不同采样与插值方法的DEM质量分析

通过编程实现数字高程模型DEM数据采集的随机采样、规则采样和成层随机采样的3种算法;再对某一地区的格网大小为30 m×30 m的栅格格式的高程数据进行采样,使用克立金法(Kriging)、样条函数法(Spline)和距离倒数加权法(Inverse Distance Weighted)3种插值方法分别对采样数据进行插值;然后计算出平均高程值之差的绝对值、中误差和单点最大误差.通过分析发现,成层随机采样与距离倒数加权插值组合适合于对高程总体偏差要求较高的应用;规则采样与样条函数插值组合适合于对相对高程要求较高的应用.     

应用样条函数处理GPS共视数据

为克服Vondrak方法平滑GPS共视比对数据的两端效应和缺值点处的插值问题,应用样条函数平滑和插值方法对NTSC和CRL的GPS共视数据进行了分析研究。结果表明:这种方法可解决Vondrak平滑方法的两端效应现象;与CircularT的数据比较,用样条函数平滑数据之后,再进行三次样条插值,缺值点的内符合精度有所提高,整体内符合精度也有所提高。     

三次样条在北斗卫星轨道插值中的应用

本文选用三次样条函数对北斗高轨卫星的轨道数据进行插值计算,结果表明,三次样条函数基本没有龙格现象,但插值模型中含有明显的随机性系统差,因此本文采用附加系统差的最小二乘配置,对三次样条的插值结果进行处理,使精度提高了10倍左右。      

内蒙古地区气温空间插值模拟方法研究

以内蒙古自治区为研究区,采用反距离权重法、样条函数法和普通克里金法对研究区119个气象观测站点的气温数据进行空间插值,结果表明,普通克里金法由于能够最优地描述气温在空间上的连续性变化特征,插值精度最高;反距离权重法插值精度次之,但其模拟结果趋于产生牛眼模式,且结果不能外推;样条函数法由于受到边界效应的影响,插值精度最低。     

基于不同插值方法的PM1污染物浓度研究

随着GIS和计算机技术的不断发展，窄间数据插值应用越来越广，本文基于PM1污染物浓度数据，阐述了反距离加权插值法（IDW），普通克里格插值法（Kriging）和样条函数插值（SPLINE）三种空间插值方法的数学含义，并指山了各自的特点。在IDW插值图像中，在权重不同的情况下，变化比较大的地方出现在采样点属性值变化剧烈和频繁的区域。SPLINE（规则样条）是基于生成具有连续的二阶导数和最小平方曲率的插值方法。Kriging比其他二种方法灵活，参数限制更多。但不管用哪一种插值方法，空间插值不能代替观测数据，在有一定数量的观测数据的基础上，插值结果才会更逼近真实值。     

基于ArcEngine的等雨量线绘制

等雨量线的绘制是济南城市防汛预警决策支持系统中最基本的功能之一。等雨量线的绘制最关键的部分为用已有站点的雨量数据进行空间插值,生成连续的雨量栅格图,再将雨量值相等的点连成等雨量线。本文用ESRI提供的ArcEngine组件实现了反距离加权插值（IDW）、样条函数插值（Spline）、克里金插值（Kriging）3种常用的插值方法,结合济南市现有的31个雨量站点的雨量数据,分别绘制出等雨量线,并比较3种插值方法的插值结果。结果表明：3种插值方法的结果都基本上反映了济南降雨的空间分布规律,而克里金插值的效果最好。     

Akima插值法在测量中的应用

本文简单介绍了Ａｋｉｍａ插值法的原理和计算方法,举例说明了它在测量中的应用,同时与线性内插和三次自然样条函数插值做了简单比较。     

空间插值方法对土壤重金属污染格局识别的影响

针对广东省某地区土壤中采样样品点的重金属污染物砷(As),文章选取统计学中具有代表性的反距离加权(IDW)、样条函数(Spline)、普通克里格(OK)3种空间插值方法,对比分析不同空间插值方法下研究区土壤中As浓度估算精度、污染特征识别和污染格局空间区划的差异。结果表明:3种空间插值方法在研究区土壤As浓度的估算中,IDW表现最佳;3种插值方法所识别的研究区As污染空间分布特征和污染格局均存在差异,但相对于OK法,IDW和Spline两种方法的结果更加相近。研究表明,在基于点状离散数据采用空间插值方法分析区域土壤重金属污染特征的过程中,应首先考虑结合区域数据样本的数量和特征,开展各空间插值方法的精度评价。     

加密不规则三角网模型的关键算法研究

提出存储TIN模型数据的拓扑数据结构，自动搜索插值原始数据的“膨胀算法”以及用于插值的曲面样条函数的数学模型。利用具有优良数学特征的曲面样条函数，可以完成对TIN的加密处理。     

Akima插值法在测量中的应用

本文简单介绍了Akima插值法的原理和计算方法,举例说明了它在测量中的应用,同时与线性内插和三次自然样条函数插值做了简单比较。     

一种矢径最短的抛物线加权平均光滑插值法

本文提出了一种抛物线加权平均曲线光滑插值算法。它满足了一个特殊的要求，即曲线通过全部节点且到弦的垂直距离最短。同时，将张力系数引入该方法中，并给出了包含张力系数的光滑方程。     

基于ArcGIS的降水量空间插值方法研究

目前对降水量空间插值方法的研究很多,针对反距离权重插值、样条函数插值、普通克里金插值在降水量空间插值中的缺陷,提出引入月平均总云量影响因子的协同克里金插值方法。并以内蒙古降水量数据为例进行实验,实验结果表明,引入月平均总云量影响因子的协同克里金插值在精度和拟合度方面得到改善。     

Area-to-point Kriging with inequality-type data

In practical applications of area-to-point spatial interpolation, inequality constraints, such as non-negativity or more general constraints on the maximum and/or minimum attribute value, should be taken into account. The geostatistical framework proposed in this paper deals with the spatial interpolation problem of downscaling areal data under such constraints, while: (1) explicitly accounting for support differences between sample data and unknown values, (2) guaranteeing coherent (mass-preserving) predictions, and (3) providing a measure of reliability (uncertainty) for the resulting predictions. The formal equivalence between Kriging and spline interpolation allows solving constrained area-to-point interpolation problems via quadratic programming (QP) algorithms, after accounting for the support differences between various constraints involved in the problem formulation. In addition, if inequality constraints are enforced on the entire set of points discretizing the study domain, the numerical algorithms for QP problems are applied only to selected locations where the corresponding predictions violate such constraints. The application of the proposed method of area-to-point spatial interpolation with inequality constraints in one and two dimension is demonstrated using realistically simulated data.     

SRTM DEM数据空洞插值填补方法对比分析

SRTM全球数字高程模型数据目前已被广泛应用于多个领域。最新版本的SRTM DEM仍然存在较小的高程空值区域（数据空洞）和模糊区域。文章在模拟某试验区域SRTM DEM数据空洞的基础上,利用线性插值、反距离权插值、二次多项式插值、三次样条插值等DEM插值方法进行了数据空洞的插值填补试验和对比分析,结果表明在丘陵地区和空...     

多面函数拟合法转换GPS高程

对GPS在高程方面的应用现状作了简单的介绍,综述近年来用GPS求定正常高的几种方法,即多项曲线拟合、多项式曲面拟合、多面函数曲面拟合、加权均值法、非参数回归法和高程异常变化梯度法、固定边界三次样条插值法、线性移动拟事法、神经网络法、非格网GPS散点数据考虑地形改正法。对GPS高程测量基本原理和基本方法进行了讨论,提出根据测区的实际情况选择不同的GPS高程转换方法,综合利用GPS点的高差和高程观测值拟合高程异常的方法,利用多面函数来拟合似大地水准面。     

采样点数目对反距离加权插值结果的敏感性分析

为了研究采样点数日对反距离加权插值结果的影响,以面积为2．076×10^5km。的自俄罗斯为研究区域,采用数目逐渐变化的采样点作为实验数据,通过交叉验证方法,得到了采样点数目与插值精度之间的关系。结果表明：随着采样点数日减少,插值误差呈现先缓慢上升后迅速上升再缓慢上升的趋势。就本组数据而言,当采样点逐渐减少到约为总采样点数目的70％左右,插值的质量会发生突变。计算采样点的密度,得出每100km。采0．9-1．3个点（即每76-109km2采集1个点）的情况下,捕值精度变化不大。鉴于研究所得,在实际的生产生活中．可供大区域插值时。采样方案设计参考。     

基于空间可视化的气温插值方法比较

基于GIS的可视化、空间插值和叠加分析功能,以1982年全国684个气温台站观测数据为插值实验样本,探讨可视条件下空间插值几种主要方法的优劣及适用性,通过对年均气温预测精度的对比及陕西省年均气温预测图的分析,得出就效果而言普通克里格空间插值最优、反距离加权法次之而规则样条法相对较差的初步结果。     

土壤重金属的空间插值方法比较分析——以阳谷县为例

空间插值通过采集少量的数据点,利用其中的空间关联,推求该区域内其他位置的属性值。本文以山东省阳谷县土壤重金属Cu采样数据为例进行空间探索性分析,分别采用了反距离权重插值和普通克里金插值两种方法进行空间分布插值模拟。结果表明,针对研究区采样数据,反距离权重插值方法生成的模型平均误差为1.97 mg/kg,总体精度为92%;普通克里金插值模型的平均误差为1.91 mg/kg,总体精度为92.35%,普通克里金插值方法更优。     

A total error-based multiquadric method for surface modeling of digital elevation models

Digital elevation model (DEM) source data are subject to both horizontal and vertical errors owing to improper instrument operation, physical limitations of sensors, and bad weather conditions. These factors may bring a negative effect on some DEM-based applications requiring low levels of positional errors. Although classical smoothing interpolation methods have the ability to handle vertical errors, they are prone to omit horizontal errors. Based on the statistical concept of the total least squares method, a total error-based multiquadric (MQ-T) method is proposed in this paper to reduce the effects of both horizontal and vertical errors in the context of DEM construction. In nature, the classical multiquadric (MQ) method is a vertical error regression procedure, whereas MQ-T is an orthogonal error regression model. Two examples, including a numerical test and a real-world example, are employed in a comparative performance analysis of MQ-T for surface modeling of DEMs. The numerical test indicates that MQ-T performs better than the classical MQ in terms of root mean square error. The real-world example of DEM construction with sample points derived from a total station instrument demonstrates that regardless of the sample interval and DEM resolution, MQ-T is more accurate than classical interpolation methods including inverse distance weighting, ordinary kriging, and Australian National University DEM. Therefore, MQ-T can be considered as an alternative interpolator for surface modeling with sample points subject to both horizontal and vertical errors.     

Combining Metric Aerial Photography and Near‐Infrared Videography to Define Within‐Field Soil Sampling Frameworks

Abstract

This paper investigates the combination of metric aerial photography and near‐infrared (NIR) videography data to improve the design of field‐survey sampling frameworks. Spatial data collection can contribute up to 80% of the cost of deploying a Geographic Information System (GIS) based Decision Support System (DSS). The use of remotely sensed information, field survey using differential Global Positioning System (dGPS) and geostatistical interpolation methods maximises data quality for a given rate of sampling.

Medium‐format colour aerial photography and NIR videography were orthorectified to the national map base and mosaiced using ERDAS Imagine. The green and red layers of the aerial photography were combined with the NIR videography to form a false‐colour composite image. Two sampling strategies were tested. The first stratified sampling on a per field basis, creating four points per hectare, randomly located within each field. The second strategy used the remotely sensed information to identify within‐field variability classes for each field, using red‐green difference or normalised difference vegetation index (NDVI) models. These variability classes were used as a sub‐stratification framework with each class sampled at the same rate of 4 per hectare. For both strategies the sample points were generated within ESRI ArcView and were located in the field using dGPS. Maps of stone content were created using geostatistical methods and validated against samples collected on a 100 metre grid. It was concluded that combining the two image sources to create a within‐field stratification framework improved the precision of the results obtained from field‐survey.