In:
Applied Optics, Optica Publishing Group, Vol. 62, No. 8 ( 2023-03-10), p. 2017-
Abstract:
As a significant and cost-effective method of obtaining shallow seabed
topography, satellite derived bathymetry (SDB) can acquire a wide range of shallow sea depth by integrating a small quantity of in-situ water depth data. This method is a
beneficial addition to traditional bathymetric topography. The seafloor’s spatial heterogeneity leads to inaccuracies in
bathymetric inversion, which reduces bathymetric accuracy. By utilizing multispectral data with multidimensional features, an SDB
approach incorporating spectral and spatial information of multispectral images is proposed in this study. In order to
effectively increase the accuracy of bathymetry inversion throughout the entire area, first the random forest with spatial coordinates is
established to control bathymetry spatial variation on a large scale. Next, the Kriging algorithm is used to interpolate bathymetry
residuals, and the interpolation results are used to adjust bathymetry spatial variation on a small scale. The data from three shallow water
sites are experimentally processed to validate the method. Compared with other established bathymetric inversion techniques, the
experimental results show that the method effectively reduces the error in bathymetry estimation caused by spatial heterogeneity of the
seabed, producing high-precision inversion bathymetry with a root mean square error of 0.78 to 1.36 meters.
Type of Medium:
Online Resource
ISSN:
1559-128X
,
2155-3165
Language:
English
Publisher:
Optica Publishing Group
Publication Date:
2023
detail.hit.zdb_id:
207387-0
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