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Remote Sens. 2016, 8(10), 841; doi:10.3390/rs8100841

Remote Sensing of Particle Cross-Sectional Area in the Bohai Sea and Yellow Sea: Algorithm Development and Application Implications

1
School of Marine Sciences, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, Jiangsu, China
2
Jiangsu Research Center for Ocean Survey Technology, NUIST, Nanjing 210044, Jiangsu, China
*
Author to whom correspondence should be addressed.
Academic Editors: Claudia Giardino, Linhai Li, Yunlin Zhang, Xiaofeng Li and Prasad S. Thenkabail
Received: 26 July 2016 / Revised: 23 September 2016 / Accepted: 8 October 2016 / Published: 22 October 2016
(This article belongs to the Special Issue Water Optics and Water Colour Remote Sensing)
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Abstract

Suspended particles in waters play an important role in determination of optical properties and ocean color remote sensing. To link suspended particles to their optical properties and thereby remote sensing reflectance (Rrs(λ)), cross-sectional area is a key factor. Till now, there is still a lack of methodologies for derivation of the particle cross-sectional area concentration (AC) from satellite measurements, which consequently limits potential applications of AC. In this study, we investigated the relationship between AC and Rrs(λ) based on field measurements in the Bohai Sea (BS) and Yellow Sea (YS). Our analysis confirmed the strong dependence of Rrs(λ) on AC and that such dependence is stronger than on mass concentration. Subsequently, a remote sensing algorithm that uses the slope of Rrs(λ) between 490 and 555 nm was developed for retrieval of AC from satellite measurements of the Geostationary Ocean Color Imager (GOCI). In situ evaluations show that the algorithm displays good performance for deriving AC and is robust to uncertainties in Rrs(λ). When the algorithm was applied to satellite data, it performed well, with a coefficient of determination of 0.700, a root mean squared error of 2.126 m−1 and a mean absolute percentage error of 40.7%, and it yielded generally reasonable spatial and temporal distributions of AC in the BS and YS. The satellite-derived AC using our algorithm may offer useful information for modeling the inherent optical properties of suspended particles, deriving the water transparency, estimating the particle composition and possibly improving particle mass concentration estimations in future. View Full-Text
Keywords: particle cross-sectional area; remote sensing; retrieval model; the Bohai Sea and Yellow Sea; Geostationary Ocean Color Imager (GOCI) particle cross-sectional area; remote sensing; retrieval model; the Bohai Sea and Yellow Sea; Geostationary Ocean Color Imager (GOCI)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, S.; Huan, Y.; Qiu, Z.; Sun, D.; Zhang, H.; Zheng, L.; Xiao, C. Remote Sensing of Particle Cross-Sectional Area in the Bohai Sea and Yellow Sea: Algorithm Development and Application Implications. Remote Sens. 2016, 8, 841.

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