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

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) to describe the influence of PSD variation on remote sensing reflectance (R). 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 and POC. The POC in Hangzhou bay caused by spring and neap tides vary significantly.