Variogram Fitting by Generalized Least Squares Using an Explicit Formula for the Covariance Structure

In the context of spatial statistics, the classical variogram estimator proposed by Matheron can be written as a quadratic form of the observations. If data are Gaussian with constant mean, then the correlation between the classical variogram estimator at two different lags is a function of the spatial design matrix and the variance matrix. When data are independent with unidimensional and regular support, an explicit formula for this correlation is available. The same is true for a multidimensional and regular support as can be shown by using Kronecker products of matrices. As variogram fitting is a crucial stage for correct spatial prediction, it is proposed to use a generalized least squares method with an explicit formula for the covariance structure (GLSE). A good approximation of the covariance structure is achieved by taking account of the explicit formula for the correlation in the independent situation. Simulations are carried out with several types of underlying variograms, as well as with outliers in the data. Results show that this technique (GLSE), combined with a robust estimator of the variogram, improves the fit significantly.     

矢量地理数据密级标识方法研究

密级标识是用于标识信息产品安全等级的隐蔽信息,是信息分级管理、控制与应用的基础和前提。作为涉密地理信息产品主要组织格式的矢量地理数据,其密级标识方法的研究具有重要意义。结合矢量地理数据在遭受几何攻击时,其要素空间关系不变性特征,以及密级标识方法的不可感知性、高鲁棒性要求,本文提出一种基于距离比值调制的矢量地理数据密级标识方法,以实现矢量地理数据的分级管理与保护。其主要研究思路为：① 基于距离比值调制的方法,能够较好地应对几何攻击;② 在每个线面要素内,通过重复嵌入密级标识,有效提高算法对于编辑操作的鲁棒性;③ 运用道格拉斯-普克算法提取特征点,在此基础上进行密级标识的嵌入,能够较好地对抗压缩攻击。实验结果表明：该方法具有良好的不可感知性;同时,对嵌入密级标识后的矢量地理数据进行几何变换、数据编辑、数据压缩等攻击后,其密级标识的提取率能够达到80%以上,表明方法具有较好的鲁棒性。     

具有鲁棒性的彩色图像检索方法

提出了一种鲁棒的图像检索方法，它能够在检索大规模图像库时实现基于内容的快速匹配。匹配的索引来源于重量化HSV颜色空间得到的灰度图（Z值图）的区域特征。由于Z值图由反映色彩的聚类区域组成，并且使用矩方法来表达特征，因此该检索方法是鲁棒的，具有2维平移、尺度、旋转不变性，同时可以避免逐点匹配产生的时间耗费。     

Testing the robustness of the physically-based ECOMAG model with respect to changing conditions

Abstract

The robustness of the physically-based, semi-distributed hydrological model ECOMAG with respect to changing (climatic or land-use) conditions was evaluated for two basins, considered within the modelling workshop held in the frame of the 2013 IAHS conference in Göteborg, Sweden. The first basin, the Garonne River basin, France, is characterized mostly by changes in climatic conditions, while the second, Obyån Creek, Sweden, was exposed to drastic land cover change due to deforestation. Tests were conducted to evaluate the model’s ability to simulate with acceptable accuracy the changing hydrological regime of each basin and to retain, in the process, relatively stable values of the parameters. Acceptable performance of the ECOMAG model was obtained under the different combinations of the calibration/evaluation periods, including, importantly, the periods of hydrological regime changes in both basins.     

Comparing the robustness of ordinary kriging and lognormal kriging: Outlier resistance

Ordinary kriging is well-known to be optimal when the data have a multivariate normal distribution (and if the variogram is known), whereas lognormal kriging presupposes the multivariate lognormality of the data. But in practice, real data never entirely satisfy these assumptions. In this article, the sensitivity of these two kriging estimators to departures from these assumptions and in particular, their resistance to outliers is considered. An outlier effect index designed to assess the effect of a single outlier on both estimators is proposed, which can be extended to other types of estimators. Although lognormal kriging is sensitive to slight variations in the sill of the variogram of the logs (i.e., their variance), it is not influenced by the estimate of the mean of the logs.This paper was presented at MGUS 87 Conference, Redwood City, California, 14 April 1987.     

滑动屋盖摩擦控制系统对地震频谱和结构刚度的鲁棒性

地震功率谱密度函数的频率范围和结构刚度变化对滑动屋盖摩擦控制系统减震效果的影响分析表明 :控制系统减震效果对地震功率谱的频域宽窄不敏感 ,而对功率谱所覆盖的结构自振频率敏感 ;结构刚度发生± 15 %的变化对减震效果的影响不大。分析还表明 ,滑动屋盖摩擦控制系统对于结构非线性地震反应有显著的减震作用     

基于三元组系数的水印算法

提出的水印方案堆于离散小波变换,利用三元组小波系数间的关系而不是单个小波系数来嵌入和提取水印.水印提取时不需要使用原始图像,算法简单,容易实现.实验结果表明该算法对大多数图像处理和攻击具有较好的鲁棒性.     

基于小波变换的矢量地理空间数据数字水印算法

基于矢量地理空间数据自身特点,运用小波变换技术,提出了一种基于小波变换的矢量地理空间数据数字水印算法。即对一系列的线、面坐标串分别进行离散小波分解,把水印信息分段嵌入到相应的小波分解后得到的低频系数中;再进行小波逆变换得到含水印信息的矢量地理空间数据。在水印信息提取过程中,解决了删点、投影变换等对水印信息提取的不利影响。实验分析表明,该算法在抗矢量地理空间数据处理中常见的噪声攻击、坐标数据轻微的移动等方面具有较好的效果。     

Mapping uncertain geographical attributes: incorporating robustness into choropleth classification design

ABSTRACT

Choropleth mapping provides a simple but effective visual presentation of geographical data. Traditional choropleth mapping methods assume that data to be displayed are certain. This may not be true for many real-world problems. For example, attributes generated based on surveys may contain sampling and non-sampling error, and results generated using statistical inferences often come with a certain level of uncertainty. In recent years, several studies have incorporated uncertain geographical attributes into choropleth mapping with a primary focus on identifying the most homogeneous classes. However, no studies have yet accounted for the possibility that an areal unit might be placed in a wrong class due to data uncertainty. This paper addresses this issue by proposing a robustness measure and incorporating it into the optimal design of choropleth maps. In particular, this study proposes a discretization method to solve the new optimization problem along with a novel theoretical bound to evaluate solution quality. The new approach is applied to map the American Community Survey data. Test results suggest a tradeoff between within-class homogeneity and robustness. The study provides an important perspective on addressing data uncertainty in choropleth map design and offers a new approach for spatial analysts and decision-makers to incorporate robustness into the mapmaking process.