空间分析中几种插值方法的比较研究

针对常用的空间插值方法在精度分析方面比较的不足,从地质统计学、数学函数和几何方法方面分别选取普通克里金插值法、三次样条函数法和距离权重倒数法进行插值精度的比较与分析。文章分析了各个方法的优缺点和局限性,选取疏密差异较大的均匀和不均匀离散点数据进行实验,利用三次趋势面模型和MATLAB,ArcGIS,GS+Version...     

局部最优形态参数的RBF分块地形插值方法与实验

径向基函数（Radial Basis Function,RBF）是一种不需对数据做任何假设,能准确逼近任意维度数据的空间插值方法。其特别适合于复杂地形的数字高程模型（Digital Elevation Model,DEM）插值重建,但随着已知点数量的增加会导致插值模型求解困难或缓慢。针对这个问题,本文基于二叉树自适应递归分块原理,采用局部最优形态参数的RBF分块插值方法进行DEM插值重建。首先,设定子区域最小点数阈值和相邻子区域的重叠率,自顶向下,对研究区域进行递归分块,构建区域分块二叉树,对二叉树叶子节点区域,采用逐点交叉验证（Leave One Out Cross Validation,LOOCV）方法求解其最优形态参数,建立局部RBF最优插值模型;然后,根据单元分解原理,采用加权平均方法对相应叶子节点区域内的待插值点高程进行加权求和,自底向上递归求解,得到待插值点最终高程值。以云南某地区DEM进行插值实验表明,采用本文方法进行DEM插值重建,稳定性较好,插值精度高。     

不排水不可压缩条件下两相介质的两重网格算法

对于不排水、不可压缩饱和软土地基的固结问题的有限元分析,可以用Biot固结方程来考虑土体颗粒与孔隙水间的相互作用。由于受Babuska-Brezzi稳定条件的限制,用常规的等插值u-p混合有限元法求解将导致孔隙压力出现紊乱的结果。提出了基于位移和压力线性等插值函数的两重网格,但位移独立变量总数大于独立压力变量总数的计算方法,可以满足Babuska-Brezzi稳定条件,使得位移场和压力场单元插值阶数保持一致。通过几个简单算例验证了提出方法的正确性。     

基于双线性内插值的CD雷达垂直剖面算法

该文针对贵州CD型号新一代多普勒天气雷达反射率因子,采用C#编程,经坐标转换后处理成三维网格数据,基于双线性内插值法,实现任意方向雷达反射率因子垂直剖面制作,结合贵阳雷达分析,结果表明双线性内插值法放大后的图像质量较高,解决了因垂直剖面图像较小不利于显示及放大的问题。     

When do we need a trend model in kriging?

Under usual estimation practice with local search windows for data and for interpolation situations, universal kriging and ordinary kriging yield the same estimates, using a data set with apparent trend, for both the unknown attribute and its trend component. Modeling the trend matters only in extrapolation situations. Because conditions of the case study presented arise most frequently in practice, the simpler ordinary kriging is the preferred option.     

Fractal reconstruction of sea-floor topography

Sea-floor bathymetric profiles exhibit features at many different scales of length; this suggests that they could be described as fractals. An algorithm interpolating a fractal line between points has been used to reconstruct bathymetric profiles from a few data points. In general, this fractal line has the same Fourier amplitude spectrum as real bathymetry, and, if the parameters of the interpolation are suitably chosen, it has a very similar appearance. The success of this fractal reconstruction algorithm for the sea-floor raises the possibility that it could be used to extrapolate, from data collected at one scale, the properties of the sea-floor at finer scales, and that similar techniques could be used to interpolate a surface between bathymetric profiles. The fractal character is a sign that the processes that shape the sea-floor are scale invariant and suggests that the renormalization group technique could be used to model these processes.     

Uncertainty in Coal Property Valuation in West Virginia: A Case Study

Interpolated grids of coal bed thickness are being considered for use in a proposed method for taxation of coal in the state of West Virginia (United States). To assess the origin and magnitude of possible inaccuracies in calculated coal tonnage, we used conditional simulation to generate equiprobable realizations of net coal thickness for two coals on a 7 min topographic quadrangle, and a third coal in a second quadrangle. Coals differed in average thickness and proportion of original coal that had been removed by erosion; all three coals crop out in the study area. Coal tonnage was calculated for each realization and for each interpolated grid for actual and artificial property parcels, and differences were summarized as graphs of percent difference between tonnage calculated from the grid and average tonnage from simulations. Coal in individual parcels was considered minable for valuation purposes if average thickness in each parcel exceeded 30 inches. Results of this study show that over 75% of the parcels are classified correctly as minable or unminable based on interpolation grids of coal bed thickness. Although between 80 and 90% of the tonnages differ by less than 20% between interpolated values and simulated values, a nonlinear conditional bias might exist in estimation of coal tonnage from interpolated thickness, such that tonnage is underestimated where coal is thin, and overestimated where coal is thick. The largest percent differences occur for parcels that are small in area, although because of the small quantities of coal in question, bias is small on an absolute scale for these parcels. For a given parcel size, maximum apparent overestimation of coal tonnage occurs in parcels with an average coal bed thickness near the minable cutoff of 30 in. Conditional bias in tonnage for parcels having a coal thickness exceeding the cutoff by 10 in. or more is constant for two of the three coals studied, and increases slightly with average thickness for the third coal.     

弹道扰动引力的有限元逼近算法

为了克服多项式逼近弹道扰动引力的缺点，根据有限元插值的原理，采用了对弹道周围空间区域进行有限元剖分的方法，利用剖分单元各顶点的扰动引力分量内插出弹道点对应的扰动引力分量值。结果表明，文中提出的逼近算法能够快速精确可靠地逼近弹道扰动引力，是一种具有应用价值的方法。     

由直线和曲线混合组成的地形符号在DCS中的处理

在ＤＣＳ输出的地籍图上，有许多由直线段和曲线段组成的地物符号，用传统方法处理难以取得理想的绘图效果。本文在分析ＤＣＳ数据结构和属性码的基础上，提出了曲线部分按三次参数样条曲线逼近，讨论了直线段和曲线段的各种组合情况，并且通过正确地选择边值条件使二者之间．的连接比较符合实际。最后扼要分析了该类线段按虚线绘出时的处理方法。     

Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique

ABSTRACT

The reliable and robust monitoring of air temperature distribution is essential for urban thermal environmental analysis. In this study, a stacking ensemble model consisting of multi-linear regression (MLR), support vector regression (SVR), and random forest (RF) optimized by the SVR is proposed to interpolate the daily maximum air temperature (T_max) during summertime in a mega urban area. A total of 10 geographic variables, including the clear-sky averaged land surface temperature and the normalized difference vegetation index, were used as input variables. The stacking model was compared to Cokriging, three individual data-driven methods, and a simple average ensemble model, all through leave-one-station-out cross validation. The stacking model showed the best performance by improving the generalizability of the individual models and mitigating the sensitivity to the extreme daily T_max. This study demonstrates that the stacking ensemble method can improve the accuracy of spatial interpolation of environmental variables in various research fields.