首页> 外文会议>Cartographic Theory and Models: Geoinformatics 2007; Proceedings of SPIE-The International Society for Optical Engineering; vol.6751 >Establishing a neurocognition-based taxonomy of graphical variables for attention-guiding geovisualisation
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Establishing a neurocognition-based taxonomy of graphical variables for attention-guiding geovisualisation

机译:建立基于神经认知的图形变量分类法,以指导地理可视化

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摘要

It is a delicate task to design suitable geovisualisations that allow users an efficient visual processing of geographic information. In digital era, such a design task is confronted with a three-fold challenge: the ever growing amount of geospatial data at various granularity levels, the diversified applications and the continuously expanding range of display sizes. A geovisualisation system that strives for a high usability must satisfy the crucial prerequisite of immediately directing the user's gaze to the location of relevant geographic information and of easy decidability of the underlying semantic meanings. To this end, the cognitive skill of visual attention contributes to mnemonic and executive processes. Attention is indispensable for the visual selection. It facilitates the relevant information retrieval, processing and storage. On the basis of neurocognitive visual information processing, the paper addresses the interdisciplinary approach of attention-guiding design of geovisualisations with the intention to establish a taxonomy of scientifically testable variables. The authors try to relate attention-guiding attributes with graphical variables that cartographers apply to encode geographic information. The work is driven by the motivation to enhance the efficiency of geovisualisations and to enable a more precise neurocognition-based evaluation of geovisualisations.
机译:设计合适的地理可视化是一项艰巨的任务,可以使用户对地理信息进行有效的视觉处理。在数字时代,这样的设计任务面临着三方面的挑战:各种粒度级别的地理空间数据数量不断增长,应用多样化以及显示尺寸的范围不断扩大。追求高可用性的地理可视化系统必须满足关键的先决条件,即立即将用户的视线引导到相关地理信息的位置,以及容易确定潜在语义的位置。为此,视觉注意力的认知能力有助于记忆和执行过程。注意对于视觉选择是必不可少的。它方便了相关信息的检索,处理和存储。在神经认知视觉信息处理的基础上,本文探讨了地理可视化注意指导设计的跨学科方法,旨在建立可科学检验的变量的分类法。作者试图将引导注意力的属性与制图师应用于编码地理信息的图形变量相关联。这项工作的动机是提高地理可视化的效率,并实现基于神经认知的更精确的地理可视化评估。

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