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首页> 外文期刊>Journal of geovisualization and spatial analysis >Determining Real-Time Patterns of Lightning Strikes from Sensor Observations
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Determining Real-Time Patterns of Lightning Strikes from Sensor Observations

机译：确定实时的闪电模式罢工从传感器观测

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摘要

Transient spatiotemporal events occur within a short interval of time, in a particular location. If such events occur unexpectedly with varying durations, frequencies, and intensities, they pose a challenge for near-real-time monitoring. Lightning strikes are examples of such events and they can have severe negative consequences, such as fires, or they precede sudden flash storms, which can result in damage to infrastructure, loss of Internet connectivity, interruption of electrical power supply, and loss of life or property. Furthermore, they are unexpected, momentary in occurrence, sometimes with high frequency and then again with long intervals between them, their intensity varies considerably, and they are difficult to trace once they have occurred. Despite their unpredictable and irregular nature, timely analysis of lightning events is crucial for understanding their patterns and behaviour so that any adverse effects can be mitigated. However, near-real-time monitoring of unexpected and irregular transient events presents technical challenges for their analysis and visualisation. This paper demonstrates an approach for overcoming some of the challenges by clustering and visualising data streams with information about lightning events during thunderstorms, in real time. The contribution is twofold. Firstly, we detect clusters in dynamic spatiotemporal lightning events based on space, time, and attributes, using graph theory, that is adaptive and does not prescribe number and size of clusters beforehand, and allows for use of multiple clustering criteria and thresholds, and formation of different cluster shapes. Secondly, we demonstrate how the space time cube can be used to visualise unexpected and irregular transient events. Along with the visualisation, we identify the interactive elements required to counter challenges related to visualising unexpected and irregular transient events through space time cubes.
机译：瞬态发生在一个时空的事件短的时间间隔,在一个特定的位置。如果发生此类事件出乎意料地不同持续时间、频率和强度,他们对近实时监测构成挑战。雷击是此类事件的例子他们可以有严重的负面影响,这样的火灾,或者他们之前突然闪电风暴,这会导致破坏的基础设施,失去网络连接中断电力供应,和生命损失财产。瞬间发生,有时高频率,然后再次与长时间的间隔他们之间,他们的强度变化明显,他们很难跟踪一旦他们发生。不可预知的和不规则的性质,及时闪电事件的分析是至关重要的了解他们的模式和行为可以减轻不利影响。然而,意想不到的近实时的监控提出了技术和不规则瞬变事件挑战他们的分析和可视化。本文展示了一种方法克服集群的一些挑战和想象的数据流信息在雷暴闪电事件,真正的时间。我们检测集群动态时空闪电活动基于空间、时间和属性,使用图论,这是自适应的,不规定的数量和大小集群之前,允许使用多个聚类标准和阈值,集群形成不同的形状。我们将演示如何时空多维数据集用于可视化意想不到的和不规则的瞬态事件。我们确定所需的交互元素应对挑战与想象意想不到的和不规则的瞬态事件时空多维数据集。

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