A study on the quantitative remote sensing model for the sediment concentration in estuary

LI Si-hai; TANG Jun-wu; YUN Cai-xing

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LI Si-hai, TANG Jun-wu, YUN Cai-xing. A study on the quantitative remote sensing model for the sediment concentration in estuary[J]. Haiyang Xuebao, 2002, 24(2): 51-58.

Citation:

LI Si-hai, TANG Jun-wu, YUN Cai-xing. A study on the quantitative remote sensing model for the sediment concentration in estuary[J]. Haiyang Xuebao, 2002, 24(2): 51-58.

LI Si-hai, TANG Jun-wu, YUN Cai-xing. A study on the quantitative remote sensing model for the sediment concentration in estuary[J]. Haiyang Xuebao, 2002, 24(2): 51-58.

Citation:

LI Si-hai, TANG Jun-wu, YUN Cai-xing. A study on the quantitative remote sensing model for the sediment concentration in estuary[J]. Haiyang Xuebao, 2002, 24(2): 51-58.

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A study on the quantitative remote sensing model for the sediment concentration in estuary

1.
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China;National Marine Data and In formation Service, Tianjin 300171, China
2.
National Satellite Marine Application Center, Beijing 100081, China
3.
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China

Received Date: 2000-07-02
Rev Recd Date: 2000-10-08

Abstract

Abstract

According to the Seastar/Sea WiFS remote sensing data and in-situ sediment concentration data acquired quasi-synchronously,the quantitative remote sensing model for suspended sediment in the Changjiang Estuary is set up.The primary Sea WiFS data are geolocated by the "exact closed-form" algorithm,and atmospherically corrected with the simplified procedures for the atmosphere transference computation,so the surface reflectance is got.After these,the remote sensing parameter,which shows the typical spectral features for sediment concentration,is obtained,and is correlated with the in-situ sediment concentration.Finally,the quantitative remote sensing model is got for sediment concentration.
- Sea WiFS,
- geolocation,
- atmosphere correction,
- sediment remote sensing

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References(14)

References

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