Mr. Jianhu Zhao Profile

Jianhu Zhao

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Proceedings Article | 29 December 2008 Paper

Underwater topography acquired by remote sensing based on SOFM

Jianhu Zhao, Fengnian Zhou, Hongmei Zhang, Juanjuan Li

Proceedings Volume 7285, 728544 (2008) https://doi.org/10.1117/12.815000

KEYWORDS: Remote sensing, Water, Reflectivity, Neurons, Associative arrays, Data acquisition, MODIS, Data modeling, Ocean optics, Earth observing sensors

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In large-scope marine investigation, the traditional bathymetric measurement can not meet the requirement of rapid data acquisition with lower cost of financial and material resources, while remote sensing (RS) technology provides a perfect way in the work. RS can not only provide quickly and efficiently the information of underwater topography with respect to the traditional method, but also present corresponding underwater topography with different-period RS images. In this paper, we depict in detail the procedures and some key techniques in acquiring underwater topography by remote sensing inversion technology based on self-organization feature mapping (SOFM). Firstly, we introduce some basic theories about the acquisition of underwater topography by the RS inversion technology. Besides, we discuss the data acquisition and preparation in the work. Moreover, we implement correlation analysis and find out the sensitive bands used for building RS inversion model. In virtue of SOFM, we construct the mapping relation between water depth and the reflectivity of sensitive band in the studied area, and test the it in two experimental water areas. The model achieves satisfying accuracy and can meet the requirement of given bathymetric scale. Finally the mapping relation is used for the water depth inversion in the studied water area. We also use the water depth from the model to draw the underwater topographic map in the water area.

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