天绘一号03星定位精度初步评估

天绘一号卫星是我国第一颗传输型立体测绘卫星,主要用于无地面控制点条件下高精度定位及1∶5万比例尺地形图测绘。01、02星分别于2010年8月24日及2012年5月6日成功发射,03星于2015年11月26日发射,目前3颗星在轨正常运行。01星定位精度经过系统检测后,定位精度为10.3 m/5.7 m(平面/高程),02星定位精度与01星精度相当。本文首先简要介绍了天绘一号卫星的总体概况及其地面处理系统中的关键技术,重点对03星的无控定位精度进行初步试验评估。通过国内外3条航线的试验发现,03星较02星精度有较大提高,在无地面控制点条件下可实现平面7.2 m、高程2.6 m的定位精度。     

径向基神经网络在沉降预测中的应用

针对大型建筑物的沉降监测存在较多的不等时间间隔沉降监测数据,现有模型需要对此类数据进行等间隔处理后建立沉降预测模型的现状,该文采用无需对监测数据进行等间隔预处理的径向基神经网络对沉降监测数据建立沉降预测。通过对西安某大厦基坑开挖对地表和周围建筑物影响的沉降监测数据进行实例分析,并与非等间隔灰色GM(1,1)预测模型进行对比,利用模型评价指标评价预测模型精度。结果表明:采用径向基神经网络建立预测模型处理过程简便,其预测精度优于非等间隔灰色GM(1,1)预测模型。     

Wave-induced seabed response analysis by radial point interpolation meshless method

Wave-induced transient response of seabeds is numerically analyzed through a radial point interpolation meshless method (radial PIM). The Biot’s consolidation theory is employed and incorporated with virtual boundary conditions to describe this wave-induced transient response of the seabed. Displacement and pore water pressure are spatially discretized by the radial PIM with the same shape function. Compactly supported basis functions are proposed to obtain a banded system equation. Because the radial PIM passes through all nodal points within an influence domain, essential boundary conditions as well as virtual boundary conditions can be easily implemented at local level. Fully implicit integration scheme is used in time domain to avoid spurious ripple effect. The proposed algorithm is assessed through the comparison of numerical results with closed-form solution or finite element solutions.     

莱洲湾沿岸浅层地下卤水蒸发成因新依据

山东莱洲湾沿岸是我国重要的天然卤水矿产地,分布广、浓度高、储量大,关于其成因通过近几十年来的研究可归纳为蒸发浓缩生卤和冰冻生卤2种,但其依据尚不够丰富。该文从海水冰冻实验与蒸发实验所经历的路径中,Na/Cl与Ca/Mg随浓缩倍数的变化趋势来分析卤水的成因,认为其应属蒸发浓缩生卤。     

基于紧支径向基函数的点插值无网格方法

紧支径向基函数能使支配方程中的刚度矩阵具有稀疏性,很适合应用于无网格方法中,其缺点是在插值计算时精度不高.点插值方法的插值函数具有Delta函数性质,可以很方便的施加本质边界条件,但在计算插值函数时矩阵易出现奇异.为了提高计算精度并避免点插值法的局限性,首先对紧支径向基函数进行完备性修正,然后用完备性修正的紧支径向基函数代替多项式来形成插值函数,建立了紧支径向基函数点插值方法.由于该方法中的形函数满足Delta函数性质,因此本质边界条件可以像传统的有限元方法一样很容易施加.然后将该方法用于二维弹性静力问题的求解,导出了其相应的离散方程.最后将该方法应用于一个悬臂梁的分析中,初步验证了该方法的有效性与合理性.     

The application of commutative algebra to geodesy: two examples

Algebra, in particular commutative algebra, is applied here to provide a general unified solution to nonlinear systems of equations encountered in geodesy. Starting with the “Abelian group”, the “polynomial ring” is defined and used to form generators of ideals. By applying Buchberger or polynomial resultant algorithms, these generators are reduced to simple structures often comprising a univariate polynomial in one of the unknowns. The advantage of the proposed unified approach is that it provides exact solutions to geodetic nonlinear systems of equations without the traditional requirements of linearization, iterations or approximate starting values. The commutative algebraic approach therefore alleviates the need for isolated exact solutions to various geodetic nonlinear systems of equations. The procedure is applied to GPS meteorology to compute refraction angles, and Helmert’s one-to-one mapping of topographical points onto the reference ellipsoid.     

A New Type of Neural Network For Reservoir Identification Using Geophysical Well Logs

We have developed a neural network algorithm of radial basis network (RBN) type for geoscience applications. This new probabilistic neural network (PNN), referred to as “gravity-capturing neural network,” employs multidimensional even distance and introduces the resultant force competition mechanism for the output layer. When used for geological pattern recognition with well-logging data, it avoids misjudgment due to a magnitude jump of a single parameter and can extract complex and hidden formulas from laboratory and field measurements more efficiently. A field case study of reservoir identification with geophysical well logs is presented to demonstrate the advantages of this neural network over the conventional PNN in such classification applications.     

Latent Compositional Factors in The Llobregat River Basin (Spain) Hydrogeochemistry

The study of hydrogeochemical data sets frequently calls for statistical dimension reducing techniques. It is well known that hydrochemical parameters are compositions and, for this type of data, the direct application of classical statistical methods based on the correlation matrix yield spurious results. But new results on compositional data analysis have identified the sampling space, the simplex, with an Euclidean space, a fact that allows us to define a simplicial factor analysis strategy, thus overcoming the problem. For illustration, we use samples from the Llobregat River and its tributaries (NE Spain). Three unobservable or latent factorial components are extracted, which are identified with pristine waters, potash-mining influence and urban sewage influence. These three factorial components or compositional factors are plotted in a factorial ternary diagram, which reflects the relative influence of each one of these factors on each observation.     

Geostatistics Analyst中空间内插方法的介绍

主流GIS软件ArcGIS 9的Geostatistics Analyst模块中所涉及的两大类空间内插方法:确 定性内插方法和地统计内插方法。结合该软件对各种插值方法的应用和处理进行了介绍,应用示例 比较各种内插方法的适用范围。     

基于RBF神经网络的遥感影像分类器设计

设计了一种运用径向基函数神经网络进行遥感影像分类的监督分类器,以实际的遥感光谱影像分类为例,将分类效果同传统的最小欧氏距离法分类进行比较,探讨了RBF分类的优越性,结果表明RBF神经网络是一种更为有效的图像分类器。