GIS-based simulation as an exploratory analysis for space-time processes

The purpose of this paper is to argue for a novel use of geographical information system (GIS) as an exploratory device for understanding complex space-time processes. Conventionally, a GIS has been configured as a spatial database management system. Therefore, the capabilities of data input, storage, retrieval, manipulation and display have been well developed, whereas the analytical and dynamic processing and modelling capabilities are under-developed. The importance of integrating GIS with dynamic and analytical models has been widely recognised. Extending the use of GIS into spatial simulation represents a plausible research direction. On the other hand, the usefulness of conventional deductive model becomes limited when dealing with complex space-time processes. In essence, the inherent complexity calls for a simulation approach. The new nonlinear modelling paradigm, for example, cellular automata (CA), opened a way in which behaviourally-richer dynamics and more micro-spatial data could be incorporated into understanding space-time processes. It is argued therefore that GIS can be used as a platform – a controlled environment or laboratory – for exploring complex space-time processes. The discussion of GIS-based simulation in this paper is illustrated with a primitive simulation of the evolution of urban spatial structure. Received: 2 July 1997/Accepted: 19 November 1998     

高性能GIS动态目标渲染引擎的设计与实现

针对海量动态目标渲染效率较慢的问题,本文研究并设计了基于混合加速的高性能GIS动态目标渲染引擎,并利用SuperMap的组件GIS研发了动态目标渲染引擎原型系统.通过比较不同类型海量空间数据的可视化实验结果表明,本文研究成果在渲染二维和三维空间海量动态目标时,满足GIS高性能可视化需求,可视化效果流畅.     

Recent Literature

Development of a temporal geographic information system (GIS) and spatio-temporal data modeling are key to incorporating time into geographic information science. This paper describes how to design and develop temporal GIS that will work with spatio-temporal data represented in various data models, and it introduces a prototype temporal GIS with a case study. In temporal GIS, the integration of multiple spatio-temporal representations is based on common spatial and temporal reference systems. In other words, a map window of temporal GIS visualizes spatio-temporal data valid at the same time within one spatial area. To achieve such visualization, separate data editing and query modules are required for each spatio-temporal data model (STDM). In the temporal query interface, after a user specifies a time, the system automatically hires correspondent modules to retrieve spatio-temporal data valid at that time. Besides temporal queries common to all STDMs, each module may provide additional temporal query capabilities specific to that STDM. In the case study, I implement a prototype temporal GIS for three STDMs. The examples of query and visualization, which use three datasets (census data, land use/land cover, and elevation data) demonstrate the prototype temporal GIS can integrate multiple temporal representations.     

Fields as a framework for integrating GIS and environmental process models. Part 1: Representing spatial continuity

Linking a GIS to a spatially distributed, physically-based environmental model offers many advantages. However, the implementation of such linkages is generally problematic. Many problems arise because the relationship between the reality being represented by the mathematical model and the data model used to organize the spatial data in the GIS has not been rigorously defined. In particular, while many environmental models are based on theories that assume continuity and incorporate physical fields as independent variables, current GISs can only represent continuous phenomena in a variety of discrete data models. This paper outlines a strategy in which field variables are used to enable modellers to work directly with the spatial data as spatially continuous phenomena. This allows the manner in which the spatial data has been discretized and the ways in which it can be manipulated to be treated independently from the conceptual modelling of physical processes. Modellers can express their spatial data needs as representations of reality, rather than as elements of a GIS database, and a GIS-independent language for model development may result. By providing a formal linkage between the various models of spatial phenomena, a mechanism is created for the explicit expression of transformation rules between the different spatial data models stored and manipulated by a GIS.     

A Hybrid System of Expanding 2D GIS into 3D Space

A hybrid system that integrates two-dimensional (2D) GIS and three-dimensional (3D) visualization has been developed to provide unique solutions to application domains where traditional 2D GIS and 3D visualization cannot alone provide a solution. In this paper, we focus on three key issues in realizing such an integrated system, including large-scale terrain rendering, 2D and 3D combination display (for example, rendering 2D GIS layers in 3D space), expanding traditional 2D GIS analysis functions into a 3D environment, and visualizing 3D geographical data. A generic framework is developed to integrate 3D visualization with various types of 2D GIS, such as commercial GIS software, open source GIS software and spatial databases. A prototype 2D and 3D hybrid system that seamlessly integrates 2D GIS (developed with ArcEngine) and 3D rendering engine (developed with DirectX) is then developed based on the framework. In this hybrid system, 2D and 3D data are viewed within the same scene. Multiple 2D GIS layers are overlaid on the base terrain using a Level of Detail (LOD) model. Advanced query functions, data accessing, data management and spatial analysis, which are executed in the traditional 2D GIS, are provided to users in a 3D environment by continuously transforming information between the 2D GIS subsystem and the 3D subsystem. The 3D data are organized and displayed by Keyhole Markup Language (KML) and textured 3D models in the COLLAborative Design Activity (COLLADA) format. The prototype demonstrates that this hybrid system has effectively addressed the three key issues identified above and that it can seamlessly integrate 2D GIS and 3D visualization. The hybrid system has great potential to be employed in many application domains, such as urban planning, landscape design and environmental decision making, among others, to enhance the 3D design capability and facilitate public participation in the planning, design and decision-making process.     

GIS时空分析系统的Clifford代数设计与实现

以Clifford代数为理论基础与数学工具,构建了时空分析原型系统：①在兼容多类常用GIS数据格式的基础上,根据Clifford代数空间构建的思想,对现有时空数据模型进行扩展,实现了时间、空间与属性的一体化表达;②定义了可支撑多维度时空分析的几何、度量等Clifford代数算子库;③基于插件的时空分析模型算法构建及集成框架,实现了高维邻域分析、网络分析以及时空栅格数据分析等地学分析算法。实验结果显示,根据Clifford代数所构建的时空分析系统可有效支撑多维时空分析。     

CAUSTA: Clifford Algebra‐based Unified Spatio‐Temporal Analysis

Introducing Clifford algebra as the mathematical foundation, a unified spatio‐temporal data model and hierarchical spatio‐temporal index are constructed by linking basic data objects, like pointclouds and Spatio‐Temporal Hyper Cubes of different dimensions, within the multivector structure of Clifford algebra. The transformation from geographic space into homogeneous and conformal space means that geometric, metric and many other kinds of operators of Clifford algebra can be implemented and we then design the shortest path, high‐dimensional Voronoi and unified spatial‐temporal process analyses with spacetime algebra. Tests with real world data suggest these traditional GIS analysis algorithms can be extended and constructed under Clifford Algebra framework, which can accommodate multiple dimensions. The prototype software system CAUSTA (Clifford Algebra based Unified Spatial‐Temporal Analysis) provides a useful tool for investigating and modeling the distribution characteristics and dynamic process of complex geographical phenomena under the unified spatio‐temporal structure.     

Building spatial models within GIS through Geo-Algebra

This paper describes Geo-Algebra, a mathematical framework for supporting geo-computational modelling in conjunction with GIS-based spacial data manipulation capabilities. Geo-Algebra overcomes the discrepancy between spacial modelling and GIS in the modes of representation as well as in their underlying concepts of space by using a common representational framework for (1) mathematical models expressing spatial relationships and (2) data models of georeferenced information. Geographic models of spatial structure and static as well as dynamic spatial interaction are formulated consistently within Gco-Algebra through a limited set of generic operations on map layers which are used simultaneously for GIS dam manipulation and analysis. A significant advantage of Geo-Algebra over other approaches to integration, such as high-level computational languages, is the development of theoretical concepts of the most general kind which allows the derivation of general properties of these in a deductive manner. In particular, Geo-Algebra formalizes and extends the mathematical notion of Map into the novel concepts of relational and metarelational Maps. These extensions lead to the novel concepts of space bridging the absolute and relative, as well as static and dynamic views of space. Such theoretical concepts are also implemented in a dynamic simulation tool called Geocellular .     

Context-dependent spatial analysis: A role for GIS?

The relationship between spatial analysis and GIS has been a debating point for over a decade. Some see GIS as leading the way to a new era in which the desire and the ability to analyse spatial data is widespread, not just in geography but throughout all disciplines in which spatial data are encountered. Others see GIS as simply providing a medium for the recycling of out-dated spatial analytical techniques and models. This paper describes a role for GIS through the development of new forms of ‘local’ or ‘context-dependent’ spatial analytical methods in which the focus is on exceptions to the general trend represented by the more traditional ‘global’ methods.     

Control of spatial discretisation in coastal oil spill modelling

Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Search” method based on GIS zone design principles is shown to significantly improve discretisation of bathymetric data and hydrodynamic modelling outputs. The concepts and methods developed in the study are expected to have general relevance for a range of applications in numerical environmental modelling.     

A classification of water erosion models according to their geospatial characteristics

In this article, an extensive inventory in the literature of water erosion modelling from a geospatial point of view is conducted. Concepts of scale, spatiality and complexity are explored and clarified in a theoretical background. Use of Geographic Information Systems (GIS) is pointed out as facilitating data mixing and model rescaling and thus increasing complexity in data-method relations. Spatial scale, temporal scale and spatial methodologies are addressed as the most determining geospatial properties underlying water erosion modelling. Setting these properties as classification criteria, 82 water erosion models are identified and classified into eight categories. As a result, a complete overview of water erosion models becomes available in a single table. The biggest share of the models is found in the category of the mechanistic pathway-type event-based models for watershed to landscape scales. In parallel, geospatial innovations that could be considered as milestones in water erosion modelling are highlighted and discussed. An alphabetical list of all models is also listed in the Appendix. For manipulating scale efficiently, two promising spatial theories are suggested for further exploitation in the future such as hierarchy theory and fractals theory. Regarding erosion applications, uncertainty analysis within GIS is considered to be necessary for further improving performance of erosion models.     

基于地理事件时变序列的时空数据模型研究与实现

首先分析比较了已有的时空数据模型的特点，针对其存在的不足，提出并讨论了一种基于地理事件时变序列的时空数据模型，阐述了该模型的时空语义概念和时空拓扑关系，并针对具体的实际应用，在现有成熟的GIS平台上进行扩展，验证了该数据模型的有效性。     

A visual programming language for spatial modelling in GIS

An integration between a visual programming environment and GIS has been developed to create and run spatial models. The visual programming environment provides graphical objects to create flowchart-like models of spatial phenomena using GIS data. The integrated system is object-oriented and designed to lessen the technical burdens of GIS programming. The system capabilities are demonstrated using a hydrological model example, and the model execution speed is compared with an equivalent model implementation in a traditional raster-based modelling system.     

An integrated environment for developing knowledge-based spatial decision support systems

Knowledge-based spatial decision support systems (KBSDSS) incorporate heuristic reasoning, and analytical and spatial modelling capabilities to support decision making in resource and environmental management. They are able to provide the assistance for both the structuring and formulation of the spatial problem, and the design and execution of a solution process by automatically integrating different types of models and data. This paper presents a KBSDSS development environment, which connects a GIS tool (ARC/INFO) with an expert system tool (CLIPS) and a hypertext diagramming tool (HARDY). ARC/INFO provides capabilities for spatial data handling. CLIPS is used to develop knowledge bases and heuristic reasoning. HARDY is used to represent spatial problems in terms of diagrams that can then be translated into a CLIPS knowledge base for evaluation. The development environment allows users to structure their problems and develop models for particular requirements and domains.     

土地利用动态监测中的时空数据模型研究

针对传统GIS数据模型存在的问题,开展了基于特征的时空数据模型研究.结合我国土地利用动态监测,提出了一个新的时空数据模型-基于变化特征状态的时空数据模型(SCFSTDM),该模型保持了地理现象的完整性,地理信息的完备性以及时空专题信息的有机集成,模型有利于面向目标定向分析方法的应用和时空分析与推理的实现,有利于地理数据的共享,设计和开发了基于SCFSTDM的时态土地利用信息系统,实现了基于特征实例的时空复合查询,时空推理以及动态播放等功能.     

An oracle-based data management method for large database in CyberCity GIS

An Oracle8i-based approach is proposed to manage the integrated databases of large CyberCity. This approach consists of three schemes: ? a special R+-tree index is designed to accelerate spatial retrieving, in which the bounding boxes of local regions have no intersection and all leaf nodes of the R+-tree (geometry records) have no repetition; ∪ different data compression algorithms are adopted to compress the digital elevation models, 3D vector models and images, such as LZ77 lossless compression algorithm for compression of vector data and JPEG compression algorithms for texture images; ? in order to communicate with Oracle8i database, a CyberCity GIS spatial database engine (SDE) is designed. On the basis of this SDE prototype a case study is done.     

基于GIS与SDM技术的可视化空间数据分类研究

提出将GIS与可视化空间数据挖掘技术之集成的基本框架。在此基础上,基于VisualC++6.0和Ma-pObject2.0组件技术设计和开发了一个可视化交互空间数据挖掘分类系统,系统采用决策树方法和贝叶斯网络作为数据挖掘方法的基本算法,采用训练与学习相结合实现空间数据的分类。文中用实例数据对系统性能、算法和规则有效性进行了验证。结果表明,该系统是一个适用的、可扩展的可视化交互空间数据挖掘工具,系统能够实现数据挖掘实时动态的交互控制,实现了数据挖掘过程的可视化、挖掘模型的可视化和结果的可视化显示、可视化思考、可视化分析与评价。     

元胞自动机（CA）模型在土地利用领域的研究综述

通过模型对区域土地利用/覆盖变化（LUCC）进行分析已经成为了当前全球的研究主要内容之一。元胞自动机（CA）模型是一种通过定义局部的简单的计算规则来模拟和表示整个系统中复杂现象的时空动态模型,其＂自下而上＂的研究思路,强大的复杂计算功能及高度动态,使得它在模拟空间复杂系统的时空动态演变方面具有很强的能力。CA模型通过与其他模型相结合,在综合考虑各种限制因素和转换规则的前提下,通过反复迭代综合空间分析与非空间分析,模拟土地利用变化情景,在国内外已经形成了较为成熟的研究模型。本文首先提出了CA模型在土地利用变化中应用的背景及其特点;然后,分析了CA模型的构成原理以及在国内外的应用进展与现状;最后,详细阐述了CA模型在土地利用变化中的发展趋势及今后研究工作中应注意的问题。     

An oracle-based data management method for large database in CyberCity GIS

An Oracle8i-based approach is proposed to manage the integrated databases of large CyberCity. This approach consists of threeschemes: ① a special R -tree index is designed to accelerate spatial retrieving, in which the bounding boxes of local regions have no intersection and all leaf nodes of the R -tree (geometry records ) have no repetitiont;② different data compression algorithms are adopted to compress the digital elevation models, 3D vector models and images, such as LZ77 lossless compression algorithm for compression of vector data and JPEG compression algorithms for texture images;③ in order to communicate with Oracle8i database, a CyberCity GIS spatial database engine (SDE) is designed. On the basis of this SDE prototype a case study is done.     

A Hybrid Spatio-Temporal Data Model and Structure (HST-DMS) for Efficient Storage and Retrieval of Land Use Information

While the incorporation of geographical and environmental modeling with GIS requires software support for storage and retrieval of spatial information that changes over time, it continues to be an unresolved issue with modern GIS software. Two complementary approaches have been used to manage the spatial and temporal heterogeneity within datasets that use a field‐based representation of the world. Some researchers have proposed new data models that partition space into discrete elements on an as‐needed basis following each temporal event, while others have focused on eliminating duplication of repeated data elements present in spatio‐temporal information. It is proposed in this paper that both approaches have merit and can be combined to create a Hybrid Spatio‐Temporal Data Model and Structure (HST‐DMS) that efficiently supports spatio‐temporal data storage and querying. Specifically, Peuquet and Duan's (1995) Event‐based Spatio‐Temporal Data Model (ESTDM) and the Overlapping R‐tree (Guttman 1984, Tzourmanis et al. 2000) are utilized to create a prototype used to store information about urban expansion for the town of Carbondale, Illinois.