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.     

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.     

环境监测信息空间表征技术研究与应用

随着环境问题的日益凸显及公众对环境问题的日益关注,如何将污染分布及发生规律、环境质量状况及变化趋势以科学、准确、直观的方式进行展示并以浅显易懂的方式传递给广大公众,是摆在环境管理者面前的一个问题.本文提出了环境监测信息空间表征定义,并介绍了基于GIS、大数据技术的环境监测信息空间表征的主要形式,包括:①点数据的空间表征;②线数据的空间表征;③面数据的空间表征;④三维可视化空间表征;⑤随时间变化的空间信息表征,以及各空间表征方法在环境监测中的应用.     

空间信息服务时态数据的管理与应用

本文面向当前空间信息应用的实际需求,以传统GIS为基础,研究建立实用的、易于实现的集矢量与栅格数据为一体的时空数据模型,增加GIS对时态属性的管理和操作。本文研究解决了时态拓扑构建的关键技术,采用面向对象方法开发了一套时态空间数据库管理系统,实现了时空数据的采集、存储、查询和显示,并以中国多个历史时期的行政界线为基础数据,进行了时空数据模型的应用研究,为TGIS发展探索了一条实用的技术路线。     

GIS分析中的空间数据不确定性问题

摘要：地理信息系统使用参照空间、时间和属性的多维坐标来描述空间现象,而所有的空间模型的表示方法都存在着不确定性问题,并通过GIS的分析操作而传播。从空间数据质量、精度和应用的量级概念等方面探讨了空间数据不确定性问题的由来和发展,认为关注不确定性和误差应从“适合使用’’出发。     

一种高时空分辨率NDVI数据集构建方法-STAVFM

ETM NDVI可以用来在30m的尺度上开展植被的监测,然而在Landsat卫星16天的重访周期和云污染等因素的影响下,常常会在相当长的一段时间内无法获取有效的ETM NDVI数据,给这一尺度下的植被动态监测带来了一定困难。相比之下,MODIS虽然在空间上只有250m分辨率的NDVI产品,却可以每天进行相同区域的监测。针对ETM空间分辨率高和MODIS时间分辨率高的特点,本研究选择实验区,基于对STARFM方法的改进,构建不同时空分辨率NDVI的时空融合模型-STAVFM,使用该模型对ETM NDVI与MODIS NDVI融合,构建了高时空分辨率NDVI数据集。研究结果表明,通过MODIS NDVI时间变化信息与ETM NDVI空间差异信息的有机结合,实现缺失高空间分辨率NDVI的有效预测（3景预测NDVI与实际NDVI的相关系数分别达到了0.82、0.90和0.91）,从而构建高时空分辨率NDVI数据集。所构建的高时空分辨率NDVI数据集在时间上保留了高时间分辨率数据的时间变化趋势,空间上又反映了高空间分辨率数据的空间细节差异。     

A Spatio‐Temporal Graph Model for Marine Dune Dynamics Analysis and Representation

Defining a model for the representation and the analysis of spatio‐temporal dynamics remains an open domain in geographical information sciences. In this article we investigate a spatio‐temporal graph‐based model dedicated to managing and extracting sets of geographical entities related in space and time. The approach is based on spatial and temporal local relations between neighboring entities during consecutive times. The model allows us to extract sets of connected entities distant in time and space over long periods and large spaces. From GIS concepts and qualitative reasoning on space and time, we combine the graph model with a dedicated spatial database. It includes information on geometry and geomorphometric parameters, and on spatial and temporal relations. This allows us to extend classical measurements of spatial parameters, with comparisons of entities linked by complex relations in space and time. As a case study, we show how the model suggests an efficient representation of dunes dynamics on a nautical chart for safe navigation.     

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。     

面向交通地理信息时空特征描述的Spatial-UML研究

空间信息系统建模的多样性、主流信息技术的高度集成性以及逐渐变复杂的系统体系都使得软件和数据库设计者向可视化建模的主流方向发展。分析面向地理信息时空特征描述而建立的空间可视化语言插件(SpatialPVLs),并基于可视化建模技术标准,应用统一建模语言(UML)内置的扩展机制实现了针对地理信息时空特征描述的扩展。UML和SpatialPVLs的集成过程定义了面向地理信息时空特征描述的可视化建模语言,即Spatial-UML。最后,以城市交通模拟地理信息系统(GIS)数据概念模型设计为实例,验证Spatial-UML的适用性和扩展性,建立一个可以满足不同领域用户访问和理解的互协作建模架构,实现交通地理对象的空间、时态和时空特征的可视化标准描述和表达。     

A Lineage Meta-Database Approach Toward Spatial Analytic Database Optimization

This work demonstrates how increasing levels of intelligence can be added to commercial geographic information systems. The lineage-knowledge representation introduced in an earlier article (Lanter 1991) provides a basis for encoding the logic applied within specific spatial analytic applications. This knowledge is general, reusable and extendible to solving many significant problems in geographic information processing. In this study, the lineage-knowledge representation is applied to automatically differentiate between source and derived layers, pick an optimal spatial analytic database configuration, and generate applications tailored to the contents of the spatial analytic database.     

Delaunay三角网支持下的空间场表达

不规则三角网TIN本质上属于基于场的空间数据模型,然而在GIS领域,通常将其局限于DTM数字地形模型的表达中,没有象规则栅格模型那样在平面实体及实体关系表达中发挥足够的作用。针对这一局限性,仿照规则格网的栅格数据模型,应用DELAUNAY三角网工具,建立一种面向平面空间场表达的形式化数据模型。应用三角形的3种基元:顶点、边、三角形面表达空间点、线、面目标,定义该模型上的3种操作:扩充、收缩与骨架化,并进一步推广到序惯操作与条件操作。在几个应用实例基础上,分析该模型在空间邻近关系表达上可发挥重要作用。     

Temporal logic and operation relations based knowledge representation for land cover change web services

Providing land cover spatio-temporal information and geo-computing through web service is a new challenge for supporting global change research, earth system simulation and many other societal benefit areas. This requires an integrated knowledge representation and web implementation of static land cover and change information, as well as the related operations for geo-computing. The temporal logic relations among land cover snapshots and increments were examined with a matrix-based three-step analysis. Twelve temporal logic relations were identified and five basic spatial operations were formalized with set operators, which were all used to develop algorithms for deriving implicit change information. A knowledge representation for land cover change information was then developed based on these temporal logic and operation relations. A prototype web-service system was further implemented based on OWL-DL. Both online access and conversion of land cover spatio-temporal information can be facilitated with such a web service system.     

The Nature of Uncertainty in Historical Geographic Information

While the presence of uncertainty in the geometric and attribute aspects of geographic information is well known, it is also present in temporal information. In spatiotemporal GIS databases and other formal representations, uncertainty in all three aspects of geography (space, time, and theme) must often be modeled, but a good data model must first be based on a sound theoretical understanding of spatiotemporal uncertainty. The nature of both uncertainty inherent in a phenomenon (often termed indeterminacy) and uncertainty in assertions of that phenomenon can be better understood through the Uncertain Temporal Entity Model , which characterizes the cause, type, and form of uncertainties in the spatial, temporal, and attribute aspects of geographic information. These uncertainties are the result of complexities and problems in two processes: the process of conceptualization, by which humans make sense of an infinitely complex reality, and measurement, by which we create formal representations (e.g. GIS) of those conceptual models of reality. Based on this framework, the nature and form of uncertainty is remarkably consistent across various situations, and is approximately equivalent in the three aspects, which will enable consistent solutions for representation and processing of spatiotemporal data.     

The Role of Knowledge Representation in Geographic Knowledge Discovery: A Case Study

With the advent of massive, heterogeneous geographic datasets, data mining and knowledge discovery in databases (KDD) have become important tools in deriving meaningful information from these data. In this paper, we discuss how knowledge representation can be employed to significantly enhance the power of the knowledge discovery process to uncover patterns and relationships. We suggest that geographic data models that support knowledge discovery must represent both observational data and derived knowledge. In addition, knowledge representation in the context of KDD must support the iterative and interactive nature of the knowledge discovery process to enable the analyst to iteratively apply, and revise the parameters of, specific analytical techniques. Our approach to knowledge representation and discovery is demonstrated through a case study that focuses on the identification and analysis of storms and other related climate phenomena embedded within a spatio‐temporal data set of meteorological observations.     

GIS中面向对象时空数据模型

由于当前的地理信息系统软件难以处理时态现象，时态数据模型已忧为ＧＩＳ领域的一个研究热点。许多学者提出了多种时态数据模型。本文作者在提出了矢量栅格一体化的面向对象数据模型之后，再一次对时态问题进行了分析研究，净面向对象的数据模型扩充到时间维。有三种方法表达空间对象的历史变化。第一种是将版本信息记录在关系表上；第二种是将版本信息标记在记录上；第三种是将版本信息标记在属性上。本文采用面向对象的方法，将版     

基于小波分析的地貌多尺度表达与自动综合

基于小波多分辨率分析原理，给出了一种尺度依赖的地表形态抽象与表达方法。基于该方法研究了多尺度的地貌自动综合，提出了利用小波系数的范数比作衡量相应尺度综合程度的数量化指标，并结合实例予以说明。     

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 .     

城市地理时空大数据管理与应用平台建设技术和方法研究

针对城市地理时空数据的专业类别多、数据格式多、数据分散等诸多特性,提出了栅格式数据、图形式数据、要素式数据、类GIS数据、ArcGIS数据5大类地理时空数据的管理方案。采用基于富客户端的地图增强技术、基于时间帧的时空数据动态表达技术和空间数据及平台功能自扩展定制技术,对城市地理时空大数据管理与应用平台进行了总体设计,开发了集管理与应用于一体的资源创建与管理系统、信息集成共享系统、数据交互应用系统,实现了城市地理时空大数据的管理与应用的高效性。本文提出的技术方法已在长沙市规划交通勘测信息集成管理与应用共享平台项目建设中得到验证,为城市地理时空大数据的集成管理和共享应用提供了技术经验。