The study on a surface sediment classification methocl by weakening moisture influence in intertidal zone using remote sensing

LI Huan; ZHANG Dong; ZHANG Ying

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LI Huan, ZHANG Dong, ZHANG Ying. The study on a surface sediment classification methocl by weakening moisture influence in intertidal zone using remote sensing[J]. Haiyang Xuebao, 2012, 34(6): 84-93.

Citation:

LI Huan, ZHANG Dong, ZHANG Ying. The study on a surface sediment classification methocl by weakening moisture influence in intertidal zone using remote sensing[J]. Haiyang Xuebao, 2012, 34(6): 84-93.

LI Huan, ZHANG Dong, ZHANG Ying. The study on a surface sediment classification methocl by weakening moisture influence in intertidal zone using remote sensing[J]. Haiyang Xuebao, 2012, 34(6): 84-93.

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The study on a surface sediment classification methocl by weakening moisture influence in intertidal zone using remote sensing

1.
School of Geographic Science, Nanjing Normal University, Nanjing 210046, China;School of Geography, Geology and Environmental Science, University of Auckland, Auckland 1010, New Zealand
2.
School of Geographic Science, Nanjing Normal University, Nanjing 210046, China

Received Date: 2011-09-02
Rev Recd Date: 2012-03-20

Abstract

Abstract

The spectral signal of sediment on intertidal flats is easily concealed as the result of high moisture inside,which is the main obstacle for retrieving sediment types by means of remote sensing technology.To improve the accuracy of quantifying sediment characteristics,the effects of varying moisture must be removed.With the use of in situ samples of sediment collected in Dafeng,Jiangsu Province,China and its spectra measured under different moisture conditions in the laboratory,a linear spectral unmixing technology is employed to obtain moisture abundance and analyze the spectral response of sediment to varied moisture content.The moisture content layer of study area retrieved by a linear regression techniology on Hyperion image is introduced as variable into multiple variable linear regression equations.The models,which can eliminate the moisture impact,are constructed and applied in Hyperion image to retrieve components'(sand,silt and clay) spatial distribution.Retrieved components are input to Shepard classification system to map the sediment types of intertidal flats automatically.The results are shown as below:(1)the spectral contribution from water is dominant while the moisture content is higher than 25% and its value increases two times with the rate of moisture content increasing;(2) the reflectance of samples in 2 143 nm is sensitive to the variation of moisture,and square (r²) of correlation coefficient of constructed moisture model is 0.81;(3)the reflectance of samples in 983 and 1 134 nm is sensitive to the content of each component,these two bands combined moisture sensitive band are utilized to construct the multiple variable linear regression equation,which can effectively remove the moisture impact on wet samples;(4)the overall classification accuracy is 75.93%,and Kappa coefficient reaches 0.60.This method is an effective way to map the spatial distribution characteristic of sediment types accurately on muddy intertidal flats.
- sediment classification,
- intertidal flats,
- hyperspectral remote sensing,
- moisture content

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References(21)

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