Intersatellite comparisons and evaluations of three ocean color products along the Zhejiang coast, eastern China

Cui, Qiyuan; Wang, Difeng; Gong, Fang; Pan, Delu; Hao, Zengzhou; Wang, Tianyu; Zhu, Qiankun

doi:10.1117/12.2278041

Cited by 1 publication

(1 citation statement)

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“…For example, Gao et al [11] validated their sediment model for JZB using the GOCI TSS product without paying attention to potential bridge contamination. Hangzhou Bay Bridge was also not considered in a GOCI-based assessment of the diurnal variation in chl-a and TSS [12], nor in mapping the suspended particulate matter [13].…”

Section: Introductionmentioning

confidence: 99%

Impact of Coastal Infrastructure on Ocean Colour Remote Sensing: A Case Study in Jiaozhou Bay, China

2019

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Spatial and temporal ocean colour data are increasingly accessible through remote sensing, which is a key tool for evaluating coastal biogeochemical and physical processes, and for monitoring water quality. Coastal infrastructure such as cross-sea bridges may impact ocean colour remote sensing due to the different spectral characteristics of asphalt and the seawater surface. However, this potential impact is typically ignored during data post-processing. In this study, we use Jiaozhou Bay (East China) and its cross-bay bridge to examine the impact of coastal infrastructure on water-quality remote-sensing products, in particular on chlorophyll-a concentration and total suspended sediment. The values of these products in the bridge area were significantly different to those in the adjacent water. Analysis of the remote-sensing reflectance and application of the Normalised Difference Water Index demonstrate that this phenomenon is caused by contamination of the signal by bridge pixels. The Moderate Resolution Imaging Spectroradiometer (MODIS) products helped estimate the pixel scale that could be influenced by contamination. Furthermore, we found similar pixel contamination at Hangzhou Bay Bridge, suggesting that the impact of large coastal infrastructure on ocean colour data is common, and must therefore be considered in data post-processing.

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Section: Introductionmentioning

confidence: 99%