Abstract
The power law particle size distribution (PSD) slope parameter is commonly used to characterize sediment fluxes, resuspension, aggregates, and settling rates in coastal and estuarine waters. However, particle size distribution metrics are also very useful for understanding sediment source and dynamic processes. In this study, a method was proposed to employ the particle size parameters commonly used in sedimentary geology (average particle size (ø), sorting, skewness, and kurtosis) as indicators of changes in sediment dynamic processes, and MODIS images were used to estimate these parameters. The particle size parameters were estimated using a Mie scattering model, Quasi-Analytical Algorithm (QAA) analysis algorithm, and least squares QR decomposition (LSQR) solution method based on the relationship between the power law distribution of the suspended particles and their optical scattering properties. The estimates were verified by field measurements in the Yellow Sea and Bohai Sea regions of China. This method provided good estimates of the average particle size (ø), sorting, and kurtosis. A greater number of wavebands (39) was associated with more accurate particle size distribution curves. Furthermore, the method was used to monitor changes in suspended particulate matter in the vicinity of the Heini Bay of China before and after the passage of a strong storm in August 2011. The particle size parameters represented the influence of a strong typhoon on the distribution of the near-shore sediment and, together with the PSD slope, comprehensively reflected the changes in the near-shore suspended particulate matter. This method not only established the relationship between remote sensing monitoring and the historical sediment record, it also extends the power law model to the application of sediment source and dynamic processes in coastal waters.
Highlights
Particle size distribution (PSD) is a fundamental property of natural water particle assemblages and plays an important indicative role in many fields of marine science [1]
Mineral particles tend to account for a large proportion of suspended particulate matter due to river discharge, coastal erosion caused by waves and currents, and seafloor resuspension [8]
The chlorophyll concentration measured before the passage of typhoon Muifa on 8 August 2011, revealed the chlorophyll concentration measured in situ has a good correlation with the measured remote sensing reflectivity at 350–720 nm (Figure 2a)
Summary
Particle size distribution (PSD) is a fundamental property of natural water particle assemblages and plays an important indicative role in many fields of marine science [1]. The theoretical relationship between the backscattering spectral slope and the power law PSD slope has been used to derive the seawater surface PSD (hereinafter referred to as the surface PSD) from ocean color remote sensing images on a global scale These estimates have been applied to identify phytoplankton functional groups and to estimate carbon sequestration within the ocean [2,3]; these generally straightforward approaches cannot accommodate the optical complexity of coastal regions that have waters rich in terrigenous material [4,5]. There is still no consensus that scattering particles in even the most oligotrophic seas may be organic or inorganic [9], and current estimation models attribute the optical properties of the surface water to plankton microorganisms and detrital matter [10] As a result, these models do not work well in coastal areas. The particle size distribution curve and Remote Sens. 2020, 12, 2581 its parameters were compared with those in the sedimentary records to obtain indices that could characterize the impact of the ocean dynamic environmental on the particle size distribution
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