地理空间不确定性边界化对用户启发式推理的影响

Lorenzo Libertini, E. Chuprikova, L. Meng
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引用次数: 0

摘要

摘要一套被称为“启发式”的心理策略——我们在不确定的情况下用来做决定的逻辑捷径——已经成为越来越多研究的主题。然而,对于不确定地理空间数据的启发式推理过程的研究相对较少。通过这项研究,我们探索了启发式决策与不确定状态下地理空间数据可视化之间的关系,特别关注边界的可视化,这里称为“边界化”。因此,我们测试了一套制图技术,通过用户调查在一系列地图上可视化两种自然灾害的边界。受访者被要求评估几个可能受空气污染或雪崩影响的住房地点的安全性和可取性。调查中的地图因“边界化”方法、背景颜色和不确定数据的信息类型(例如,外在与内在)而有所不同。使用混合定量和定性方法分析的调查结果证实了先前的建议,即启发式在影响用户的地图体验和随后的决策方面发挥了重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect of Geospatial Uncertainty Borderization on Users’ Heuristic Reasoning
Abstract. A set of mental strategies called "heuristics" – logical shortcuts that we use to make decisions under uncertainty – has become the subject of a growing number of studies. However, the process of heuristic reasoning about uncertain geospatial data remains relatively under-researched. With this study, we explored the relation between heuristics-driven decision-making and the visualization of geospatial data in states of uncertainty, with a specific focus on the visualization of borders, here termed "borderization". Therefore, we tested a set of cartographic techniques to visualize the boundaries of two types of natural hazards across a series of maps through a user survey. Respondents were asked to assess the safety and desirability of several housing locations potentially affected by air pollution or avalanches. Maps in the survey varied by "borderization" method, background color and type of information about uncertain data (e.g., extrinsic vs. intrinsic). Survey results, analyzed using a mixed quantitative-qualitative approach, confirmed previous suggestions that heuristics play a significant role in affecting users' map experience, and subsequent decision-making.
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