Mr. Xiangcheng Wang Profile

Xiangcheng Wang

at Nanjing Univ

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Proceedings Article | 26 July 2007 Paper

Hyperspectral models of coastal water depth extraction

Jingjing Wang, Qingjiu Tian, Wenxue Fu, Xiangcheng Wang, Xindong Du

Proceedings Volume 6752, 675219 (2007) https://doi.org/10.1117/12.760681

KEYWORDS: Reflectivity, Algorithm development, Water, Remote sensing, Signal attenuation, Near infrared, Coastal modeling, Solids, Atmospheric particles, Error analysis

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The theoretical basis of water depth retrieval by optical remote sensing was analyzed based on radiation transfer process of light wave in water. After a summary of water depth retrieval methods of the predecessors, derivative spectra method for water depth retrieval was introduced. Water reflective spectra were collected using ASD field spectroradiometer, and water depths were measured by a digital echo sounding system simultaneously at radial sandy ridges in Southern Huanghai Sea of China. The turbidity was inhomogeneous in the test area and scattered signal from material in the water was also different in spatial distribution. The reflectance of near infrared band (760~900nm) was most sensitive to water depth(R = -0.73). As simulated in TM band settings, the correlation between water depth and reflectance ratio between TM4 and TM1 is better than others(R=-0.81). The correlation between water depth and the first derivative of reflectance at 711nm is significant(R=-0.87). The accuracy evaluation of Single band algorithm, Band ratio algorithm and derivative algorithm showed that the accuracy of single band and band ratio algorithms were low for the samples near the shore, which average relative error was more than 30%. The accuracy of derivative algorithm was improved as to the same samples, which average relative error was 17%. The results indicated that derivative spectra method was an effective tool for reducing the error bring by variety of water quality.

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