Determination of complexity factor and its relationship with accuracy of representation for DEM terrain

Based on the estimating rule of the normal vector angles between two adjacent terrain units, we use the concept of terrain complexity factor to quantify the terrain complexity of DEM, and then the formula of terrain complexity factor in Raster DEM and TIN DEM is deduced theoretically. In order to make clear how the terrain complexity factor E _CF and the average elevation h affect the accuracy of DEM terrain representation RMSE _Et , the formula of Gauss synthetical surface is applied to simulate several real terrain surfaces, each of which has different terrain complexity. Through the statistical analysis of linear regression in simulation data, the linear equation between accuracy of DEM terrain representation RMSE _Et , terrain complexity factor E _CF and the average elevation h is achieved. A new method is provided to estimate the accuracy of DEM terrain representation RMSE _Et with a certain terrain complexity and it gives convincing theoretical evidence for DEM production and the corresponding error research in the future.     

数字高程模型误差及其评价的问题综述

从数字高程模型(DEM)传递误差、基于中误差的DEM误差模型及其主要问题、DEM误差分布实验和DEM内插误差新认识几个方面分析了当前DEM误差研究的主要进展,用"中误差"讨论DEM传递误差是建立在测量误差传递理论基础之上的,但沿用"中误差"来讨论DEM内插模型逼近误差和DEM整体误差却缺乏理论依据。DEM误差分布的空间相关性实验对DEM中误差评价法所应具备的随机误差性提出质疑,却可以用基于逼近理论的DEM内插模型来解释,说明用逼近误差理论研究DEM内插误差的途径是正确、可行的。     

GIS中直线元内插点精度及对误差带的影响

基于误差传播定律，考虑参数r误差影响，推导了线元内插点的精度计算公式，讨论内插点精度对线元误差带的影响，并对影响的结果进行了分析，得到了一些有益的结论。     

基于双二次插值多项式的DEM传递误差模型

基于函数插值方法,得出了基于不完全双二次插值多项式的规则格网数字高程模型(DEM)的表面表达模型,并推导了相应的传递误差公式.公式表明,不完全双二次多项式的DEM传递误差与双线性多项式的传递误差相同.但由于不完全双二次多项式的DEM表面建模误差低于线性多项式的DEM表面建模误差,因此基于不完全双二次多项式的DEM表面模型具有更高的精度.     

基于双二次插值多项式的DEM传递误差模型

基于函数插值方法,得出了基于不完全双二次插值多项式的规则格网数字高程模型(DEM)的表面表达模型,并推导了相应的传递误差公式。公式表明,不完全双二次多项式的DEM传递误差与双线性多项式的传递误差相同。但由于不完全双二次多项式的DEM表面建模误差低于线性多项式的DEM表面建模误差,因此基于不完全双二次多项式的DEM表面模型具有更高的精度。     

基于多点的规则格网DEM的传递误差分析

论述了利用数量不同的格网数据构建的样条函数DEM模型和Coons曲面DEM模型的传递误差不同,指出同一插值方法的DEM模型随着构建模型所用的格网数据数目的增多,传递误差增大;当格网数据数目同样多时,减弱相邻格网单元上格网数据权重比例,传递误差就会相应地减少。     

规则格网上双方向性插值DEM精度研究

简要介绍双方向性插值方法的原理，并以线性插值和三次插值过程中的误差传播为基础，利用误差传播定律，推导出双方向性插值方法生成的DEM曲面平均高程误差值，并对线性插值和三次插值公式本身的精度进行分析。     

基于Coons曲面的规则格网DEM表面模型

内插是数字高程模型的核心问题。目前的内插模型主要是由离散的格网数据构建的连续曲面,直接以点推面,可能存在较大的地形误差。本文建立的Coons曲面DEM表面模型,首先利用离散的格网数据构造与格网边界相对应的地形剖面曲线的拟合曲线,再基于拟合曲线构建DEM表面模型。实验表明：Coons曲面DEM表面模型是一种高精度的DEM表面模型,其地形模拟误差比直接基于格网数据建立的双线性内插、样条函数内插和移动曲面拟合法的误差都小,实际地形模拟误差与双线性模型相比减少15％-28％,且精度随着构建边界拟合曲线所用格网点的增多而逐渐提高。     

基于二元样条函数的DEM传递误差模型

根据两点数值微分公式建立了基于二元样条函数的规则格网数字高程模型(DEM)的表面表达模型,得出了基于二元样条函数的传递误差公式。公式表明,二元样条函数的DEM传递误差与双线性多项式的传递误差相同。但由于样条函数的DEM表面建模误差低于线性多项式的DEM表面建模误差,因此,基于样条函数的DEM表面模型具有更高的精度。     

基于高精度曲面模型的DEM构建与误差分析

引入地形表达误差(terrain representation error,Etr),选择标准曲面和甘肃省董志塬地区作为研究对象,利用窗口分析法实现Etr的提取;用统计分析法得出Etr随网格分辨率变化的回归方程;根据误差传播定律计算DEM中误差。数值结果表明,该方法能更准确的计算HASM生成的DEM精度;相同的采样数下,HASM较传统方法(IDW,Spline和Kriging)能生成更高精度和分辨率的DEM。在难以获取已知数据的地区,HASM提供了生成相对准确DEM的高效工具。     

插值条件下格网DEM坡度计算模型的噪声误差分析

针对目前DEM（Digital Elevation Model, DEM）数字地形分析的精度评价多数不考虑DEM误差的空间自相关性或仅仅采用经验的自相关性模型问题,本文从DEM插值入手,从理论上推导了插值条件下格网DEM邻域窗口内坡度噪声误差的空间自相关性模型以及坡度精度模型,并选取典型的插值方法和坡度差分算法,从实验角度分析了在顾及和不顾及空间自相关性两种情况下的格网DEM坡度计算模型的噪声精度,实验结果表明：坡度精度受DEM噪声误差的空间自相关性影响较大,并与DEM插值方法和坡度计算模型中的差分算法有关。     

DEM内插算法与精度评定研究

本文分析了DEM数据产品的误差源、内插算法的误差模型,简要介绍了目前DEM数据产品精度评定的指标与方法途径.通过介绍DEM引出了数字高程模型内插方法,比较了各种DEM内插方法,并且分析了模型精度.     

Improving the Elevation Accuracy of Digital Elevation Models: A Comparison of Some Error Detection Procedures

The widespread availability of powerful desktop computers, easy‐to‐use software tools and geographic datasets have raised the quality problem of input data to be a crucial one. Even though accuracy has been a concern in every serious application, there are no general tools for its improvement. Some particular ones exist, however, and some results are presented here for a particular case of quantitative raster data: Digital Elevation Models (DEM). Two procedures designed to detect anomalous values (also named gross errors, outliers or blunders) in DEMs, but valid also for other quantitative raster datasets, were tested. A DEM with elevations varying from 181 to 1044 m derived from SPOT data has been used as a contaminated sample, while a manually derived DEM obtained from aerial photogrammetry was regarded as the ground truth to allow a direct performance comparison for the methods with real errors. It is assumed that a “better” value can be measured or obtained through some methodology once an outlier location is suggested. The options are different depending upon the user (DEM producers might go to the original data and make another reading, while end users might use interpolation). Both choices were considered in this experiment. Preliminary results show that for the available dataset, the accuracy might be improved to some extent with very little effort. Effort is defined here as the percentage of points suggested by the methodology in relation with its total number: thus 100 per cent effort implies that all points have been checked. The method proposed by López (1997) gave poor results, because it has been designed for errors with low spatial autocorrelation (which is not the case here). A modified version was then designed and compared with the method proposed by Felicísimo (1994). The three procedures can be applied both for error detection during DEM generation and by end users, and they might be of use for other quantitative raster data. The choice of the best methodology is different depending on the effort involved. The conclusions have been derived for a photogrammetrically obtained DEM; other production procedures might lead to different results.     

基于随机过程的格网DEM精度场模型

针对目前DEM格网精度从理论上难于统一量化描述问题,提出一种基于随机过程的格网DEM（grid digital elevation model, grid DEM）精度场模型,该模型从随机过程理论入手,借助DEM的统一插值模型,建立了DEM两类误差（噪声误差和逼近误差）的数学表达,并分析了构成DEM误差的各个分量的数学意义。与已有的模型相比,该模型实现了传统DEM两类误差的统一描述,此外,该模型适用任意插值方式生成的格网DEM的精度评价。     

Spatio‐temporal prediction of land surface temperature using semantic kriging

Spatio‐temporal prediction and forecasting of land surface temperature (LST) are relevant. However, several factors limit their usage, such as missing pixels, line drops, and cloud cover in satellite images. Being measured close to the Earth's surface, LST is mainly influenced by the land use/land cover (LULC) distribution of the terrain. This article presents a spatio‐temporal interpolation method which semantically models LULC information for the analysis of LST. The proposed spatio‐temporal semantic kriging (ST‐SemK) approach is presented in two variants: non‐separable ST‐SemK (ST‐SemK_NSep) and separable ST‐SemK (ST‐SemK_Sep). Empirical studies have been carried out with derived Landsat 7 ETM+ satellite images of LST for two spatial regions: Kolkata, India and Dallas, Texas, U.S. It has been observed that semantically enhanced spatio‐temporal modeling by ST‐SemK yields more accurate prediction results than spatio‐temporal ordinary kriging and other existing methods.     

InSAR高程模型及其精度分析

提出了一种改进的InSAR高程模型，建立了高程和干涉相位的直接关系，并对公式推导中一般采用的平行射线近似处理方法所引入的高程误差进行了量化分析。结果表明，对于星载雷达而言，平行射线近似误差不能忽略。给出了近似误差与基线参数的确定性关系及相应的误差传播曲线，有助于误差纠正和重建高精度DEM。另外，基于改进的高程模型，推导出了高程测量误差传播公式，明确了基线长度和方向对测高精度的影响，对合理选择干涉像对具有指导意义。     

数字高程模型精度评价及其问题探讨

分析了数字高程模型（DEM）精度评价中检查点“中误差”法的局限及DEM产品的实际质量问题,提出了采用等高线回放法以逼近误差的概念,以衡量DEM全域出现的最大误差。     

DEM Fusion using a modified k-means clustering algorithm

Digital elevation models (DEMs) are a necessary dataset for modelling the Earth’s surface; however, all DEMs contain error. Researchers can reduce this error using DEM fusion techniques since numerous DEMs can be available for a region. However, the use of a clustering algorithm in DEM fusion has not been previously reported. In this study a new DEM fusion algorithm based on a clustering approach that works on multiple DEMs to exploit consistency in the estimates as indicators of accuracy and precision is presented. The fusion approach includes slope and elevation thresholding, k-means clustering of the elevation estimates at each cell location, as well as filtering and smoothing of the fusion product. Corroboration of the input DEMs, and the products of each step of the fusion algorithm, with a higher accuracy reference DEM enabled a detailed analysis of the effectiveness of the DEM fusion algorithm. The main findings of the research were: the k-means clustering of the elevations reduced the precision which also impacted the overall accuracy of the estimates; the number of final cluster members and the standard deviation of elevations before clustering both had a strong relationship to the error in the k-means estimates.     

An Adaptive Method of Non‐stationary Variogram Modeling for DEM Error Surface Simulation

Geostatistical characterization of local DEM error is usually based on the assumption of a stationary variogram model which requires the mean and variance to be finite and constant in the area under investigation. However, in practice this assumption is appropriate only in a restricted spatial location, where the local experimental variograms vary slowly. Therefore, an adaptive method is developed in this article to model non‐stationary variograms, for which the estimator and the indicator for characterization of spatial variation are a Voronoi map and the standard deviation of mean values displayed in the Voronoi map, respectively. For the adaptive method, the global domain is divided into different meshes with various sizes according to the variability of local variograms. The adaptive method of non‐stationary variogram modeling is applied to simulating error surfaces of a LiDAR derived DEM located in Sichuan province, China. Results indicate that the locally adaptive variogram model is more accurate than the global one for capturing the characterization of spatial variation in DEM errors. The adaptive model can be considered as an alternative approach to modeling non‐stationary variograms for DEM error surface simulation.