线状空间数据传输的几何相似性度量算法与实验分析

 同一地物在不同比例尺或者不同来源的地图上通常存在着相似性,对于图形几何形似性度量方法的研究有利于地图编制、查询、匹配、更新。线状地物要素在地图中占有很大的比例,因此,本文以线状空间目标为例,在前人的基础上给出了线状空间数据的几何图形相似性度量模型:(1)以差异距离作为相似性特征的位置相似度;(2)以分形维数作为相似性特征的形状相似度;(3)以长度或者周长作为相似性特征的大小相似度。相对于(3)大小相似度而言,(1)位置相似度、(2)形状相似度综合考虑了几何图形整体统计的方法和局部几何特征结构。完成多尺度传输的线状空间数据几何相似性度量实验,并对数据传输量与几何相似性度量方法进行比较,实验结果表明:基于广义Hausdorff距离模型的中位数Hausdorff距离的位置相似性对于空间数据渐进性传输具有稳定性和可行性。最后,总结了本文的研究成果,并展望了该方向进一步研究的若干问题。     

叠加变形有限应变分解及其应用探讨

本文提出了二维不同类型叠加变形的有限应变分解方法。只要测定有限应变及能代表各期主应变面的面理或剪切指向,就可以计算出各期构造应变。     

The method of a two-point conditional column density for estimating the fractal dimension of the distribution of galaxies

We suggest a new method for estimating the fractal dimension of the spatial distribution of galaxies: the method of selected cylinders. We show the capabilities of this method by constructing a two-point conditional column density for galaxies with known redshifts from the LEDA database. The fractal dimension of a sample of LEDA and EDR SDSS galaxies has been estimated to be 2.1±0.1 for cylinder lengths of 200 Mpc. A major advantage of the suggested method is that it allows scales comparable to the catalog depth to be analyzed for galaxy surveys in the form of conical sectors and small fields in the sky.     

基于GIS技术的莱州湾东岸河流分形研究

应用地理信息系统(GIS)技术提取了莱州湾东岸河流信息,在此基础上运用计盒方法对莱州湾东岸的黄水河和王河水系进行了分形分析,获得了两水系的主河道河长分维数和河网分维数,并以此探讨了分维数与流域地貌和地质构造之间的相互关系。分形分析为研究区流域地貌学与水文学研究提供了一种新的研究途经。     

S-A多重分形法在地球化学异常 圈定中的对比应用—以甘肃文康地区为例

通过对甘肃省陇南文康地区的地质背景分析,采用区域1:5万水系沉积物测量的17种常量元素含量数据,分别运用传统统计学方法、S-A（能谱密度-累计面积）多重分形滤波法,确定成矿元素（以Au为例）异常下限值,圈定化探异常。结果表明,与传统方法相比,S-A多重分形法所圈定的异常面积小、数量多,传统统计法圈定的面积较大;两种方法圈定的异常展布方向基本一致,与研究区内已知的矿点吻合度高。本次研究认为S-A多重分形法所圈定的异常基本位于传统方法所圈定异常的内带之中,重点突出,与矿床空间位置对应关系较好,便于野外开展工作。同时在传统异常周边提取了部分低背景区的弱异常,这些弱异常可作为下一步找矿工作的新靶区。     

遥感尺度内涵及遥感像元尺度效应分析的改进分形方法

本文首先分析了遥感影像尺度的三层次内涵。重点针对遥感像元尺度,分析了遥感像元尺度效应及其分形机理,由于现有分形方法没有考虑影像本身尺度(空间分辨率),造成尺度间分形维数的比较时像元尺度效应变化难以有效反映,本文针对此问题提出了基于表面积的加窗分形布朗运动和加窗双层地毯两种改进分形方法。为验证改进分形方法的可靠性,采用了不同像元尺度下系列监督分类进行验证。试验结果表明,每种地物的分维数都随着空间分辨率的降低或像元尺度的缩小,呈总体下降趋势,在某些特征尺度上会出现预示着某些地物结构的拐点,这些拐点对观测该区域地物具有一定指示意义。系列监督分类精度也一定程度上证明了以上两种改进分形方法在分析尺度效应中的可行性。因此本文的方法对于分析遥感像元尺度效应和探索地物尺度聚合规律具有一定的理论意义。     

Surface roughness of alumina fragments caused by hypervelocity impact

Hypervelocity impact experiments are carried out with alumina ceramic targets at impact velocities of 2-4 km/s. The fractal dimension (or roughness exponent) of fragment surfaces is estimated by two different methods (different length scales). One is a divider method (large scale) and the other is a gas-absorption one (small scale). The obtained fractal dimensions are different: ∼2.2-2.4 for larger scale and ∼2.5-2.7 for smaller scale. These values are regardless of the degree of fragmentation.     

Plio-/Pleistocene climate modeling based on oxygen isotope time series from deep-sea sediment cores: The Grassberger-Procaccia algorithm and chaotic climate systems

The question whether paleoclimatic systems are governed by a small number of significant variables (low-dimensional systems) is of importance for modeling such systems. As indicators for global Plio-/Pleistocene climate variability, four marine, sedimentary oxygen isotope time series are analyzed with regard to their dimensionality using a modified Grassberger-Procaccia algorithm. An artificial, low-dimensional chaotic time series (Hénon map) is included for the validation of the method. In order to extract equidistant data the raw data are interpolated with the Akima-subspline method since this method minimizes the change in variance due to the interpolation. The nonlinear least-squares Gauss-Marquardt regression method is used instead of the linear least-squares fit to the logarithmically transformed points, in order to acquire an unbiased estimate of the correlation dimension. The dependences of the estimated correlation dimension on the embedding dimension do not indicate a small number (i.e., less than 5) of influencing variables on the investigated paleoclimatic system, whereas the low dimension for the Hénon map is verified (dimension 1.22–1.28). Because of the limited amount of data in the oxygen isotope records, dimensions greater than about 5 cannot be examined.     

Multifractal and Chaotic Analysis of Vrancea (Romania) Intermediate-depth Earthquakes: Investigation of the Temporal Distribution of Events

The Vrancea seismic region contains an isolated cluster of events beneath the Carpathian Arc Bend in Romania, dipping to about 200 km depth. Seismic activity mainly occurs at intermediate depths (h > 60 km). The main goal of the paper is to perform an in-depth, complex analysis of the occurrence times of these intermediate-depth events. We also try to show the versatility of the methods used to characterize different aspects of the seismicity evolution and to offer a user-friendly software toolbox to do most of the related computations. The earthquake catalog used in this study spans from 1974 to 2002 and includes only the intermediate-depth events. In the first part of the paper, we analyze the multifractal characteristics of the temporal distribution of earthquakes. The study reveals two distinct scaling regimes. At small scales we found a clear nonhomogeneous, multifractal pattern, while at large scales the temporal distribution of events shows a monofractal, and close to Poissonian (random), behavior. The multifractal behavior at small scales (minutes-hours) is shown to be clearly an effect of the short aftershock sequences that occurred after some major Vrancea earthquakes. In the second part of the paper we analyze whether our temporal series shows a persistent (or anti-persistent) long-term behavior, by using the Detrended Fluctuation Analysis (DFA) method. The results suggest that the analyzed temporal series of Vrancea earthquakes is a non-correlated process. In part three of the paper we seek to determine whether the dynamics of our earthquake system (described by the occurrence time of Vrancea earthquakes) is deterministically chaotic, deriving from a rather simple evolution law, or whether it is stochastic and is generated by a system that possesses many degrees of freedom. The results suggest that our signal is stochastic (probably does not possess an attractor). The limited time-span of the catalog and the analysis performed in this paper cannot rule out the emergence of an interesting, quasi-deterministic and low-dimensional structure in the case of major Vrancea earthquakes.Acknowledgement One of the authors (BE) is grateful to the Japanese Ministry of Education for providing him a Monbusho scholarship for studying in DPRI, Kyoto University. We thank Z.R. Struzik, M Holschneider, J. Mori and D. Kaplan for their useful comments, and acknowledge the support of the staff of DPRI, Kyoto University and the National Inst. for Earth Physics, Bucharest. We thank the two reviewers, M.B. Geilikman and M. Anghel, for their useful suggestions which improved the quality of this work.     

INFLUENCE OF SERIES OF SQUARE GRIDS ON FRACTAL DIMENSIONS—A Case Study of Mountains of China＇s Mainland

MANDELBROT enunciated the uncertainty of the length of a coastline in his paper “How long is the coastline of Britain?” published in Science in 1967. The fractal concept was presented for the first time in that paper and has been applied to many fields ever since. Although fractal dimensions of lots of phenomena were calculated by the box-counting method, the quantitative influence of series of square grids on them is ignored. The issue is systematically discussed as a case study of the mountains of China‘s Mainland in this paper. And some significant conclusions are drawn as follows: 1) Although the fractal character objectively exists in the mountains of China‘s Mainland, and it does not vary with the changes of series of square grids, the fractal dimensions of the mountains of China‘s Mainland are different with these changes. 2) The fractal dimensions of the mountains of China‘s Mainlandvary with the average lengths of sides of series of square grids. The fractal dimension of the mountains of China‘s Mainland is the function of the average length of side of square grid. They conform to the formula D=f(r) (where D is the fractal dimension, and r is the average length of side of square grid). 3) Different dots of data collection can affect the fractal dimension of the mountains of China‘s Mainland. 4) The same range of length of side of square grid and dots of data collection can ensure the comparison of fractal dimensions of the mountains of China‘ s Mainland. The research is helpful to get the more understanding of fractal and fractal dimension, and ensure that the fractal studies would be scientific.