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Proceedings Paper

Study on the quantitative model of suspended sediment from MODIS in the Yangtze River
Author(s): Hai-lin Zhang; Can-de Liu; Bao-yin He; Mao-tian Li; Yie Yi
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Paper Abstract

Remote sensing techniques are used widely to observe bodies of water. Among satellite sensors commonly used for water quality studies, the Moderate-resolution Imaging Spectroradiometer (MODIS) has potential in water quality monitoring, because of moderate spatial resolution and high temporal resolution. In this paper, the utility of MODIS satellite imagery for suspended sediment monitoring in the estuary and the middle Yangtze River is investigated. Using the Yangtze estuary, China as an example, we explored the potential for using MODIS 250 m bands for suspended sediment study. It is shown that suspended sediment concentration correlates well with reflectance values retrieved from MODIS 250 m image data (R2=0.85, n=25). In the middle Yangtze River, It is concluded that suspended sediment concentration correlates well with reflectance values (R1-R2)/(R1+R2) retrieved from MODIS 250m image data (R2=0.72, n=41). Based on this correlation, we obtain the empirical model of suspended sediment concentration in the middle Yangtze River from MODIS. It is shown that it is useful for MODIS data to monitor this parameter of water quality.

Paper Details

Date Published: 3 November 2008
PDF: 9 pages
Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 71451Z (3 November 2008); doi: 10.1117/12.813053
Show Author Affiliations
Hai-lin Zhang, Central China Normal Univ. (China)
Can-de Liu, Institute of Geodesy and Geophysics (China)
Bao-yin He, Institute of Geodesy and Geophysics (China)
Mao-tian Li, East China Normal Univ. (China)
Yie Yi, Central China Normal Univ. (China)


Published in SPIE Proceedings Vol. 7145:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Yong Lao, Editor(s)

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