Affiliation:
1. Ministry of Natural Resources
2. Zhejiang Institute of Surveying and Mapping Science and Technology
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.
Funder
Key Laboratory of Ocean Geomatics,
Ministry of Natural Resources
National Natural Science Foundation of
China
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献