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Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species

机译:时空事件预测的视觉分析:调查侵袭性种类的传播动态

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Invasive species are a major cause of ecological damage and commercial losses. A current problem spreading in North America and Europe is the vinegar fly Drosophila suzukii. Unlike other Drosophila, it infests non-rotting and healthy fruits and is therefore of concern to fruit growers, such as vintners. Consequently, large amounts of data about the occurrence of D. suzukii have been collected in recent years. However, there is a lack of interactive methods to investigate this data. We employ ensemble-based classification to predict areas susceptible to the occurrence of D. suzukii and bring them into a spatio-temporal context using maps and glyph-based visualizations. Following the information-seeking mantra, we provide a visual analysis system Drosophigator for spatio-temporal event predictions, enabling the investigation of the spread dynamics of invasive species. We demonstrate the usefulness of our approach in three use cases and an evaluation with more than 30 domain experts.
机译:侵入性物种是生态损害和商业损失的主要原因。 目前在北美和欧洲传播的问题是醋苍蝇果蝇铃木。 与其他果蝇不同,它侵染了非腐烂和健康的水果,因此对果树种植者(例如葡萄酒者)的关注。 因此,近年来收集了关于D. Suzukii的发生的大量数据。 但是,缺乏互动方法来调查此数据。 我们雇用基于合奏的分类来预测易于发生D. Suzukii的发生的区域,并使用地图和基于格术的可视化将它们带入时空上下文。 在寻求信息寻求的Mantra之后,我们提供了一种视觉分析系统脱棘器,用于时空事件预测,从而调查了侵入性物种的传播动态。 我们展示了我们在三种用例中的方法的有用性,并以超过30个领域专家评估。

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