GIS conceptual data model

In order to set up a conceptual data model that reflects the real world as accurately as possible, this paper firstly reviews and analyzes the disadvantages of previous conceptual data models used by traditional GIS in simulating geographic space, gives a new explanation to geographic space and analyzes its various essential characteristics. Finally, this paper proposes several detailed key points for designing a new type of GIS data model and gives a simple holistic GIS data model.     

Change of geographic information service model in mobile context

IntroductionGreat progress of scientific and technologicalcivilization dramatically i mproves the interactivemethods between people and world. At the sameti me various intelligent mobile terminals spreadInternet over anywhere in human’s life . Mobilecomputing and mobility of computational toolswill reform traditional geographic informationservice model ,combine seamlessly people ,real-ity and digital world through networks each oth-er ,achieve interoperability without li mitation ofti me and …     

面向GIS数据共享的概念模型设计研究

Ｇ Ｉ Ｓ 数据共享的主要问题是数据的语义共享。在数据共享的保障基础———技术基础、标准化体系及政策法规体系中,标准化工作最为直接,而其中面向数据共享的概念模型的设计又是最基础性的工作之一。面向数据共享的概念模型设计的主要任务是寻求一种规范化、标准化的约束法则来保障数据的共享,为了保障数据共享的安全性,所设计的概念模型应能提供用于共享的抽象概念,这些抽象概念所描述的是地理概念而非纯空间概念,并应能提供语义抽象机制。采用语义数据模型的方法,提出利用地理特征这一概念作为建模的基本概念。通过一个实例对其应用进行了初步探讨。     

LBS中多尺度空间方位的自然语言描述

位置服务是地理信息系统（GIS）应用的重要领域,GIS提供关于空间位置的坐标描述,但这不符合人们的认知和日常习惯。地理空间中人们日常的交流通常使用方位描述。基于自然语言的空间方位的描述对移动目标（如驾驶员）是十分重要的,通过规范的地点描述语言进行快速的地理定位,可提高人的空间反应和处理能力。本文依据人的多尺度空间认知,分析空间参考和定位习惯,结合自然语言描述知识,利用GIS分析功能,给出多尺度环境下空间方位的自然语言描述。     

云GIS平台构建的关键技术研究

云计算是一种新型的分布式计算模式,也是当前IT界研究热点。云GIS平台提供了一种稳定、高效、低成本、环保的支撑应用架构,可以构建各种基于Web的弹性的、按需的地理信息服务,必将成为下一代GIS服务平台。本文在分析了国内外云GIS平台发展现状的基础上,研究了涉及云GIS平台构建的基础设施虚拟化、地理数据云存储、GIS自动化部署等关键技术,从而为相关云GIS平台建设提供一定的指导与借鉴。     

Temporal data mining using genetic algorithm and neural network —A case study of air pollutant forecasts

This paper integrates genetic algorithm and neural network techniques to build new temporal predicting analysis tools for geographic information system (GIS). These new GIS tools can be readily applied in a practical and appropriate manner in spatial and temporal research to patch the gaps in GIS data mining and knowledge discovery functions. The specific achievement here is the integration of related artificial intelligent technologies into GIS software to establish a conceptual spatial and temporal analysis framework. And, by using this framework to develop an artificial intelligent spatial and temporal information analyst (ASIA) system which then is fully utilized in the existing GIS package. This study of air pollutants forecasting provides a geographical practical case to prove the rationalization and justness of the conceptual temporal analysis framework.     

Representing Complex Geographic Phenomena in GIS

Conventionally, spatial data models have been designed according to object- or field-based conceptualizations of reality. Conceptualization of complex geographic phenomena that have both object- and field-like properties, such as wildfire and precipitation, has not yet been incorporated into GIS data models. To this end, a new conceptual framework is proposed in this research for organizing data about such complex geographic phenomena in a GIS as a hierarchy of events, processes, and states. In this framework, discrete objects are used to show how events and processes progress in space and time, and fields are used to model how states of geographic themes vary in a space-time frame. Precipitation is used to demonstrate the construction and application of the proposed framework with digital precipitation data from April 15 to May 22, 1998, for the state of Oklahoma, U.S.A. With the proposed framework, two sets of algorithms have been developed. One set automatically assembles precipitation events and processes from the data and stores the precipitation data in the hierarchy of events, processes, and states, so that attributes about events, processes, and states are readily available for information query. The other set of algorithms computes information about the spatio-temporal behavior and interaction of events and processes. The proposed approach greatly enhances support for complex spatio-temporal queries on the behavior and relationships of events and processes.     

Temporal Data Mining Using Genetic Algorithm and Neural Network--A Case Study of Air Pollutant Forecasts

This paper integrates genetic algorithm and neural network techniques to build new temporal predicting analysis tools for geographic information system (GIS). These new GIS tools can be readily applied in a practical and appropriate manner in spatial and temporal research to patch the gaps in GIS data mining and knowledge discovery functions. The specific achievement here is the integration of related artificial intelligent technologies into GIS software to establish a conceptual spatial and temporal analysis framework. And, by using this framework to develop an artificial intelligent spatial and temporal information analyst (ASIA) system which then is fully utilized in the existing GIS package. This study of air pollutants forecasting provides a geographical practical case to prove the rationalization and justness of the conceptual temporal analysis framework.     

Temporal Data Mining Using Genetic Algorithm and Neural Network——A Case Study of Air Pollutant Forecasts

This paper integrates genetic algorithm and neural network techniques to build new temporal predicting analysis tools for geographic information system (GIS). These new GIS tools can be readily applied in a practical and appropriate manner in spatial and temporal research to patch the gaps in GIS data mining and knowledge discovery functions. The specific achievement here is the integration of related artificial intelligent technologies into GIS software to establish a conceptual spatial and temporal analysis framework. And, by using this framework to develop an artificial intelligent spatial and temporal information analyst (ASIA) system which then is fully utilized in the existing GIS package. This study of air pollutants forecasting provides a geographical practical case to prove the rationalization and justness of the conceptual temporal analysis framework.     

矢量与栅格集成的三维数据模型

以矿山地质为背景，深入分析三维空间信息系统所涉及到的空间对象以及它们之间的联系，提出了几种新的空间对象类型。探讨用矢量与栅格混合的数据结构，以及面向对象的数据模型来表达各类三维空间对象，以此作为设计和建立三维地理信息系统的基础     

时态GIS及其在艾滋病时空分布研究中的应用

时态GIS是GIS向多维化发展的产物。介绍了时态GIS的概念、特征、关键技术及主要时空数据模型。针对艾滋病传播的时空变化特性,提出了基于时态GIS的艾滋病时空分布动态监测的初步解决方案,较详细探讨了基于基态修正模型的艾滋病时空分布动态监测历史库与现时库动态更新方法。     

An integrated data model in three dimensional GIS

The current GIS can only deal with 2-D or 2.5-D information on the earth surface. A new 3-D data structure and data model need to be designed for the 3-D GIS. This paper analyzes diverse 3-D spatial phenomena from mine to geology and their complicated relations, and proposes several new kinds of spatial objects including cross-section, column body and digital surface model to represent some special spatial phenomena like tunnels and irregular surfaces of an ore body. An integrated data structure including vector, raster and object-oriented data models is used to represent various 3-D spatial objects and their relations. The integrated data structure and object-oriented data model can be used as bases to design and realize a 3-D geographic information system.     

实时GIS时空数据模型

为满足动态目标与传感器等实时观测数据获取、存储、管理、分析与可视化的要求,需要发展一种新型地理信息系统—实时GIS。本文根据实时GIS中各种地理要素的特点以及存贮管理要求,提出了一种面向动态地理对象与动态过程模拟的实时GIS时空数据模型,它将时空过程、地理对象、事件、事件类型、状态、观测等相关要素整合在一个时空数据模型中。基于该模型研发了新一代实时GIS,并以四种动态地理对象（包括移动对象、原位传感器对象、视频对象和过程模拟对象）的时空数据的实时接入、存储与可视化为例,验证的模型的可行性。     

Assessing Similarity of Geographic Processes and Events

The increased availability of spatiotemporal data collected from satellite imagery and other remote sensors provides opportunities for enhanced analysis of geographic phenomena. Much of the new data includes regular snapshots of the environment. Comparison of these snapshots can provide information about changes to the phenomena of interest. However, conventional GIS data models and analytical tools lack capabilities to adequately handle massive multidimensional data. One of the fundamental tools necessary to meet such challenges is query support to retrieve and summarize data according to dynamic geographic phenomena, such as geographic events and processes, of interest. Such query support depends upon abilities to assess spatiotemporal similarity so that data representing geographic events that exhibit the spatiotemporal characteristics of interest can be identified in a GIS database. To this end, this paper introduces a method to assess similarity of geographic events and processes (such as storms) based on their spatiotemporal characteristics (such as distribution of precipitation). We developed six indices to capture static and dynamic characteristics of geographic events and applied the Dynamic Time Warping method to temporal sequences of the six indices to examine the similarity among these events. With a case study, we demonstrated the proposed indices and method capable of comparing spatiotemporal characteristics of events as recorded in a GIS database and categorizing spatiotemporal data into groups of events according to their behavior in space and time.     

RS与GIS一体化数据结构的研究

详细阐述了RS与GIS一体化的概念 ,通过对RS与GIS一体化方面的研究与分析 ,进一步明确RS与GIS一体化对空间数据存储结构的要求 ,着重探讨了几种典型的用于RS与GIS一体化的数据结构 ,针对现有数据结构存在的问题与不足 ,提出了一种具有普遍适用价值的基于语义网络的空间数据存储结构 ,并给出一个应用实例     

基于一体化全局模型的智能型制图方法

提出了一种基于一体化全局模型的智能型制图方法.该方法基于一体化全局模型(拓扑信息模型),归纳和发现了矢量数据处理过程中显性的数学逻辑和隐含的作业规则;组建了知识库;进行了基本知识组合并在数据处理的不同环节中自动作用于全局数据库.由此不断改写全局数据库,使之逐步趋近为具有一体化特征的矢量地理信息,形成矢量智能化处理流程.在获取满足GIS要求数据的同时,获取用空间几何数据和相应符号参数表示的制图数据.     

GIS环境下的制图自动综合方法研究

制图综合一直是地图学领域研究的重要课题,近年来又成为国际GIS领域内的热点和前沿问题之一。借助GIS的可视化以及GIS的空间分析工具,制图自动综合的研究进入了一个新阶段。本文简要介绍了在GIS环境下制图自动综合的概念和特点,以及相关内容,并从知识表示方面分析了制图综合的理论。其中重点讨论了制图综合的综合算法以及模型综合,而模型综合是地理信息的概念层次上的综合,是地图综合的前提和基础。     

Use of a Three-Domain Repesentation to Enhance GIS Support for Complex Spatiotemporal Queries

As the development of Geographic Information Systems (GIS) proceeds to advanced scientific and societal applications, there is an emerging need to enhance GIS support for complex spatiotemporal queries. Dynamic GIS representations (as opposed to static, map-based representations) that can integrate proper data elements in the production of geographic information are required. This paper demonstrates the use of a three-domain representation that facilitates compilation of higher-level information (such as frequency and rate) from preliminary data records (such as time and location) stored in a database. The three-domain representation is compared with snapshot, space-time composite, and spatiotemporal object models using a sample data set for forest transitions. While the three-domain representation is a normalization of these data models, it offers a conceptual alternative that enables GIS to represent spatiotemporal behaviors of geographic entities, in addition to entities as well as histories at locations as emphasized in most GIS data models. The comparison shows that the three-domain representation has combined the strengths of the space-time composite and spatiotemporal object models. Moreover, it enables aggregations of analytical use along with dynamic mappings between geographic concepts and locations, a distinct capability that takes GIS query processing beyond the level of information support offered by static map-based data models.