Stochastic modeling of seafloor morphology: A parameterized Gaussian model
Stochastic modeling of seafloor morphology: A parameterized Gaussian model
复制标题
海底形态的随机建模：参数化高斯模型
DOI：
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发表时间：
1989
期刊：
影响因子：
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通讯作者：
T. Jordan
中科院分区：
文献类型：
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作者：
J. Goff;T. Jordan
随机分析方法对于量化诸如深海丘陵等小尺度测深特征的总体特性是有用的。在本文中，我们将海底模拟为一个平稳的、零均值的高斯随机场，完全由其自协方差函数来描述。我们构造了一个各向异性自协方差函数，它有5个自由参数，描述了海底地形的幅度、各向异性方向和纵横比、特征长度和Hausdorff(分维)。通过对海束数据的反演从各个海底区域估计的参数表明，在该模型的约束范围内，海底呈现出广泛的随机特征。利用傅立叶方法，可以从高斯模型生成任意尺度和分辨率的合成地形。这些合成物的彩色图像有助于说明该模型的随机行为。
Stochastic methods of analysis are useful for quantifying ensemble properties of small-scale bathymetric features such as abyssal hills. In this paper we model the seafloor as a stationary, zero-mean, Gaussian random field completely specified by its autocovariance function. We formulate an anisotropic autocovariance function that has five free parameters describing the amplitude, anisotropic orientation and aspect ratio, characteristic length, and Hausdorff (fractal) dimension of seafloor topography. Parameters estimated from various seafloor regions by an inversion of Sea Beam data indicate that the seafloor exhibits a wide range of stochastic characteristics within the constraints of the model. Synthetic topography can be generated at arbitrary scale and resolution from the Gaussian model using a Fourier method. Color images of these synthetics are useful for illustrating the stochastic behavior of the model.