中国西部环境与生态科学数据中心：面向西部环境与生态科学的数据集成与共享

国家自然科学基金委员会“中国西部环境与生态科学研究计划”自2001年启动以来,有力地推动了西部区域环境演化、陆地生态过程和人类活动对环境的影响等方面的研究,积累了丰富的基础数据。国家自然科学基金委员会“中国西部环境与生态科学数据中心”承担“西部计划”项目数据产出的收集、管理、集成,并面向西部环境与生态科学的各个领域提供科学数据服务。“西部数据中心”的总体框架是以“西部计划”和地球系统科学发展的科学需求为导向,建成以数据共享、知识积累、合作交流和数据科学为主要内容的集成平台,为“西部计划”多学科的交叉研究和成果的综合集成及地球科学发展的长远目标服务。以共建共享的指导思想集成针对西部环境与生态现状与变化的基础背景数据、环境与生态观测数据、模型数据集、数据工具及数据文档;并以完全与开放的数据共享原则为用户提供推送式数据服务。目前,“西部数据中心”已完成了数据共享平台、知识积累平台与合作交流平台的开发和集成,初步形成了科学数据平台,整理并发布了大量的西部环境生态科学所需的关键数据集。     

国土资源数据分析及其整合与集成

本文详细分析了国土资源数据特点、综合数据来源、产生方式和使用方法等方面,对数据进行了分类,比较了不同的数据格式。在此基础上,阐述了国土资源数据的集成框架,讨论了数据整合和集成的方法和流程,提出了数据整合与集成的三种框架问题。     

Dynamic data integration for structural modeling: model screening approach using a distance-based model parameterization

This paper proposes a novel history-matching method where reservoir structure is inverted from dynamic fluid flow response. The proposed workflow consists of searching for models that match production history from a large set of prior structural model realizations. This prior set represents the reservoir structural uncertainty because of interpretation uncertainty on seismic sections. To make such a search effective, we introduce a parameter space defined with a “similarity distance” for accommodating this large set of realizations. The inverse solutions are found using a stochastic search method. Realistic reservoir examples are presented to prove the applicability of the proposed method.     

蚌埠市地理信息系统应用探讨

阐述了GIS系统的设计原则,建设方案,揭示了GIS系统功能模块的效能,利用Map控件建立信息管理系统,最后探讨了GIS系统在应用领域的发展前景。     

数字化测图中指向箭头的设计

提出在数字化测图的外业编码数据采集过程中,对于未能连线的方向给与一个指向箭头,以便于在内业的地形图编辑中,根据指向箭头进行连线,提高连线率,减小外业作图工作量,提高工作效率。     

基于ArcGIS的动态符号化设计与实现

地图符号是地图的语言单位,通过对地图符号的解读,可以直观的了解地图所表达的地理信息。ArcGis的符号化功能对于测绘符号的绘制是有一定局限的。而其他大部分测图软件的符号系统基本上是针对各个软件的,不同的软件都有独立的符号系统,离开了软件平台,如不打散块状符号或不添加辅助线就不能为其它软件所调用,本文中提出的ArcSymbol插件实现了在ArcGis操作环境下无需打散或添加辅助线即可方便、快速、无损的查看和打印满足地形图图式要求的图形,减少空间数据库中的数据冗余。并且ArcSymbol支持Shape、Coverage、Geodatabase格式,不需要数据的转换就能轻松地实现图形符号化,实现符号化的无损性。     

GPS-RTK联合全站仪的野外数据采集

对于地形测绘和其它环境条件复杂的地区,用常规方法进行数据采集比较困难,传统的测绘方法越来越不能满足测量效率和成本的要求,但采用GPS RTK与全站仪联合作业,使RTK与全站仪优势互补,在保证测量精度的前提下,可大幅度提高测量速度和效率。     

GPS CORS系统中NTRIP传输技术的应用研究

NTRIP是一种播发实时差分定位改正信息的IP协议。本文讨论了NTRIP的组成、工作原理,并给出一个应用实例。     

The Tau Model for Data Redundancy and Information Combination in Earth Sciences: Theory and Application

Many decision-making processes in the Earth sciences require the combination of multiple data originating from diverse sources. These data are often indirect and uncertain, and their combination would call for a probabilistic approach. These data are also partially redundant with each other or with all others taken jointly. This overlap in information arises due to a variety of reasons—because the data arises from the same geology, because they originate from the same location or the same measurement device, etc. The proposed tau model combines partially redundant data, each taking the form of a prior probability for the event being assessed to occur given that single datum. The parameters of that tau model measure the additional contribution brought by any single datum over that of all previously considered data; they are data sequence-dependent and also data value-dependent. Data redundancy depends on the sequence in which the data is considered and also on the data values themselves. However, for a given sequence, averaging the tau model parameters over all possible data values leads to exact analytical expressions and corresponding approximations and inference avenues. Information on multiple-point connectivity of permeability arrives from core data, well-test data and seismic data which are defined over varying supports with complex redundancy between these information sources. In order to compute these tau weights for determining connectivity, one needs a model of data redundancy, here expressed as a vectorial training image (Ti) constructed using a prior conceptual knowledge of geology and the physics of data measurement. From such a vectorial Ti, the tau weights can be computed exactly. Neglecting data redundancy leads to an over-compounding of individual data information and the possible risk of making extreme decisions.