WhereNext: Towards a Cartographic Framework for Movement
WhereNext: Towards a Cartographic Framework for Movement
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发表时间：
2020
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通讯作者：
S. Dodge
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作者：
S. Dodge
本文介绍了一个正在进行的研究，对发展的制图框架的映射运动。虽然对轨迹数据和运动分析的研究正在兴起（Long等人，2018），地图理论对运动作为一种动态现象的适用性以及当前使用大型跟踪数据集进行知识发现的可视化方法的有效性仍然没有得到充分研究（Griffin，罗宾逊和Roth，2017; Demšar，斯林斯比和Weibel，2019）。现在以非常高的空间和时间分辨率收集关于轨迹的大量信息（即移动的实体的按时间排序的位置集合）。这些数据有望提供有关全球人员和货物流动、疾病爆发、交通变化对城市动态的影响或人类活动对竞争物种行为的影响的新形式的知识。然而，随着计算方法提高了我们分析轨迹数据的能力，我们对如何以准确和信息丰富的方式显示运动模式的理解仍然有限。
This paper describes an ongoing research towards the development of a cartographic framework for mapping movement. Although research on trajectory data and movement analytics is on the rise (Long et al., 2018), the suitability of cartographic theories for movement as a dynamic phenomenon and the efficacy of current visualization approaches for knowledge discovery using large tracking data sets remain understudied (Griffin, Robinson and Roth, 2017; Demšar, Slingsby and Weibel, 2019). A vast amount of information on trajectories (i.e. time-ordered sets of locations of mobile entities) is now collected at very high spatial and temporal resolutions. These data promise new forms of knowledge about global flows of humans and goods, disease outbreaks, the impact of transportation changes on urban dynamics, or effects of human activity on the behavior of competing species. However, as computational approaches advance our ability to analyze trajectory data, we remain limited in our understanding of how movement patterns should be displayed in accurate and informative ways.