面向对象的语义数据模型及其在空间数据库中的应用

传统的数据库模型适合于表示数字字母数据,难以处理复杂的空间数据。面向对象的语义数据模型克服了传统数据模型的许多不足,越来越多地应用于计算机科学各个领域。本文先描述了面向对象的语义数据模型,然后介绍了建立于这种模型基础上的空间数据库实验系统 spobase。     

对我国国土规划几个主要问题的重新认识

本文基于对我国国土规划近十年实践中所反映的问题的分析,阐述了应改变国土规划的基本性质、以空间结构布局为其核心内容,以及国土规划一般不宜在市域或地区及以下地域层次开展的观点,进而就国土规划特性新的内涵、国土规划的内容重点等问题进行了初步探讨。     

Structural Spatial Interaction*

This paper identifies a concept of structural spatial interaction. Although it is defined differently from its counterpart of structural unemployment in economics, it attempts to define a similar idea. In economics, the focus is on equilibrium in the supply and demand of labor. In this paper structural interaction is that which minimizes aggregate distance travelled, subject to constraints on origins and destinations. The structural interaction model produces an equilibrium, therefore, in the supply and demand of movers, while identifying a spatially efficient trip distribution. It is portrayed as a type of relaxed interaction model and is illustrated using an example of structural migration with Canadian interprovincial migration data.     

Multivariable variogram and its application to the linear model of coregionalization

In this article, we present the multivariable variogram, which is defined in a way similar to that of the traditional variogram, by the expected value of a distance, squared, in a space withp dimensions. Combined with the linear model of coregionalization, this tool provides a way for finding the elementary variograms that characterize the different spatial scales contained in a set of data withp variables. In the case in which the number of elementary components is less than or equal to the number of variables, it is possible, by means of nonlinear regression of variograms and cross-variograms, to estimate the coregionalization parameters directly in order to obtain the elementary variables themselves, either by cokriging or by direct matrix inversion. This new tool greatly simplifies the procedure proposed by Matheron (1982) and Wackernagel (1985). The search for the elementary variograms is carried out using only one variogram (multivariable), as opposed to thep(p + 1)/2 required by the Matheron approach. Direct estimation of the linear coregionalization model parameters involves the creation of semipositive definite coregionalization matrices of rank 1.     

菏泽5.9级地震前后三项地震活动性参数的空间动态演化

用地震活动性参数（地震频度Ｎ，地震能量Ｅ和地震ｂ值）的二维空间等值线计算机扫描技术，系统地追踪了１９８３年菏泽５．９级地震前后三项地震活动性参数的空间动态演化情况。结果表明，菏泽５．９级地震前１－４年，河北平原断陷南部地区特别是其东界聊考断裂带地震活动异常增强，地震频度增高，地震能量释放加速而地震ｂ值降低；地震活动增强区的长度约２００余公里，未来主震发生于地震活动增强区的边缘；震后约一年左右震中周     

大震前地磁场时空间线性度变化的初步研究

把用来分析地震波波形的时间线性度和空间线性度两种方法，应用到地磁资料分析当中，具体分析处理了１９７６年７月２８日唐山Ｍｓ７．８地震和１９８９年１０月１９日大同Ｍｓ６．１地震前后地磁场资料，并对这两次地震前后地磁时空线性度变化情况进行了研究。所得结果表明：①较大地震前地磁场的时空线性度均可能呈现出较明显的下降异常变化，有些在震前回升，②各分量的时空线性度呈现异常的时间基本上同步，并与波速异常发展趋势基本相符。     

Evaluation and comparison of spatial interpolators II

The performance of several variations on ordinary kriging and inverse distance estimators is evaluated. Mean squared errors (MSE) were calculated for estimates made on multiple resamplings from five exhaustive data bases representing two distinctly different types of estimation problem. Ordinary kriging, when performed with variograms estimated from the sample data, was more robust than inverse-distance methods to the type of estimation problem, and to the choice of estimation parameters such as number of neighbors.Notice: Although the research described in this article has been funded in part by the United States Environmental Protection Agency through Cooperative Agreement CR818526 to the Harry Reid Center for Environmental Studies, University of Nevada-Las Vegas, it has not been subjected to Agency review. Therefore it does not necessarily reflect the views of the Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

地震波动力学特征变化指标在短期地震预报中的应用

本文研究了地震前地震波动力学特征的变化，主要是波形和频谱的变化，并从中提取出可望在短期（半年以内）地震预报中应用的一些预报指标。这些指标包括：Ｐ波初始部分波形的时间线性度和空间线性度，初始段平均半周期，Ｓ，Ｐ波频谱的峰值频率，拐角频率，相对带宽度，相对频谱峰值，高频段的谱线斜率绝对值等。同时还研究了短周期地脉动的波形线性度及频谱特征量（峰值频率等）在大震前出现的短期（半年以内）和临震（９天以内）的     

区域化变量的空间聚类分析

传统的聚类分析方法利用数据对平均值的偏差，研究变量之间的相互关系。当它应用于区域化变量的分类时，因缺乏对区域化变量的空间结构的考虑，对合理解释区域化变量之间的相互关系不利。空间聚类分析方法比较好地解决了这个问题。本文介绍了该方法的基本原理及其算法，并说明了它在非条件模拟及在某矿区中的应用情况