Visualizing Motion: A Framework for the Cartography of Movement

可视化运动:运动制图框架

基本信息

  • 批准号:
    1853681
  • 负责人:
  • 金额:
    $ 32.88万
  • 依托单位:
  • 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

项目摘要

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.
这个项目将研究如何运动作为一种现象,具有复杂的空间和时间维度,是有效地表示在地理视觉显示。它将开发可视化方法和工具,以绘制个人之间的移动模式和互动。这些工具对于研究与社会和生态系统相关的各种应用的假设生成和视觉传达至关重要。现在以非常高的空间和时间分辨率收集关于运动中的物体和物体的大量信息。这些数据有可能为与全球人员和货物流动、疾病爆发、交通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来揭示和传达具有社会重要性的复杂模式和过程。该项目将有助于深入了解人类如何感知运动模式,并提高对不同制图技术在绘制运动交互中的有效性的认识。该项目开发的理论、方法和工具可广泛用于绘制和研究地理信息科学(GIS)、生态学、交通和健康等不同学科的运动。通过与工业界的合作,这项研究将弥合学术研究和工业界之间的差距,为研究人员、政策制定者、学生和世界各地其他人使用的现有商业GIS软件产品提供新的制图技术。本科生和研究生将接受STEM研究培训,与行业合作,撰写科学出版物,开发地理可视化工具。可视化方法和工具将公开提供,并用于培训学生通过课堂环境和外联活动绘制动态地图,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的例子中对其进行测试。它将探讨两个首要的研究问题:(1)什么是基本的视觉原则和设计元素,以准确和有效的方式表示运动?(2)运动的表征如何促进我们对相互作用的认识和理解?通过解决这两个研究问题,这项研究将有助于新的制图方法,以促进有效的原始运动数据转化为有用的知识,在不同的背景下(即动物和人类运动)的运动。 为了评估拟议框架的有效性和开发方法的可用性,将进行一系列评估性用户研究和眼动追踪实验。用户研究实验将产生有效的和更合理的方式沟通运动模式的指导方针。 作为一个研究用例,本研究将调查运动的可视化如何帮助理解物种相互作用的问题,在这种情况下,泰国的濒危老虎。虽然这项研究的重点是运动的制图,它将有助于方法和技术,以促进在动态的社会和生态系统中的个人之间的相互作用的理解。这个奖项反映了NSF的法定使命,并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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:
  • 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
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
WhereNext: Towards a Cartographic Framework for Movement
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Dodge
  • 通讯作者:
    S. Dodge
A time-geographic approach to quantify the duration of interaction in movement data
量化运动数据中交互持续时间的时间地理方法
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Somayeh Dodge其他文献

Exploring the effects of wildfire events on movement patterns
探索野火事件对移动模式的影响
  • DOI:
    10.1016/j.apgeog.2025.103602
  • 发表时间:
    2025-06-01
  • 期刊:
  • 影响因子:
    5.400
  • 作者:
    Evgeny Noi;Somayeh Dodge;Alan T. Murray
  • 通讯作者:
    Alan T. Murray
HaniMob 2022 Workshop Report: The 2nd ACM SIGSPATIAL Workshop on Animal Movement Ecology and Human Mobility
HaniMob 2022 研讨会报告:第二届 ACM SIGSPATIAL 动物运动生态学与人类流动性研讨会
  • DOI:
    10.1145/3632268.3632278
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    F. Ossi;F. Hachem;Benjamin Robira;Diego Ellis Soto;Christian Rutz;Somayeh Dodge;Francesca Cagnacci;M. Damiani
  • 通讯作者:
    M. Damiani

Somayeh Dodge的其他文献

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{{ truncateString('Somayeh Dodge', 18)}}的其他基金

Advancing Methods to Trace and Contextualize Space-Time Interaction Patterns in Movement Data
改进运动数据中时空交互模式的追踪和情境化方法
  • 批准号:
    2217460
  • 财政年份:
    2022
  • 资助金额:
    $ 32.88万
  • 项目类别:
    Standard Grant
CAREER: Modeling Movement and Behavior Responses to Environmental Disruptions
职业:模拟对环境破坏的运动和行为反应
  • 批准号:
    2043202
  • 财政年份:
    2021
  • 资助金额:
    $ 32.88万
  • 项目类别:
    Continuing Grant

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职业生涯:用于辅助人类意志运动的下肢外骨骼的任务不变定制框架
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Developing an Experimental and Computational Framework for Studying Neural Representations of Tactile Motion on the Hand
开发用于研究手部触觉运动神经表征的实验和计算框架
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    2023
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NSF/FDA SIR: Towards the Establishment of a Validation Framework for Wearable Motion Analysis Systems: Development and Evaluation of an Open-Design Sync Platform
NSF/FDA SIR:建立可穿戴运动分析系统的验证框架:开放式设计同步平台的开发和评估
  • 批准号:
    2229538
  • 财政年份:
    2022
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使用人工智能开发人体背部无标记动作捕捉框架
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基于深度学习的 3D 超声心动图左心室分割和运动跟踪框架
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使用贝叶斯框架进行肌电图信号处理,用于下一代运动集成人机界面
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