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.     

一种基于对象和快照的混合地表覆盖时空数据存储模型

时空数据模型是数据库和时空数据分析研究热点之一。由于时空数据变化类型多、分析计算复杂及应用范围广,一种观点认为建立通用的时空数据模型具有高度复杂性。本文针对地表覆盖变化时空数据建库和时空分析应用需求,提出了基于对象和快照的混合时空数据模型。该模型用面向对象描述地表覆盖的斑块对象时空过程,组织管理斑块对象时空事件和空间、属性信息,同时用快照描述地表覆盖整体时空分布,组织管理栅格快照,两者通过基于时间和空间位置的逻辑关联关系形成混合模型。模型在表达对象自身变化的时空事件类型基础上,增加了不同分类对象之间互相转变的时空事件表达。该模型既可以用于对地表覆盖历史观测数据组织存储建库,又可以用于支持时空统计分析、时空演变模拟和时空数据挖掘。通过对黑龙江地区地表覆盖时空数据建库、查询检索、整体格局演变分析和斑块变化时空过程检索与表达的试验,验证了模型的有效性。     

The Impact of Hurricanes on Crime: A Spatio-Temporal Analysis in the City of Houston,Texas

The impact that natural disasters have on crime is not well understood. In general, it is assumed that crime declines shortly after the disaster and slowly increases to pre-disaster levels over time. However, this assumption is not always confirmed by the few empirical studies that have been conducted to date. In this paper we analyze the impacts that Hurricane Rita, and for the purpose of comparison, Hurricane Katrina had on the temporal and spatial distributions of reported crimes in the city of Houston, TX. Crime data were collected before, during, and after the landfall of both hurricanes. The modeling part of this paper focused on primarily spatio-temporal and local regression models at the local scale. Spatio-temporal models were applied to identify potential spatio-temporal crime clusters associated with the hurricanes. A local regression model in the form of a geographically weighted regression was applied to explore relationships between crime clusters and possible underlying factors leading to the creation of said clusters.

The results show that while Hurricane Katrina did not have any apparent impact on crime, Hurricane Rita led to a significant short-term increase in burglaries and auto thefts. The post important result was the identification of a large, highly significant spatio-temporal burglary cluster located in the northeastern part of Houston. This cluster lasted from a few days before to a few days after the landfall of Hurricane Rita. Empirical evidence was found that the mandatory evacuation order that was issued prior to the arrival of Hurricane Rita led to a short-time spike in burglaries. It was assumed that these crimes were committed by individuals who did not follow the evacuation order, but instead burglarized the residences of individuals who did evacuate. No mandatory evacuation order was issued for Hurricane Katrina. Altogether, three variables including the percentage of African Americans, the percentage of persons living below the poverty level, and the distance to the nearest police station was identified as having a positive relationship with the increase in burglaries associated with Hurricane Rita     

时空过程对象的LULC时空演变分析算法

地理时空变化是地理学研究的重要内容之一，如何用计算机技术来表达空间数据的时空变化独具前瞻性。从揭示LULC时空演变过程和挖掘时空演变规律出发，讨论了基于地类图斑的时空演变过程类型与判定方法，并构建了一种基于地类图斑的时空变化分析算法。通过对抚仙湖流域近40年来LULC时空演变分析，验证了算法的可靠性与有效性。表明该方法可用于地表覆盖等地理要素的时空变化过程分析，能较好地揭示地理要素及其属性在时间轴上的改变过程。     

支持地图综合的面状目标约束Delaunay三角网剖分

针对多边形面状目标的综合问题,建立了二维空间中约束Ｄｅｌａｕｎａｙ三角网剖分结构,融入多边形的环、岛屿、边界、顶点的描述,通过形式化条件检索,在该结构上提取二维空间中各种感兴趣的由剖分三角形组成的区域,用于支持地图综合中邻近多边形的搜索、多边形弯曲部位的识别、冲突关系探测、多边形合并等操作。并对基于骨架线的图结构建立、分枝宽度计算等几何问题进行了详细讨论,指出了其在诸如双线河中轴化、街道中轴线网络模型建立、多边形合并中的邻近关系分析、面状目标注记自动定位领域的支持作用。     

面向地理信息大数据的时空事件关系可视化分析框架

不同类型的地理信息大数据蕴含了丰富的时空关系，反映个体或者群体时空事件之间的变化模式，在资源、环境、交通等领域的智慧应用中起到关键性作用。然而，地理信息大数据拥有的多尺度和多语义特性，在挖掘地理信息大数据的时空关系时会存在许多困难。如何有效地构建多尺度多语义时空关系，并直观地表达这些时空关系是一个重大挑战。本文设计了一种时空事件关系可视化分析框架，通过定义事件间时空关系的描述，设计了一种多视图协同的可视化分析方法，结合时空关系的可视化协同交互，实现地理信息大数据时空事件可视分析。基于时空轨迹数据，通过试验说明该方法可以探寻时空事件及背景间的时空关系，实现时空事件的交互可视分析。     

Toward a Differential Calculus for Temporal Map Analysis

Investigators in many fields are analyzing temporal change in spatial data. Such analyses are typically conducted by comparing the value of some metric (e. g., area, contagion, or diversity indices) measured at time T₁ with the value of the same metric measured at time T₂ . These comparisons typically include the use of simple interpolation models to estimate the value of the metric of interest at points in time between observations, followed by applications of differential calculus to investigate the rates at which the metric is changing. Unfortunately, these techniques treat the values of the metrics being analyzed as if they were observed values, when in fact the metrics are derived from more fundamental spatial data. The consequence of treating metrics as observed values is a significant reduction in the degrees of freedom in spatial change over time. This results in an oversimplified view of spatio-temporal change. A more accurate view can be produced by (1) applying temporal interpolation models to observed spatial data rather than derived spatial metrics; (2) expanding the metric of interest's computational equation by replacing the terms relating to the observed spatial data with their temporal interpolation equations; and (3) differentiating the expanded computational equation. This alternative, three-step spatio-temporal analysis technique will be described and justified. The alternative technique will be compared to the conventional approach using common metrics and a sample data set.     

基于植被分布特征的森林景观建模方法

在虚拟地理环境中如何快速地生成具有特定空间格局的森林景观是一个具有挑战的问题。现有的研究主要以模拟或随机的方式确定树木的位置,但难以反映每个树种的分布特征。本文提出了一种基于图的中性景观模型,根据指定的景观指数生成特定组成结构和空间配置的森林景观。模型将格网随机划分为若干不规则的区域,并将其转化为对应的区域邻接图,通过源节点的受限生长生成特定大小和形状的图斑。相比其他中性景观模型,该模型在可控性和灵活性上具有优势,能对每种类型的景观特征分别进行表达。最后根据模型生成的森林景观确定树木的位置与种类。本方法不仅能为植被场景的可视化提供合理的植被分布,而且能反映森林景观的空间分布特征,为虚拟森林环境中的林业规划决策以及植被分布规律认知提供一定的支持。     

基于VB + MapObjects的土地利用动态变化更新与实现

在土地利用动态监测中,地理信息系统是实现空间数据动态更新和分析的主要技术手段。本文分析了土地利用动态变化更新模式、土地利用图中图斑的特点以及图斑对象的更新模型,结合土地利用动态变化更新中的GIS空间分析方法,给出了土地利用动态变更中的图斑模型,采用VB+MapObjects进行了组件式GIS二次开发实现。经过实际数据的检验,证明了程序具有很好的稳定性、可靠性和较高的效率。     

一种基于属性水平版本结构的时空数据模型

以属性水平版本结构为理论基础,在空间数据表中,面状地物类表和线状地物类表是有效时间(Tv)和数据库时间(Td)的载体,事务时间反映版本创建时间(Tc),并将结点和弧段的版本改变记录到它们所属的面状地物类表中;属性数据表中,区分记录属性的连续变化与不连续变化。数据模型既体现了版本信息和时间要素,又减少了数据冗余。     

The cognition of change: scaling deformations in mind and spatial theories

The dynamics of the earth and its inhabitants have become a core topic and focus in research in the spatial sciences. The spatio-temporal data avalanche challenges researchers to provide efficient and effective means to process spatio-temporal data. It is of vital importance to develop mechanisms that allow for the transition of data not only into information but also into knowledge. Knowledge representation techniques from artificial intelligence play an important role in laying the foundations for theories dealing with spatio-temporal data. Specifically, the advances in the area of qualitative spatial representation and reasoning (QSTR) have led to promising results. Categorical distinctions of spatio-temporal information identified by QSTR calculi potentially correspond to those relevant to humans. This article presents the first behavioral evaluation of qualitative calculi modeling geographic events associated with scaling deformations of entities, that is, changes in size by either expansion or contraction. Examples of such dynamics include a lake flooding its surroundings or an expanding oil spill in the ocean. We compare four experiments using four different semantic domains. Each domain consists of two spatially extended entities: one entity is undergoing scaling deformations while the other is static. We kept the formal QSTR characterization, which are paths through a topologically defined conceptual neighborhood graph, identical across all semantic domains. Our results show that for geographic events associated with scaling deformations (a) topological relations are not equally salient cognitively; (b) domain semantics has an influence on the conceptual salience of topological relations.     

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。     

一种基于特征-语义的时空数据组织方法

在全面研究时空数据模型理论及构建方法的基础上,本文采用面向特征的数据模型构建方法结合时空语义思想,并引入无缝时空理念,探讨了一种基于特征的无缝时空数据模型构建方法。该模型将地理时空过程特征抽象为特征对象、特征事件、特征过程,不仅能够实现地理实体的空间数据组织及复杂拓扑分析,而且,通过描述特征事件、特征过程及其相互关系实现时空语义表达,进而实现海量信息存储以及高层次时空分析,也为通用性时空数据模型的构建提供了一种新思路。     

基于灰集的不确定性时空数据模型

不确定性处理是时空数据库面临的新问题。其研究的首要任务是对不确定时空对象进行建模,研究时空不确定性的表示和存储,进而设计离散模型实现数据库系统。提出了建立在灰集理论上的时空数据抽象模型,适合处理部分已知部分未知的不确定对象。首先给出了抽象数据类型的定义,包括建立在灰集理论上的基本数据类型,空间数据类型和时空数据类型;随后对不确定时空分析操作进行了简单的定性分析;最后给出不确定性时空查询的表达方式。     

基于加权图的地籍时空数据描述模型研究

以计算机通用的数据结构——图为基础，研究了基于加权图的时空数据组织策略，为表达时空语义提供了一种形式化的描述方法，并分析了以该模型为中间件实现不同时空模型转换的应用前景。     

基于特征的空间数据模型研究

与传统的基于分层的数据组织方式相比,基于特征的空间数据组织方式更符合人们认识和分析现实世界的模式,有利于完整而精确地描述地理现象。本文详细论述了基于特征的空间数据组织的相关概念,对基于特征的空间数据模型进行了探讨。     

基于网络和图的时空智能——概念、方法和应用

当前时空智能(SpaceTimeAI)和地理空间智能(GeoAI)已是热门的话题,该研究领域旨在将计算机科学的最新方法(如深度学习)应用于地理空间问题。虽然深度学习方法因其对栅格数据的自然适用性而在图像处理中取得了巨大成功,但仍未广泛应用于其他空间和时空数据类型。本文提出使用网络和图作为SpaceTimeAI或GeoAI的基本结构的倡议,并将其应用于城市研究中。相比于基于网格的表达,基于网络的结构更加精确和实用。图能实现对点、线、面/多边形/网格和网络等多种空间结构的表达。本文通过时空预测、聚类和时空优化等常用时空分析方法展示基于网络和图的时空智能分析的优势,并介绍其在交通出行、警务和公共卫生等领域的应用。     

基于位置点统计的时空异常检测与分析

探讨了位置数据异常分析的一种新思路,给出了面向异常的时空表达模型,建立了基于区域位置点统计的异常检测和分析框架,探寻异常在事件影响下的时空发展趋势和分布特征。通过纽约两个月的出租车出行数据的实验分析验证了框架的有效性,并发现一些有趣的规律,为公共安全、交通管控应急、城市功能区分析等提供指导信息。     

点集数据不规则形状时空异常聚类模式挖掘研究

传统扫描统计方法在进行时空异常聚类模式挖掘时,受扫描窗口形状的限制,不能准确地获取聚类区域形状。提出一种改进的不规则形状时空异常聚类模式挖掘方法stAntScan。新方法基于26方位时空邻近单元格构建时空邻接矩阵,再对蚁群最优化扫描统计方法进行改进,使其能适应三维大数据量的时空区域扫描。模拟数据和真实微博签到数据的实验证明,stAntScan能有效地识别时空范围内的不规则形状异常聚类,并且准确性较经典的SaTScan方法高。     

A computational approach for the analysis of changes in polygon distributions

 This paper develops a computational method for analyzing changes in polygon distributions. Unmovable polygons that change discontinuously without explicit functional linkage information are discussed. Six types of primitive events are used to describe the change: 1) generation, 2) disappearance, 3) expansion, 4) shrinkage, 5) union, and 6) division. The change of polygon distributions is decomposed into a combination of these events. A computational procedure for deducing a set of events from polygon distributions of two times is proposed. The method is applied to the analysis of the spatial competition between the major and small chains of convenience stores in Tokyo, Japan. Some empirical findings are shown. Received: 3 August 2000 / Accepted: 6 February 2001