, R-rs(555) 0.016 sr(-1) or R-rs(645) 0.009 sr(-1) was recommended as the switching scheme for NIR-SWIR algorithm. Considering contrasted estuarine, coastal and some inland waters, combining NIR- and SWIR-based atmospheric correction algorithm with the proposed switching scheme should be useful for remote sensing monitoring over these waters.
机译:准确的大气校正对于海洋彩色遥感应用至关重要。基于近红外(NIR)的算法在清澈的海水中表现良好;虽然基于短波红外(SWIR)的算法在混浊水域中可以获得很好的效果,但是,对于清澈的水域,它倾向于产生嘈杂的模式。一种实用的策略是将基于NIR和SWIR的算法分别应用于清澈和浑浊的水域,这称为NIR-SWIR组合大气校正算法。但是,当前为NIR-SWIR算法应用的切换方案破坏了大气校正性能。本研究旨在寻找一种适用于NIR-SWIR算法的切换方案。四个MODIS陆带用于切换基于NIR和SWIR的算法。模拟数据集用于评估基于NIR和SWIR的算法的大气性能。将每个MODIS陆地频段的切换阈值确定为R-rs值,基于SWIR的算法比基于NIR的算法性能更好。使用同时的MODIS Aqua图像和AERONET-OC数据的匹配评估切换方案,然后在西太平洋上使用MODIS Aqua图像进行测试。结果表明,R-rs(469),R-rs(555),R-rs(645)和R-rs(859)的切换阈值分别为0.009、0.016、0.009和0.0006 sr(-1);对于NIR-SWIR算法,阈值为0.009 sr(-1)的R-rs(645)和阈值为0.016 sr(-1)的R-rs(555)效果很好,而R-rs(469)和R -rs(859)产生了较差的性能。因此,建议将R-rs(555)> 0.016 sr(-1)或R-rs(645)> 0.009 sr(-1)作为NIR-SWIR算法的切换方案。考虑到河口,沿海和部分内陆水域的对比,将基于NIR和SWIR的大气校正算法与所提出的切换方案相结合,对于这些水域的遥感监测应该是有用的。

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    Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Minist Nat Resources, Shenzhen 518060, Peoples R China|Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China|Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;

    Hong Kong Baptist Univ, Dept Geog, Kowloon, Hong Kong, Peoples R China;

    Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Minist Nat Resources, Shenzhen 518060, Peoples R China|Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China|Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;

    Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Minist Nat Resources, Shenzhen 518060, Peoples R China|Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China|Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;

    Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Minist Nat Resources, Shenzhen 518060, Peoples R China|Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China|Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;

    Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Minist Nat Resources, Shenzhen 518060, Peoples R China|Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China|Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China|Shenzhen Univ, Coll Life Sci & Oceanog, Shenzhen 518060, Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Water quality; Ocean color atmospheric correction; NIR-SWIR; Aerosol;

    机译:水质海洋色彩大气校正近红外-短波红外气溶胶;

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