利用GPS水准点精化局部CQG2000

CQG2000模型的精度仍不能满足中、大比例尺的测图需要,如何充分利用现有成果,提高其价值和实用性,是目前需要迫切解决的问题。本文提出了通过加密GPS水准点来提高现有CQG2000精度的方法,并研究了GPS水准点数目和分布对提高结果的影响。     

基于最小二乘配置的三维空间坐标转换

在求解未知转换参数时,鉴于公共点坐标本身的误差,提出利用最小二乘配置法进行空间坐标转换,即将公共点本身坐标作为随机参数,把转换参数作为非随机参数进行处理,最后通过实验对比分析表明,该方法明显优于一般坐标转换方法。     

抗差最小二乘配置在数字化地图几何纠正中的应用讨论

抗差估计具有较好的抗拒异常观测值及粗差的能力,而最小二乘配置又能较好地处理系统误差,本文结合两者的优点,利用抗差最小二乘配置对数字化地图进行几何纠正,其中对协方差函数采用抗差拟合,得到了较好的结果。实验证明在GIS数据处理的扫描数字化地图几何纠正中,抗差最小二乘配置在抗拒异常值和处理系统误差方面优于单纯的最小二乘估计和单纯的最小二乘配置方法。     

Recent advances in (soil moisture) triple collocation analysis

To date, triple collocation (TC) analysis is one of the most important methods for the global-scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method. Different notations that are used to formulate the TC problem are shown to be mathematically identical. While many studies have investigated issues related to possible violations of the underlying assumptions, only few TC modifications have been proposed to mitigate the impact of these violations. Moreover, assumptions, which are often understood as a limitation that is unique to TC analysis are shown to be common also to other conventional performance metrics. Noteworthy advances in TC analysis have been made in the way error estimates are being presented by moving from the investigation of absolute error variance estimates to the investigation of signal-to-noise ratio (SNR) metrics. Here we review existing error presentations and propose the combined investigation of the SNR (expressed in logarithmic units), the unscaled error variances, and the soil moisture sensitivities of the data sets as an optimal strategy for the evaluation of remotely-sensed soil moisture data sets.     

配置法在局部大地水准面精化中的实例研究

从最小二乘配置方法的基本原理出发,以我国某地区范围内1km分辨率的大地水准面高模型数据为例,根据实用公式计算了试验区大地水准面高的协方差值后,采用多项式函数模型和高斯函数模型分别拟合了该地区大地水准面高的局部协方差函数,并对试验区内18个检核点做了推估计算。根据推估值(Nfit)与实测值(NGPSL)的比较分析表明,虽然多项式协方差函数模型略优于高斯协方差函数模型,但它们都能以厘米级的精度拟合局部大地水准面,这表明了配置法用于精化厘米级大地水准面的有效性。     

二次曲面与最小二乘配置的组合模型在GPS高程异常拟合中的应用

在工程实践应用中,为了有效利用GPS高程数据,减少对传统水准测量的依赖,提高GPS高程异常的拟合精度便显得十分重要。为此,本文在介绍二次曲面拟合和最小二乘配置拟合基本原理分析、算法过程推导的基础上,提出了一种新的高程异常拟合方法。首先在二次曲面拟合的基础上,计算得到原始观测数据与拟合数据之间的残差序列,然后采用最小二乘配置模型对包括二次曲面拟合模型误差的综合误差进行优化减弱,最后得到新的高程异常。通过实例,将二次曲面拟合法,最小二乘配置法与文中提出的新方法进行比较分析。结果表明：新的组合方法的拟合预测精度要明显优于最小二乘配置及二次曲面拟合。     

Local Oceanic Vertical Deflection Determination with Gravity Data Along a Profile

Deflections of the vertical (DOVs) over oceans cannot be directly measured, which restricts their applications. A local covariance function of anomalous potential is put forward in this paper in conjunction with the least-squares collocation (LSC) method to compute the oceanic DOVs utilization of oceanic gravity data along a profile. The covariance functions of gravity field quantities have been derived directly as functions of x, y and z without the need to introduce coordinate transformations corresponding to along- or cross-profile components. In the proposed methodology, gravity data along a profile were used to calculate the residual gravity anomaly using the remove-compute-restore technique. The residual gravity anomaly was used to calculate the parameters of the proposed covariance function of the local anomalous gravity field, which was used in the LSC to compute the residual DOVs along the profile. The residual DOVs added model DOVs to recover the DOVs along the profile. The results of a simulation experiment prove that the proposed methodology is feasible and effective.     

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

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.     

Mapping and initial dilution estimation of an ocean outfall plume using an autonomous underwater vehicle

A monitoring mission to study the shape and estimate initial dilution of the S. Jacinto outfall plume using an autonomous underwater vehicle (AUV) was performed on July 30, 2002. In order to reduce the uncertainty about plume location and to concentrate the vehicle mission only in the hydrodynamic mixing zone, outputs of a near-field prediction model, based on effective real-time in situ measurements of current speed and direction and density stratification, were opportunistically used to specify in real time the mission transects. The surface characteristics of the outfall plume were found to be influenced strongly by the relatively weak stratification and low current velocities. Dilution was estimated using a temperature–salinity (TS-) diagram with initial mixing lines between wastewater and ambient waters. Effluent dilutions were at least 30:1 in this study. In order to efficiently map the plume dispersion we applied the least-squares collocation method technique. Our results demonstrate that AUVs can provide high-quality measurements of physical properties of effluent plumes in a quite effective manner and valuable considerations about the initial mixing processes under real oceanic conditions can be further investigated.