Spatiotemporal data model for network time geographic analysis in the era of big data

There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities.     

Directed movements in probabilistic time geography

This article studies probabilistic time geography for space–time prisms, that is, for situations where observers know the location of an agent at one time and then again at another time. In the intervening period, the agent would have moved freely, according to its time budget. The article demonstrates that the probability of finding the agent somewhere in the space–time prism is not equally distributed, so any attempt of a quantitative time geographic analysis must consider the actual probability distribution. This article develops, implements, and demonstrates this distribution. A preceding article introduced probabilistic time geography for space–time cones. With cones and prisms, the elementary space–time volumes of time geography are provided.     

GIS research to address tensions in geography

The rise of Geographic Information Systems (GIS) technologies has been producing powerful tools for spatial data processing, management, analysis, modeling, and visualization. While supporting many tasks, GIS technologies have evoked new thinking and advanced intellectual inquiries in geography. Technological advances in other fields often stimulate new research questions and lead to revolutionary discoveries. The Hubble telescope revolutionizes our understanding of the universe, and 3D digital microscopes transform our knowledge of the coordination among biological, neurological, and physiological systems in living organisms. Can GIS claim similar revolutionary effects on geography? The answer is much up for debate. With GIS technologies, geographic studies can explore a broader extent across multiple scales in space and time and tackle problems through increasingly complex spatial statistics, visual analytics, computation, simulation, machine learning, and artificial intelligence. Both the Hubble telescope and 3D digital microscope were built based on scientific research that subserves the technological advances for inquiries into space and life systems. Likewise, GIScience research innovates GIS methods that enable novel geographic investigations and therefore contribute to geographic knowledge production. For the sake of simplicity, the term GIS used here represents both GIScience and GIS technologies. This essay attempts to clarify the intellectual contributions of GIS to geography on the following two questions: (1) What novel geographic thinking is driven by GIS? (2) How may GIS provoke new geographic inquiries and knowledge? Building on Nystuen's notion of four tensions that trigger geographic questions, the essay discusses how GIS innovations mediate historical tension, space‐time tension, dimensional tension and scale tensions.     

Design and Usability of an Enhanced Geographic Information System for Exploration of Multivariate Health Statistics*

The multidimensional nature of many types of data in modern geography calls for creative and innovative approaches to their analysis. Statisticians have recently developed methods for exploring and visualizing large, multivariate datasets, but cartographers and geographers in general have only recently begun to integrate these methods for use with spatial and spatiotemporal datasets that are multivariate in character. This article will present an example of such an integration—an environment for visualization of health statistics—as a case study to demonstrate the philosophical and practical advantages of geovisualization systems for the exploration of complex spatiotemporal information. Emphasis is placed on the encouragement of creative thinking about geographic phenomena through the use of such data‐rich graphical tools.     

Design and Usability of an Enhanced Geographic Information System for Exploration of Multivariate Health Statistics

Abstract

The multidimensional nature of many types of data in modern geography calls for creative and innovative approaches to their analysis. Statisticians have recently developed methods for exploring and visualizing large, multivariate datasets, but cartographers and geographers in general have only recently begun to integrate these methods for use with spatial and spatiotemporal datasets that are multivariate in character. This article will present an example of such an integration—an environment for visualization of health statistics—as a case study to demonstrate the philosophical and practical advantages of geovisualization systems for the exploration of complex spatiotemporal information. Emphasis is placed on the encouragement of creative thinking about geographic phenomena through the use of such data-rich graphical tools.

     

行为地理学的学科定位与前沿方向

始自行为革命,行为地理学逐渐走向多元化的发展方向,不断扩展自身的理论框架和实践外延,反思并重新认识自身的意义,成为了人文地理学的重要组成部分。伴随着社会经济转型的深入,世界越来越向着多样化、个体性、动态化发展,人们的空间行为决策、选择的差异与个性越来越明显,空间与行为的交互越来越强,为行为地理学带来了新的发展机遇。论文通过梳理行为地理学的学科基础,提出行为地理学的学科定位与内涵外延,并指出行为地理学已经呈现出面向动态人地关系、面向个体生活质量及面向社会可持续发展3个前沿发展方向。在此基础上,论文对行为地理学面临的方法论、研究方法与跨学科的挑战进行讨论,并展望行为地理学的未来发展,以期为中国行为地理学的理论创新与实践探索提供启示。     

地理学在新冠肺炎疫情早期防控中的学术响应及展望

重大公共卫生突发事件如新冠肺炎等对区域人类活动有着深刻影响。作为以空间分析和人地关系为主要方法和对象的地理学,在疫情早期防控中的角色贡献以及未来趋势是迫切需要总结和讨论的重要议题。基于2020年1月20日~2月28日的文本数据,着重总结地理学者以及地理学视角下关于疫情的相关研究,地理学在疫情传播与扩散、区域规划与应急、数据与决策支撑等疫情早期防控方面做出了积极贡献,总结归纳了手机信令、百度迁徙数据等移动定位大数据与人工智能、数据挖掘、语义识别等新一代技术方法在疫情防控中发挥的支撑作用,反思提出未来应该在学科理论和防控措施方面,进一步优化风险预测模型、强化应急规划治理、加强国际合作及多学科数据交叉集成共享,从而提升应对重大公共卫生事件的科学性、主动性和高效性,为后疫情时期经济社会管理与空间治理提供科学支撑和依据。     

物联网时代信息地理研究的思考

近年来物联网在全球掀起巨大热潮。作为新一代信息技术,物联网不仅将给生产运行、经济和社会管理乃至个人生活带来极大影响,同时将会给地理学带来深刻变化,成为信息地理研究的重要对象。深入分析物联网对于地理学核心概念以及信息地理研究方法带来的影响,构建物联网时代信息地理研究的理论框架,主要包括:物联网构造了新的地理空间--现实地理空间与虚拟空间的统一体,推动人地关系的改善;物联网时代的信息实时收集与处理特征,使得空间结构、产品空间、行为空间发生重要变化,信息作为区位的影响因素将得到增强,城市交通、居住、工作和休憩功能空间受到影响,物联网从规范产业链和改变消费行为两个方面影响商业模式,人的环境感应能力增强,影响人们的空间感知和空间行为;基于物理世界的海量实时数据,信息地理研究方法发生变化,实证、时间维度、微观尺度等方面的研究将会增强。进而,系统性提出物联网时代信息地理的主要研究内容。     

地理计算及其前沿问题

地理计算是地理信息科学的核心内容之一, 主要研究地理信息科学的方法学问题, 内容 包括建模、算法、计算体系和一般方法学问题。本文介绍了地理计算的五个前沿问题: (1)地学数据 挖掘从地理学问题出发, 对各种数据作地理学的模型处理和结果计算以发现地理知识; (2)空间运 筹在地理学中的应用日益广泛, 它的算法更加简单严密、精度也更高; (3)多自主体系统模拟已经 成为地理学科学研究中除归纳和演绎之外的第三种重要研究方法; (4) 离散空间的定性计算是进 行地理空间计算的必要基础; (5)本体论的发展是地理信息科学乃至整个地理学发展的需要。     

大数据时代城市时空间行为研究方法

信息技术的快速发展带来了“大数据”时代的到来,改变了城市的空间组织和居民行为,并使得城市时空间行为研究方法面临变革。本文在总结传统城市时空间行为研究方法存在问题的基础上,对影响其变革的数据获取与处理技术进行梳理,重点从居民时空行为、城市空间及城市等级体系3个方面综述了国内外应用大数据进行城市时空间行为研究的最新进展,构建了基于大数据应用的城市时空间行为研究方法框架。本文认为,大数据时代城市时空间行为研究方法的变革主要取决于对反映居民时空行为的网络或移动信息设备数据的挖掘、处理及应用,但是还需要进一步推动相关学科间的交叉与融合,加强社交网站等网络数据在居民时空行为和城市空间研究中的应用,并指导城市规划编制与管理方法的创新。     

An Overview of Spatial Analysis of Emerging Infectious Diseases

Emerging infectious diseases (EIDs) are of increasing global concern, and quantitative geography can play an important role in integrating spatial data describing drivers of disease emergence and building models of EID risk. This article lays out the key issues of EIDs and describes problems and opportunities for integrative quantitative geography to inform on patterns of EIDs. Issues of data quality are highlighted, as are methods of spatial analysis and forms of research communication and visualization as they relate to the study of EIDs. Our review demonstrates that geography is critically needed in EID research, and many of the issues central to understanding and predicting EIDs are inherently of a geographical nature.     

Active Learning Strategies and Assessment in World Geography Classes

Abstract

Active learning strategies include a variety of methods, such as inquiry and discovery, in which students are actively engaged in the learning process. This article describes several strategies that can be used in secondary-or college-level world geography courses. The goal of these activities is to foster development of a spatial perspective in students through frequent analysis and interpretation of spatial data. Detailed examples of one particular technique, the “atlas warmup”, are included. Active approaches supplement expository teaching of standards-based geography concepts and current geographic issues. Assessment of the impact of these methods reveals the need for ongoing guided practice in the use of these skills.     

国内外情感地理研究热点、内涵及意义——基于文献计量与可视化

随着西方地理学的情感转向,以人为本的“情地关系”研究逐渐受到国内外学者的高度关注。基于文献计量法与可视化对1992—2020年主题为“情感地理”的265篇外文文献与248篇中文文献进行全面梳理、归纳,凝练出情感地理的研究热点、内涵和意义。结果发现,国内外情感地理经过近30年的研究,主题与内容不断拓展：国外侧重教育、政治、社会性别、儿童的情感地理成为研究热点,国内则侧重旅游和居民的地方感研究;研究内涵方面,国外学者不同学术领域专家对情感地理有不同的诠释,教育地理学家侧重教学互动关系,人类地理学家注重情感空间特征,文化地理学者强调情感与文化的联系。国内大多数学者则认为情感地理是揭示人、情感与地方三者之间的相互关系,着力研究不同地理空间的自然和人文特征对情感的影响;情感地理突出情感的时间性、空间性和社会性研究,关注人地关系“情地关系”、人际关系“情感传递”,将有温度的情感融入空间或区域,赋予地方新的使命。情感是社会关系的重要组成部分,研究其在教育、政治、社会性别、儿童、旅游和居民等方面都具有重要意义。     

地理学视角下城市复杂性研究综述——基于近20年文献回顾

城市作为组织结构复杂的开放人地地域系统,一直是地理学的研究核心之一。论文以2000—2020年相关文献为数据源,构建一套定量分析与定性认知相结合的文献分析判读体系,基于地理学视角从概念内涵、研究主题、技术方法等方面综述城市复杂性研究成果并开展讨论。过去20 a来,中国的城市复杂性研究逐渐从单尺度的格局、过程和机制研究转向于多尺度下复杂交互过程的集成与综合研究,并逐步形成了城市设施网络、城市人居环境、城市经济活动以及城市空间治理4个主要主题,在数据方法上逐步转向于空间技术及社会计算支持下的全景式全生命周期数据支撑的多维场景化分析。今后及未来一段时期,地理学视角下的城市复杂性研究需要进一步加强城市数字基础设施建设及全周期信息采集能力,加深对城市生态经济体系的综合测度及监控,增强跨区域发展机制影响下的城市流空间研究。     

定性GIS在时空间行为研究中的应用

定性GIS已经成为地理学混合研究方法的重要组成部分,通过扎根理论并与可视化结合、GIS和民族志整合等途径,对时空间行为研究产生了深远的影响。其通过文本或非文本质性材料与GIS地理特征的整合,形成了时空行为研究中独特的地理环境系统与空间机制分析,一个重要的前沿领域就是地理叙事在时间地理学研究中的应用。时间地理学是研究人类时空行为的重要视角,但由于对个体主观性及行为的社会文化因素的相对忽视等原因,受到了一定的质疑。近年来以GIS为代表的地理空间技术的定性分析与表达,为时间地理学融入质性分析提供了方法论基础。关美宝创建的基于GIS的地理叙事方法,通过借鉴叙事分析的一般方法尤其是三维叙事空间分析,结合时间地理学概念框架,开发了基于GIS平台的计算机辅助叙事分析组件(3D-VQGIS),实现了在GIS内可视化的、循环交互的叙事分析,为定性GIS发展中GIS与叙事分析方法的融合做出了贡献。将地理叙事方法用于时空行为研究,可以为时间地理学方法创造一个更便于理解与解释研究对象日常行为的地理环境,为其融入行为与主体的质性分析提供从数据整合、数据分析到解释与展示的一整套研究方法与具体操作工具。     

网络空间地理学的理论基础与技术路径（英文）

Cyberspace is a new spatial realm of activities involving both humans and data, and it has become a cornerstone of the national security of every country. A scientific understanding of cyberspace is essential for analyzing cyberspace incidents, governing cyberspace and ensuring cybersecurity. Accordingly, cyberspace has become a new field of geographic research in the Information Age. Against the backdrop of fierce international competition over cyberspace, there has been an urgent need to strengthen research between the fields of geography and cybersecurity, leading to theoretical and methodological innovations that have created the sub-discipline of cyberspace geography. Cyberspace geography(CG) extends geographical research from real spaces to virtual spaces, and its theoretical basis is the evolution of the traditional geographic human-land relationship theory into a human-land-network relationship theory. CG research includes constructing mapping relationships between cyberspace and real space, redefining the traditional geographic concepts of distance and regions for cyberspace, creating a language, models and methodologies for visually representing cyberspace, drawing maps of cyberspace, and researching the principles governing the evolution of cyberspace structures and behaviors. The technical methods of CG include collecting and integrating data on elements of cyberspace, visually representing cyberspace and conducting cyberspace situational and behavioral intelligence awareness. Intelligence awareness covers cyberspace situational status assessments, network hotspot event dissemination and traceability analysis, and network event situational simulations and risk predictions. CG offers new perspectives on the scientific understanding of cyberspace, the development of disciplines such as geography and cybersecurity, and the creation of national cybersecurity prevention and control mechanisms as well as a community of common future in cyberspace.     

面向国土空间优化的三生空间研究进展

解决经济高速增长、社会快速转型中存在的国土开发秩序混乱和资源环境代价沉重等问题是人文—经济地理学在区域可持续发展领域的重大科学命题。党的十八大报告将优化国土空间开发格局作为生态文明建设的首要举措,并提出“促进生产空间集约高效、生活空间宜居适度、生态空间山清水秀”,由此构成的“三生”空间成为构建空间规划体系、完善国土空间开发保护制度和各类尺度空间落实主体功能区规划的重要基础。本文围绕国土空间优化和区域可持续发展目标,对国内外“三生”空间相关文献进行系统梳理,紧紧围绕“三生”空间的数量配比和空间配置两个科学问题进行综述,按照精度深化和尺度细化的要求,集中在“三生”功能分类、空间识别、空间优化等内容,从而勾勒出三生空间研究的框架体系。今后应重视三生空间动态演化,促进各尺度适宜性评价的统一和整合,响应“多规合一”的实践需求,最终服务于国土空间格局优化。     

从实时定位、环境监测到神经生理：行为地理学技术发展前沿

方法与技术的前沿性是行为地理学的学科特色,技术视角的学科梳理有助于认识行为地理的自身价值与优势。论文回顾了实时定位、环境监测与神经生理3项技术的发展脉络,围绕行为背景、行为环境、行为体验的技术应用进行了综述,并总结了空间—行为互动、地理背景不确定性、批判神经地理的理论推进与批判反思;进一步构建了融合动态背景—精细环境—实时体验的全面技术框架,形成了从背景到环境再到体验的行为地理综合研究体系,并提出了神经生理技术融入行为地理学研究的理论提升方向。论文旨在贡献地理流动性背景下的行为地理学创新路径,服务于行为地理学的知识生产与理论发展。     

基于女性主义地理学视角的家庭暴力研究进展——超越公私二分法

人文地理学者通过家透视生活空间中的社会现象,西方人文地理学文化转向与女性主义研究兴起后,家庭暴力成为学者们关注的对象。在女性主义社会批判特征和地理学空间视角的双重影响下,女性主义地理学家着眼女性的空间经历及情感体验,聚焦女性在家庭中的暴力问题。论文首先介绍“家庭暴力”的概念和公私二分法,指出其中的空间隐蔽性,据此引入女性主义地理学的研究路径,通过分析家庭空间的意义建构,以及容忍家庭暴力存在的更广泛的地理环境,超越空间的公私二分法探讨家庭暴力。基于对国外相关研究的梳理,归纳出家庭、社区/邻里、国家和全球3种尺度分析家庭暴力的地理研究。通过物质、功能、象征维度的家庭空间性分析揭示性别权力在空间上对女性的控制和压迫;运用物质决定论逻辑和社会-文化逻辑2种视角解读家庭暴力存续的社区环境特征及其内在对女性的政策和制度排斥;分析家庭暴力与恐怖主义、军事战争的联系,将家庭暴力议题推向政治地理领域。     

Leveraging parallel spatio-temporal computing for crime analysis in large datasets: analyzing trends in near-repeat phenomenon of crime in cities

ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.