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.     

基于特征的时空数据模型用于地籍变更的探讨

传统的基于专题地理分层的GIS数据模型在数据组织 ,数据共享及复杂的空间分析方面存在明显的不足 ,认为发展新一代的基于特征的时空模型成为必然。本文结合实践中地籍变更的特点 ,提出了基于特征变化状态的时空数据模型。该模型保持了地理现象的完整性 ,实现了时空专题信息的有机集成 ,有利于发展复杂的面向目标的定向分析。     

地理信息系统专业实践教学规划与设计

针对当前地理信息系统专业的发展现状和社会对GIS领域的人才需求,提出了地理信息系统专业实践教学规划的指导思想,构建了本专业实践教学体系的基本框架,设计了本专业实践教学的层次结构。     

一种时空过程的梯形分级描述框架及其建模实例

以对象建模视图和事件模型为基础的自底向上的时空过程表达方法,缺少对地理时空现象的显式定义,在时空因果链的细化表达方面存在不足。本文设计一种时空过程的梯形分级描述框架STP-TRAP,对时空过程进行自顶向下的显式化建模和集成时空因果链的分级描述,并在事件模型基础上,通过引入约束关系描述扩展时空因果链的表达模式。土地利用变迁过程建模实例与土地利用管理信息系统的设计和实现证明,该框架对土地利用变迁时空过程表达效果较好,为土地利用变更数据管理提供了新的思路。     

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.     

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.     

网络空间同位模式的加色混合可视化挖掘方法

同位模式挖掘是空间数据挖掘的热点问题之一,应用领域广泛。已有的同位模式挖掘方法一般采用统计或数据挖掘的方式,要求对复杂的数学公式、算法及相关参数等有深刻的理解,主要针对同质的欧式空间中地理现象。而城市空间中人为地理现象大多发生在网络空间,鉴于此,本文提出了一种网络空间同位模式可视化挖掘方法。该方法利用视觉语言表达网络空间现象之间的影响和交互作用。首先,利用网络空间核密度估计表达网络空间现象的分布情况和影响范围,为网络空间现象的同位模式挖掘提供支持,并建立单个地理现象分布情况与颜色之间的映射;然后基于色光加色混合原理获得两个地理现象相互影响的认知,借以挖掘空间同位模式。本文提出的方法属于形象思维,具有直观,形象和易感受等特点。     

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。     

Dynamic GIS Case Studies: Wildfire Evacuation and Volunteered Geographic Information

Incorporating the temporal element into traditional GIS is a challenge that has been researched for many years and has many proposed solutions. The implemented system "Extended Dynamic GIS" or EDGIS is based on the "geo-atom" and Space Time Point (STP). EDGIS provides a platform for spatiotemporal data representation, storage, and query in order to address the need for a dynamic GIS to manage complex geographic data types. The system has the capability of executing spatiotemporal object interaction queries (OIQs) such as crossing and coincidence of field-objects and object-fields. In this article existing dynamic GIS analysis techniques are further improved and enhanced through exploration of more in-depth case studies. Further examined here are applications to wildfire evacuation modeling and travel scenarios of urban environments with individuals providing volunteered geographic information (VGI). The EDGIS platform provides a means for interacting with a range of dynamic geographic phenomena. The areas of transportation, location based services (LBS), hazards, and geo-sensor networks provide challenges intertwined with the above applications as well as additional challenges pertinent to the ongoing GIScience research topic of spatiotemporal GIS. Using EDGIS to explore the described case studies of wildfire evacuation as well as VGI provides the advancements described above and demonstrates implemented uses for dynamic GIS.     

Simulating Complex Adaptive Geographic Systems: A Geographically Aware Intelligent Agent Approach

The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information, knowledge structures, and learning processes are needed for modeling intelligent agents situated within geographic systems. The representation of these agents requires the integration of agent-based models, machine learning, and GIS. Existing software packages for agent-based modeling, however, often provide insufficient support for this integration. The agent-based simulation package presented here is specifically designed to achieve such integration by assisting the development of agent-based models from the simulation framework. Object-oriented modeling techniques were used to implement this simulation package, which includes four modules: simulation, visualization, learning, and geoprocessing. In particular, the learning and geoprocessing modules facilitate the representation of adaptive behavior in agents within spatially explicit environments. The utility of the agent-based simulation package is illustrated using two simulation models: one of adaptive elk behavior and another of pedestrian movement. The successful design of the simulation models suggests that the modeling framework with the supporting software package is well suited to the resolution of complex adaptive geographic problems.     

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.     

地理学视角下测绘地理信息再透视

系统回顾了地理信息系统产生以来地理信息内涵发展与拓展的主要历程,指出地理信息的定义一直是在"空间+属性"的地图信息基本框架下逐步扩展,其发展历程经历了地图GIS、语义GIS、时空GIS和大数据GIS 4个不同的阶段,但仍无法满足时空大数据的分析和应用需求。从地理学研究的对象和内容出发,对地理学所需要的"地理信息"的内涵和外延进行了系统的梳理总结,提出了涵盖"空间定位""语义描述""属性特征""几何形态""演化过程""要素相互关系"的地理信息六要素表达模型。在地理定律和地理规律的指导下,面向地理现象空间分布、时空格局、演化过程、相互作用机理的集成表达、系统分析和高效管理,设计了六要素集成表达的几何代数统一GIS数据模型、地理规律与相互作用驱动的新型GIS数据结构、非结构化时空数据组织与存储等关键技术,为测绘地理信息走向地理科学信息提供了另一个理论基础与技术方法支撑,有助于提升GIS对地理格局、演化过程和要素相互作用等地理规律的组织、管理、表达和分析能力。     

Analyzing Cognitive Conceptualizations Using Interactive Visual Environments

The conceptualization of spatio-temporal information is an interdisciplinary research area. The focus of this article is on human conceptualizations of spatio-temporal geographic phenomena (also referred to as events). Identifying and understanding human conceptualizations is a crucial component in defining the semantics of spatio-temporal information. However, most research focuses primarily on how humans imbue dynamic phenomena with meaning on a general level. In contrast, this article is concerned with contextual factors (specifically: individual differences) that are too often neglected in general theories and in the analysis of behavioral data. In other words, we are interested in individual or group strategies of participants that are not detected by classical analysis methods. Research on individual difference is gaining widespread attention in cognitive and spatial sciences and it is time to consider individual differences in the area of conceptualizing spatio-temporal information. To understand individual differences in behavioral data on how people conceptualize events, we have developed illustrative software and have combined them with established similarity measures. We demonstrate the feasibility of our approach, its usefulness in analyzing behavioral data, and results that can be obtained through this individualized analysis by reanalyzing four sets of experimental data we previously collected.     

An Event‐driven Spatiotemporal Data Model (E‐ST) Supporting Dynamic Expression and Simulation of Geographic Processes

The wide use of various sensors makes real‐time data acquisition possible. A new spatiotemporal data model, the Event‐driven Spatiotemporal Data Model (E‐ST), is proposed to dynamically express and simulate the spatiotemporal processes of geographic phenomena. In E‐ST, a sensor object is introduced into the model as a flexible real‐time data source. An event type that is generating and driving conditions is registered into a geographic object, so an event can not only express spatiotemporal change in a geographic object, but also drive spatiotemporal change in some geographic objects. As a dynamic GIS data model, the E‐ST has five characteristics – Temporality and Spatiality, Real‐time, Extendability, Causality, and Realizability. Described and realized in UML, a test‐case deployment demonstrating the impact of urban waterlogging on traffic confirms that a spatiotemporal change process in a geographic phenomena is expressed and simulated by this model. Summarizing this work, four directions for future research are outlined.     

面向对象技术在GIS数据建模中的应用

本文介绍了几种空间数据模型以及传统数据模型的不足,提出了面向对象的数据模型,并以公交数据建模为例说明了面向对象技术在GIS数据建模中的应用。     

基于GeoServer的移动GIS旅游系统设计与实现

在对移动GIS技术和框架分析的基础上,选取GeoServer地理信息发布平台,进行移动GIS旅游系统功能设计;采用OGC提出的空间数据互操作规范WMS、WFS实现地理信息数据交换;以七台河旅游数据作为专题数据,实现移动端旅游景点查询与语音导游系统。     

Modeling the spread of spatio-temporal phenomena through the incorporation of ANFIS and genetically controlled cellular automata: a case study on forest fire

Abstract

Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth. Spread modeling, which is one of the most helpful analyses in the geographic information system (GIS), plays a prominent role in meeting this objective. This study proposes a new model that considers both aspects of static and dynamic behaviors of spreadable spatio-temporal in cellular automata (CA) modeling. Therefore, artificial intelligence tools such as adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) were used in accordance with the objectives of knowledge discovery and optimization. Significant conditions in updating states are considered so traditional CA transition rules can be accompanied with the impact of fuzzy discovered knowledge and the solution of spread optimization. We focused on the estimation of forest fire growth as an important case study for decision makers. A two-dimensional cellular representation of the combustion of heterogeneous fuel types and density on non-flat terrain were successfully linked with dynamic wind and slope impact. The validation of the simulation on experimental data indicated a relatively realistic head-fire shape. Further investigations showed that the results obtained using the dynamic controlling with GA in the absence of static modeling with ANFIS were unacceptable.     

虚拟地理环境认知与表达研究初步

分析了地理学的地理环境与当前地理信息技术中的地理空间两者概念之间的差异,探讨了地图与地理信息系统空间认知的发展及特点,初步研究了虚拟地理环境认知与表达的对象、特征与主要内容。从基于虚拟地理环境的地理认知和基于地理认知的虚拟地理环境表达两个层面分析了虚拟地理环境的认知与表达;指出虚拟地理环境的认知与表达研究不仅需要进一步发展地理空间认知理论和方法,还需要拓展对地理过程及人类行为的认知与表达理论和方法研究;并着重探讨了地理过程的表达和人类行为的模拟,指出当前虚拟地理环境认知与表达研究的关键内容。