Spatial variation of the intertidal sediments and macrozoo-benthic assemblages along Eighty-mile Beach, North-western Australia

The extensive intertidal flats along Eighty-mile Beach in North-western Australia appear to be monotonous and homogeneous and seem ideally suited to study tidal zonation in macrozoo-benthic communities and their possible correlates with characteristics of the sediment. In October 1999, we sampled benthic invertebrates and sediments at a total of 895 sampling stations distributed over six different locations, each location separated by 15 km of unsampled foreshore along Eighty-mile Beach. To test for the presence or absence of patterns of tidal zonation (distinct height-related zones of specific sediment grain sizes or zoobenthic taxonomic groups) or patchiness (distinct patches of specific sediment grain sizes or zoobenthic taxonomic groups not related to tidal height) each location was divided into three along-shore sections and each section (transect) was examined at two or three tidal heights. Zonation was observed for sediment grain sizes. Sediments were coarser at the highest intertidal level and finer towards the low water line. Benthic assemblages also differed among tidal heights, but in terms of species-composition the differences were not consistent among the locations. Each location supported a unique collection of benthic invertebrates. Therefore the hypothesis of the presence of distinct zones of specific species or zoobenthic taxonomic groups was rejected; the presence of benthic patches was confirmed. The distribution of sediments and the composition of benthic assemblages were surprisingly poorly correlated compared to those reported in 12 previous quantitative studies around the world. One possible explanation might be that super-cyclone Vance, which hit the study-area only six months before this study, contributed to this poor correlation. Alternatively, the poor correlation may indicate that biotic interactions are more important than the assumed abiotic structuring.     

基于高光谱Hyperion数据的线性光谱混合模型与神经网络模型的比较

混合像元问题是定量遥感中的热点问题之一,为了改进从遥感数据中提取定量信息,人们建立了各种混合光谱分解技术,其中线性光谱混合模型和神经网络模型就是两种比较成熟的方法。以陕西省横山地区的高光谱Hyperion数据为研究基础,通过最小噪声变换(MNF)、像元纯度指数(PPI)转换和RMS误差分析的迭代方法相结合提取影像中的纯净像元作为终端端元。分别运用神经网络模型和线性光谱混合模型对影像进行光谱分解,得到各个组分的分解图像。以标准植被指数(NDVI)影像为衡量标准,选取训练样本点,分别对两种模型进行回归分析,结果显示NDVI影像与线性光谱混合模型植被分解图像的判定系数(R2=0.91)要大于其与神经网络模型的判定系数(R2=0.81)。进一步分析表明在一般情况下,线性光谱混合模型具有比神经网络模型略高的分离精度,但是神经网络模型对细部信息的提取的效果要好于线性光谱混合模型,最后提出了端元均方根误差(EAR)指数,一种新的混合像元分解的思路。     

Chebyshev逼近滤波器在位场分离中的应用

在对经典FIR数字滤波器的设计方法进行研究的基础上,提出了一种可以用于位场分离的基于Chebyshev最佳一致逼近原理的FIR滤波器的设计方法。在理论模型实验中,采用基于Hanning窗的低通滤波器计算出的区域异常最大误差为6.266×10^-6 m/s² ,均方差为2.115×10^-6 m/s² ,最大百分比误差为22.2%,而且计算点在±9 km以外的误差均大于10.1%。而利用最佳一致逼近原理分离出的区域场和局部场与理论异常值拟合得较好,曲线基本重合。分离出的区域异常最大误差为3.101×10^-6 m/s² ,均方差为0.989×10^-6 m/s² ,最大百分比误差仅在边部的几个数据上,为7.76%,其余各点的误差均小于4.1%。实例检验中将该方法用于孙吴—嘉荫剖面布格重力异常场的分离,分离出的区域场中局部场残留少,分离彻底,效果较为理想。     

Open source, spatial analysis, and activity-travel behaviour research: capabilities of the aspace package

This paper reports on recent experience with the development of aspace, an Open Source (OS) library for the geographic visualization and analysis of activity-travel behaviour. The paper begins with an overview of recent progress with respect to the convergence of Open Source technology, spatial analysis, and travel behaviour research. The remainder of the paper focuses on aspace; a collection of functions that, when combined with data describing the geographical location of daily activities, can be used to visualize and describe spatial properties of individual and household activity spaces. These properties include: size, orientation, shape, and the geographical dispersion of activity locations contained within the activity space. Several planar geometries are used to transform measurable spatial properties into intuitive objects for visualizing spatial patterns of activity participation. Experiments are conducted, using data from the first wave of the 2003 Toronto Travel Activity Panel Survey, to demonstrate the potential application of aspace for basic and applied policy-based research into activity-travel behaviour. The toolkit is distributed as a downloadable ‘package’ from the Open Source R Project for Statistical Computing.      

Income distribution dynamics and cross-region convergence in Europe

This paper presents a continuous version of the model of distribution dynamics to analyse the transition dynamics and implied long-run behaviour of the EU-27 NUTS-2 regions over the period 1995–2003. It departs from previous research in two respects: first, by introducing kernel estimation and three-dimensional stacked conditional density plots as well as highest density regions plots for the visualisation of the transition function, based on Hyndman et al. (J Comput Graph Stat 5(4):315–336, 1996), and second, by combining Getis’ spatial filtering view with kernel estimation to explicitly account for the spatial dimension of the growth process. The results of the analysis indicate a very slow catching-up of the poorest regions with the richer ones, a process of shifting away of a small group of very rich regions, and highlight the importance of geography in understanding regional income distribution dynamics.

Voronoi图的首最邻近递归收敛特性及其应用

讨论了Voronoi图的首最邻近递归收敛特性,即从任一伪最邻近对象开始,递归查找其首最邻近对象,最后必然收敛于最邻近对象.利用该特性,初步实现了移动目标直接邻近对象的连续查询.     

Some Results on the Spatial Breakdown Point of Robust Point Estimates of the Variogram

The effect of outliers on estimates of the variogram depends on how they are distributed in space. The ‘spatial breakdown point’ is the largest proportion of observations which can be drawn from some arbitrary contaminating process without destroying a robust variogram estimator, when they are arranged in the most damaging spatial pattern. A numerical method is presented to find the spatial breakdown point for any sample array in two dimensions or more. It is shown by means of some examples that such a numerical approach is needed to determine the spatial breakdown point for two or more dimensions, even on a regular square sample grid, since previous conjectures about the spatial breakdown point in two dimensions do not hold. The ‘average spatial breakdown point’ has been used as a basis for practical guidelines on the intensity of contaminating processes that can be tolerated by robust variogram estimators. It is the largest proportion of contaminating observations in a data set such that the breakdown point of the variance estimator used to obtain point estimates of the variogram is not exceeded by the expected proportion of contaminated pairs of observations over any lag. In this paper the behaviour of the average spatial breakdown point is investigated for cases where the contaminating process is spatially dependent. It is shown that in two dimensions the average spatial breakdown point is 0.25. Finally, the ‘empirical spatial breakdown point’, a tool for the exploratory analysis of spatial data thought to contain outliers, is introduced and demonstrated using data on metal content in the soils of Sheffield, England. The empirical spatial breakdown point of a particular data set can be used to indicate whether the distribution of possible contaminants is likely to undermine a robust variogram estimator.     

中强地震前后能量分布的自仿射特性

根据简化的地震波传播理论,“漫化”地震能量在空间的分配,减弱能量空间分布概率的极端情形及消除统计域为“空”的情形,由此构造类似于二维ｆＢｍ的地震能量空间分布概率曲面。与起伏不平的地形相似,由于基在水平方向及垂直方向的变化不是等比例的,因而这一分形曲面可能是统计自仿射的。     

The deposit size frequency method for estimating undiscovered uranium deposits

The deposit size frequency (DSF) method has been developed as a generalization of the method that was used in the National Uranium Resource Evaluation (NURE) program to estimate the uranium endowment of the United States. The DSF method overcomes difficulties encountered during the NURE program when geologists were asked to provide subjective estimates of (1) the endowed fraction of an area judged favorable (factorF) for the occurrence of undiscovered uranium deposits and (2) the tons of endowed rock per unit area (factorT) within the endowed fraction of the favorable area. Because the magnitudes of factorsF andT were unfamiliar to nearly all of the geologists, most geologists responded by estimating the number of undiscovered deposits likely to occur within the favorable area and the average size of these deposits. The DSF method combines factorsF andT into a single factor (F·T) that represents the tons of endowed rock per unit area of the undiscovered deposits within the favorable area. FactorF·T, provided by the geologist, is the estimated number of undiscovered deposits per unit area in each of a number of specified deposit-size classes. The number of deposit-size classes and the size interval of each class are based on the data collected from the deposits in known (control) areas. The DSF method affords greater latitude in making subjective estimates than the NURE method and emphasizes more of the everyday experience of exploration geologists. Using the DSF method, new assessments have been made for the young, organic-rich surficial uranium deposits in Washington and idaho and for the solution-collapse breccia pipe uranium deposits in the Grand Canyon region in Arizona and adjacent Utah.