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Remote sensing approach for the estimation of particulate organic carbon in coastal waters based on suspended particulate concentration and particle median size

机译:基于悬浮颗粒浓度和粒子中值尺寸的沿海水中沿水域粒子有机碳估计的遥感方法

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摘要

The particulate organic carbon (POC) content retrieved by remote sensors is influenced by the suspended particulate concentration (SPC) and the particle size distribution (PSD). The objective of this study was to provide study case of remote sensing monitoring of non-optical activity substance POC in Hangzhou bay, China. A modified empirical remote sensing algorithm was established based on SPC and median particle size (D-50) to describe the influence of PSD variation on remote sensing reflectance (R-rs). The algorithm was applied to MODIS data to reveal POC spatial and temporal variations. The results show that the accuracy of the remote sensing estimation algorithm, established on the basis of Mie theory, is relatively higher than the empirical model simply based on the statistical correlation between R-rs and POC. The POC in Hangzhou bay caused by spring and neap fides vary significantly.
机译:通过远程传感器检索的颗粒状有机碳(POC)含量受悬浮颗粒浓度(SPC)和粒度分布(PSD)的影响。本研究的目的是提供中国杭州湾非光学活性物质POC的研究案例。基于SPC和中值粒度(D-50)建立了修改的经验遥感算法,以描述PSD变化对遥感反射率(R-RS)的影响。该算法应用于Modis数据以显示PoC空间和时间变化。结果表明,在MIE理论的基础上建立的遥感估计算法的准确性,仅基于R-RS与POC之间的统计相关性相对高于经验模型。杭州湾的POC由春天和NEAP FIDE造成的显着变化。

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