全球地理信息系统(G2IS)架构体系初探

随着人们对全球GIS的需求不断增加,现有的地理信息系统在技术上已不能适应,因此,建设新一代全球GIS成为当前GIS发展的客观要求。本文基于地球剖分理论,以计算机集群技术、时空一体化技术和虚拟现实技术为辅助技术,提出了关于全球地理信息系统(G2IS)的架构体系的初步设想,认为新一代全球地理信息系统将成为GIS发展的一个重要方向。     

一种基于GPU和内存映射文件的高分辨率遥感图像快速处理方法

高分辨率遥感图像处理经常面临程序执行时间过长和内存空间不足的问题,虽然并行计算技术可以提高遥感图像的处理速度,但是无法降低算法占用的巨大内存空间。为了解决这一问题,本文提出了一种利用CUDA和内存映射文件的高分辨率遥感图像快速处理方法,并以K-Means算法为例进行了实现。其中,CUDA技术可以有效利用GPU强大的并行计算能力,而内存映射文件技术降低了磁盘I/O速度较慢对算法性能的影响。实验结果表明,本文方法比传统K-Means聚类算法计算速度提高了30倍左右,内存使用量降低了90%以上。     

Deterministic non-linear wave prediction using probe data

The accurate prediction of non-linear sea states represents a great challenge, with a number of applications in oceanography, marine engineering, security of people and marine transportation, etc. In this paper, we report on the development of two efficient deterministic prediction models for 2D irregular wave-fields. These models are based on the exploitation of wave elevation time series given by one or more probes and on the use of two different numerical models for the wave-fields simulation. Two effective data assimilation processes are developed to improve the wave-field estimates obtained from the study of one or several probe signals, so that we obtain proper initial conditions for the forecast. The assimilation schemes have been validated on the reconstruction of model-generated observations and accurate predictions of the corresponding synthetic wave-fields evolution have been obtained.     

MODIS遥感数据格式及使用方法综合分析

针对当前MODIS遥感资料推广应用中数据产品使用者和开发者在实际工作中经常遇到数据格式和计算方法方面的问题,分析了MODIS遥感资料的数据格式,以及如何使用定标后的1B数据计算地球视场的光谱反射率和辐射率进而生成各种气象和环境监测应用产品,并给出了一个数据处理应用实例.     

Stress‐dependent hardening and failure surfaces of dry sand

During several triaxial compression experiments on plastic hardening, softening, and failure properties of dense sand specimens, it was found on various stress paths that the size of the failure surface was not constant. Instead, it changed depending on the current state of hydrostatic pressure. This finding is in contrast to the standard opinion consisting of the fact that the failure surface remains constant, once it has been reached during an experiment or in situ. In general, the behaviour of cohesionless granular‐material‐like sand is somehow characterised in between fluid and solid, where the solid behaviour results from the angle of internal friction and the confining pressure. Although the friction angle is an intrinsic material property, the confining pressure varies with the boundary conditions, thus defining different solid properties like plastic hardening, softening, and also failure. Based on our findings, it was the goal of the present contribution to introduce an improved setting for the plastic strain hardening and softening behaviour including the newly found yield properties at the limit state. For the identification of the material parameters, a complete triaxial experimental analysis of the tested sand is given. The overall elasto‐plasticity concept is validated by numerical computations of several laboratory foundation‐ and slope‐failure experiments. The performance of the proposed approach is compared with the standard concept of a constant failure surface, where the corresponding yield surfaces are understood as contours of equivalent plastic work or plastic strain. Copyright © 2012 John Wiley & Sons, Ltd.     

Prediction by regression and intrarange data scatter in surface-process studies

Modeling is a major component of contemporary earth science, and regression analysis occupies a central position in the parameterization, calibration, and validation of geomorphic and hydrologic models. Although this methodology can be used in many ways, we are primarily concerned with the prediction of values for one variable from another variable. Examination of the literature reveals considerable inconsistency in the presentation of the results of regression analysis and the occurrence of patterns in the scatter of data points about the regression line. Both circumstances confound utilization and evaluation of the models. Statisticians are well aware of various problems associated with the use of regression analysis and offer improved practices; often, however, their guidelines are not followed. After a review of the aforementioned circumstances and until standard criteria for model evaluation become established, we recommend, as a minimum, inclusion of scatter diagrams, the standard error of the estimate, and sample size in reporting the results of regression analyses for most surface-process studies.     

矿山地理信息系统中的空间和时间四维数据模型

现有的许多地理信息系统（GISs）一般都没有考虑时间这一维数据。本文依据矿山的特点和需求，提出了能满足空间和时间要求的GIS的概念。针对传统数据模型所存在的缺点，以及根据处理历史数据所具有的特点，提出了一种用于矿业开发的空间和时间综合四维数据模型。这种模型通过采用四维空间线性编码技术，可大大减少数据存贮所需的辅助操作。为了适应综合四维数据处理的需要，笔者研究出了一种新的拓扑结构——四维空间和时间因素的拓扑关系。     

实时波形数据断记的解决办法

应用Windows操作系统的网络技术和自行开发的报警软件，解决了牡丹江地震台连续波形数据断记问题。本文详细介绍了解决方案和报警软件的安装及使用方法。     

苏北地区大地电磁测深采集方法技术研究

根据苏北地区大地电磁勘探环境特点进行了电极距长度、磁场位置和采集时长的试验工作，确定了大地电磁测深勘探技术参数设置下限，电极距长度不能小于50m，采集时间要大于8h，磁距应控制在2km范围内。     

Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools

Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets. Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.