Visualizing Motion: A Framework for the Cartography of Movement

可视化运动：运动制图框架

• 批准号: 1853681
• 负责人: Somayeh Dodge
• 金额: $ 32.88万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1853681&HistoricalAwards=false
• 关键词: Visualizing; Motion; Framework; Cartography; Movement

This project will examine how motion as a phenomenon, with complex space and time dimensions, is effectively represented in geographic visual displays. It will develop visualization methods and tools to map movement patterns and interaction between individuals. These tools are essential for hypothesis generation and visual communication for studying a variety of applications related to social and ecological systems. Vast amounts of information on bodies and objects in motion is now collected at very high spatial and temporal resolutions. These data have the potential to inform critical areas related to global movements of humans and goods, disease outbreak, impact of transportation changes on urban traffic, or effects of human activity on endangered species. Effective visual representations of motion are needed to reveal and communicate complex patterns and processes of societal importance. This project will contribute insights into how humans perceive movement patterns and advance knowledge on the effectiveness of different cartographic techniques in mapping interaction in motion. The theory, methods, and tools developed by this project can be used broadly to map and study movement across diverse disciplines such as geographic information science (GIS), ecology, transportation, and health. Through collaboration with industry, this study will bridge the gap between academic research and industry by contributing new cartographic techniques to existing commercial GIS software products which are used by researchers, policy makers, students, and others worldwide. Undergraduate and graduate students will be trained for research in STEM, partnering with industry, writing scientific publications, and developing geographic visualization tools. The visualization methods and tools will be made publicly available and used for training students to develop maps in motion through classroom settings and outreach activities.This research will create a new theoretical framework for the cartography of movement and test it on examples taken from movement ecology and human mobility. It will investigate two overarching research questions: (1) What are fundamental visual principles and design elements for representing motion in accurate and effective ways? (2) How can representation of motion advance our knowledge and understanding of interaction? By addressing these two research questions, this research will contribute new cartographic methods to facilitate effective transformation of raw movement data into useful knowledge of motion in different contexts (i.e. animal and human movements). To assess the efficacy of the proposed framework and the usability of developed methods, a series of evaluative user studies and eye-tracking experiments will be conducted. User study experiments will generate guidelines on effective and more plausible ways of communicating movement patterns. As a research use case, this research will investigate the question of how visualization of motion helps to understand species interaction, in this case endangered tigers in Thailand. Although this research focuses on the cartography of motion, it will contribute methods and techniques to advance the understanding of interaction between individuals in dynamic social and ecological systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将研究如何在地理视觉显示中有效地表示具有复杂空间和时间维度的现象。它将开发可视化方法和工具来绘制个人之间的运动模式和相互作用。这些工具对于研究与社会和生态系统有关的各种应用是至关重要的。现在，在非常高的空间和时间分辨率上收集了有关运动和物体的大量信息。这些数据有可能为与人类和商品的全球运动，疾病爆发，运输变化对城市交通的影响或人类活动对濒危物种的影响有关的关键领域提供信息。需要有效的运动视觉表示，以揭示和传达社会重要性的复杂模式和过程。该项目将有助于洞悉人类如何感知运动模式以及提高对不同制图技术在运动中映射相互作用的有效性的知识。该项目开发的理论，方法和工具可以广泛地用于绘制和研究跨越地理信息科学（GIS），生态，运输和健康等不同学科的运动。通过与行业的合作，这项研究将通过向现有的商业GIS软件产品贡献新的制图技术来弥合学术研究与行业之间的差距，这些技术由研究人员，政策制定者，学生和全球其他人使用。本科生和研究生将接受STEM研究，与行业合作，撰写科学出版物以及开发地理可视化工具的培训。可视化方法和工具将被公开提供，并用于培训学生通过课堂环境和外展活动开发运动地图。这项研究将为运动制图创建一个新的理论框架，并在运动生态学和人类流动性中进行的示例进行对其进行测试。它将研究两个总体研究问题：（1）哪些基本视觉原理和设计要素是哪些以准确有效的方式代表运动？ （2）运动的表示如何推进我们对互动的知识和理解？通过解决这两个研究问题，这项研究将贡献新的制图方法，以促进在不同情况下（即动物和人类运动）有效地将原始运动数据转化为有用的运动知识。 为了评估所提出的框架的功效和开发方法的可用性，将进行一系列评估用户研究和眼睛跟踪实验。用户研究实验将生成有关有效且更合理的交流运动方式的准则。 作为研究用例，这项研究将研究运动可视化如何有助于理解物种相互作用的问题，在这种情况下，在泰国濒临灭绝的老虎。尽管这项研究的重点是运动制图，但它将为动态社会和生态系统中个人之间的相互作用的理解做出贡献。该奖项反映了NSF的法定使命，并认为值得通过基金会的知识分子优点和更广泛的影响审查标准通过评估来进行评估。

项目成果

A classification framework and computational methods for human interaction analysis using movement data

使用运动数据进行人类交互分析的分类框架和计算方法

• DOI: 10.1111/tgis.12960
• 发表时间: 2022
• 期刊: Transactions in GIS
• 影响因子: 2.4
• 作者: Su, Rongxiang;Dodge, Somayeh;Goulias, Konstadinos
• 通讯作者: Goulias, Konstadinos

Mapping trajectories and flows: facilitating a human-centered approach to movement data analytics

• DOI: 10.1080/15230406.2021.1913763
• 发表时间: 2021-05-22
• 期刊: CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE
• 影响因子: 2.5
• 作者: Dodge, Somayeh;Noi, Evgeny
• 通讯作者: Noi, Evgeny

Assessing the cognition of movement trajectory visualizations: interpreting speed and direction

评估运动轨迹可视化的认知：解释速度和方向

• DOI: 10.1080/15230406.2022.2157879
• 发表时间: 2023
• 期刊: Cartography and Geographic Information Science
• 影响因子: 2.5
• 作者: Bae, Crystal J.;Dodge, Somayeh
• 通讯作者: Dodge, Somayeh

WhereNext: Towards a Cartographic Framework for Movement

• 发表时间: 2020
• 作者: S. Dodge

ORTEGA: An object-oriented time-geographic analytical approach to trace space-time contact patterns in movement data

• DOI: 10.1016/j.compenvurbsys.2021.101630
• 发表时间: 2021-04-03
• 期刊: COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
• 影响因子: 6.8
• 作者: Dodge, Somayeh;Su, Rongxiang;Ahearn, Sean C.
• 通讯作者: Ahearn, Sean C.