...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Geodesy >Non-stationary covariance function modelling in 2D least-squares collocation
【24h】

Non-stationary covariance function modelling in 2D least-squares collocation

机译：二维最小二乘配置中的非平稳协方差函数建模

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the observed data. However, the assumption that the spatial dependence is constant throughout the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage for dealing with non-stationarity in geodetic data. We then compared stationary and non-stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC.
机译：标准最小二乘搭配（LSC）假设2D平稳性和3D各向同性，并且依赖协方差函数来说明观测数据中的空间依赖性。但是，有时会违反在整个感兴趣区域中空间依赖性恒定的假设。假设平稳的协方差结构可能导致例如山上的重力场过度平滑，而大平原上的平滑度不足。我们从空间统计中引入了针对非平稳协方差结构的核卷积方法，并展示了其在处理大地数据中的非平稳性方面的优势。然后，我们将二维LSC中的平稳和非平稳协方差函数与西澳大利亚达令断层附近重力异常插值的经验示例进行了比较，该场是各向异性且非平稳的。就形式误差和针对插值中未使用的数据的交叉验证而言，具有非平稳协方差函数的结果优于标准LSC，这表明使用非平稳协方差函数可以改善标准（平稳）LSC。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号