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Title: Assessment of total suspended sediment distribution under varying tidal conditions in Deep Bay : initial results from HJ-1A/1B satellite CCD images
Authors: Tian, L
Wai, OWH 
Chen, X
Liu, Y
Feng, L
Li, J
Huang, J
Keywords: Atmospheric correction
Ocean color
Remote sensing
Total suspended sediment
Issue Date: 2014
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Remote sensing, 2014, v. 6, no. 10, p. 9911-9929 How to cite?
Journal: Remote sensing 
Abstract: Using Deep Bay in China as an example, an effective method for the retrieval of total suspended sediment (TSS) concentration using HJ-1A/1B satellite images is proposed. The factors driving the variation of the TSS spatial distribution are also discussed. Two field surveys, conducted on August 29 and October 26, 2012, showed that there was a strong linear relationship (R2 = 0.9623) between field-surveyed OBS (optical backscatter) measurements (5-31NTU) and laboratory-analyzed TSS concentrations (9.89-35.58 mg/L). The COST image-based atmospheric correction procedure and the pseudo-invariant features (PIF) method were combined to remove the atmospheric effects from the total radiance measurements obtained with different CCDs onboard the HJ-1A/1B satellites. Then, a simple and practical retrieval model was established based on the relationship between the satellite-corrected reflectance band ratio of band 3 and band 2 (Rrs3/Rrs2) and in-situ TSS measurements. The R2 of the regression relationship was 0.807, and the mean relative error (MRE) was 12.78%, as determined through in-situ data validation. Finally, the influences of tide cycles, wind factors (direction and speed) and other factors on the variation of the TSS spatial pattern observed from HJ-1A/1B satellite images from September through November of 2008 are discussed. The results show that HJ-1A/1B satellite CCD images can be used to estimate TSS concentrations under different tides in the study area over synoptic scales without using simultaneous in-situ atmospheric parameters and spectrum data. These findings provide strong informational support for numerical simulation studies on the combined influence of tide cycles and other associated hydrologic elements in Deep Bay.
EISSN: 2072-4292
DOI: 10.3390/rs6109911
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