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。     

微气象自动观测网

本文介绍利用计算机和通讯技术,建立局地网络的微气象观测系统,实现气象数据的自动采集、无线传输和集中实时处理。整个系统由一个中心站和五个(或更多)观测子站组成,是一个点到点的通讯网络。该系统为研究不同下垫面地气相互作用的观测实验提供了手段和方便。整个系统分两部份介绍,本文作一总体概述,第二部份说明数据采集和无线传输的具体实施。     

自记水位仪的数字化改造

本文详细叙述了采用光电编码和微机技术对自记水位仪进行数字化改造的方案选择、理论计算和改造实践。     

地下流体前兆模糊识别

在地震的孕育、发生到发展的过程中，可能会出现多项地下流体观测量不同程度的前兆异常变化，这些异常变化是复杂多样、模糊不清的。引入模糊识别法对一定区域和一定时间段的地下流体观测数据进行了分析和处理，表明模糊识别法可较好地识别和分辨出地下流体前兆的地震异常。     

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.     

A case study to verify methods for estimating transmissivity distributions along boreholes

Two methods, both using data from fixed-interval-length hydraulic tests and geological mapping on different scales, have been utilised to estimate transmissivity distributions of individual fractures. Individual fracture properties are of importance in estimating transport of water and solutes; they influence the spreading of grout when sealing tunnels. One of the methods is non-parametric, while the other is based on combinatorics and the multiplication principle. The study verified the usefulness of both methods for estimating the probability of conductive and non-conductive fractures, and the transmissivity distributions. Data for estimating transmissivity distributions originate from flow logging of a borehole in Sweden. Fracture frequency data are from core logging and images using a borehole image processing system (BIPS). Estimated transmissivity distributions, based on flow log data from 3-m sections (test scale length, L: 3 m, and step length, dL: 3 m), were compared with transmissivities obtained directly from detailed, overlapping flow logging which identify individual conductive fractures (test scale, L: 0.5 m, step length, dL: 0.1 m). The latter data are considered to be an acceptable approximation of the individual fracture transmissivities; the agreement, compared with the calculated transmissivity distributions based on 3-m section data, is good for both methods.

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Resumen Se han utilizado dos métodos, ambos procesando datos de pruebas hidráulicas de longitud e intervalo fijo y mapas geológicos en distintas escalas, para estimar las distribuciones de transmisividad de fracturas individuales. Las propiedades de fracturas individuales son de importancia para estimar el transporte de agua y solutos; las propiedades influyen en la propagación de lechada al sellar túneles. Uno de los métodos es no paramétrico mientras que el otro se basa en el principio de multiplicación y combinatorio. El estudio verifica la utilidad de ambos métodos para estimar la probabilidad de fracturas conductivas y no conductivas y las distribuciones de transmisividad. Los datos para estimar las distribuciones de transmisividad se originan del registro de flujo de un pozo en Suecia. Los datos de frecuencia de fracturas provienen de registros de núcleo e imágenes usando un Sistema de Procesamiento de Imágenes de Pozo (BIPS). Se compararon las distribuciones estimadas de transmisividad basadas en datos del registro de flujo en secciones de 3 m (longitud de escala de la prueba L: 3 m, y escalón de longitud dL: 3 m), con transmisividades obtenidas directamente de registros detallados de flujo superpuesto el cual identifica fracturas conductivas individuales (escala de la prueba, L: 0.5 m, escalón de longitud, dL: 0.1 m). Los últimos datos se consideran una aproximación aceptable de las transmisividades de fracturas individuales; la consistencia, comparada con las distribuciones de transmisividad calculada basadas en datos de sección de 3 m, es buena para ambos métodos.

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Résumé Deux méthodes ont été testées afin d’estimer la distribution des transmissivités de fractures unitaires; toutes deux utilisent des données issues de tests hydrauliques effectués à intervalles réguliers et de cartographies géologiques à plusieurs échelles. La connaissance des propriétés des fractures unitaires est importante pour estimer le transport d’eau et de solutés; elles influencent en outre l’étalement du coulis lors du scellement des tunnels. La première méthode est non-paramétrique, et la seconde repose sur l’analyse combinatoire et le principe de multiplication. Cette étude a vérifié l’utilité des deux méthodes pour estimer la probabilité d’occurrence de fractures conductrices et non-conductrices, et la distribution des transmissivités. Les distributions des transmissivités ont été estimées à partir de diagraphies effectuées sur un forage situé en Suède. Les densités de fracturation proviennent de carottages et d’imagerie BIPS (Borehole Image Processing System). Les distributions estimées des transmissivités, basées sur des diagraphies de flux effectuées sur des sections de 3 m (échelle du test L:3 m; pas dL:3 m), ont été comparées aux transmissivités obtenues sur des diagraphies de flux détaillées et se chevauchant, identifiant les fractures conductrices unitaires (échelle du test L: 0.5 m ; pas dL: 0.1 m). Il est admis que ces dernières données représentent une approximation satisfaisante des transmissivités des fractures unitaires; les deux méthodes sont en accord avec les distributions des transmissivités calculées à partir des données acquises sur des sections de 3 m.

     

A model for estimating the value of sampling programs and the optimal number of samples for contaminated soil

A model is presented for estimating the value of information of sampling programs for contaminated soil. The purpose is to calculate the optimal number of samples when the objective is to estimate the mean concentration. A Bayesian risk–cost–benefit decision analysis framework is applied and the approach is design-based. The model explicitly includes sample uncertainty at a complexity level that can be applied to practical contaminated land problems with limited amount of data. Prior information about the contamination level is modelled by probability density functions. The value of information is expressed in monetary terms. The most cost-effective sampling program is the one with the highest expected net value. The model was applied to a contaminated scrap yard in Göteborg, Sweden, contaminated by metals. The optimal number of samples was determined to be in the range of 16–18 for a remediation unit of 100 m². Sensitivity analysis indicates that the perspective of the decision-maker is important, and that the cost of failure and the future land use are the most important factors to consider. The model can also be applied for other sampling problems, for example, sampling and testing of wastes to meet landfill waste acceptance procedures.     

Bayesian data fusion in a spatial prediction context: a general formulation

In spite of the exponential growth in the amount of data that one may expect to provide greater modeling and predictions opportunities, the number and diversity of sources over which this information is fragmented is growing at an even faster rate. As a consequence, there is real need for methods that aim at reconciling them inside an epistemically sound theoretical framework. In a statistical spatial prediction framework, classical methods are based on a multivariate approach of the problem, at the price of strong modeling hypotheses. Though new avenues have been recently opened by focusing on the integration of uncertain data sources, to the best of our knowledges there have been no systematic attemps to explicitly account for information redundancy through a data fusion procedure. Starting from the simple concept of measurement errors, this paper proposes an approach for integrating multiple information processing as a part of the prediction process itself through a Bayesian approach. A general formulation is first proposed for deriving the prediction distribution of a continuous variable of interest at unsampled locations using on more or less uncertain (soft) information at neighboring locations. The case of multiple information is then considered, with a Bayesian solution to the problem of fusing multiple information that are provided as separate conditional probability distributions. Well-known methods and results are derived as limit cases. The convenient hypothesis of conditional independence is discussed by the light of information theory and maximum entropy principle, and a methodology is suggested for the optimal selection of the most informative subset of information, if needed. Based on a synthetic case study, an application of the methodology is presented and discussed.