Interactive visual query of density maps on latent space via flow‐based models

IF 2.1 3区 地球科学 Q2 GEOGRAPHY
Ning Li, Tianyi Liang, Shiqi Jiang, Changbo Wang, Chenhui Li
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引用次数: 0

Abstract

Visual querying of spatiotemporal data has become a dominant mode in the field of visual analytics. Previous studies have utilized well‐designed data structures to speed up the querying of spatiotemporal data. However, reducing storage overhead while improving the querying efficiency of data distribution remains a significant challenge. We propose a flow‐based neural representation method for efficient visual querying. First, we transform spatiotemporal data into density maps through kernel density estimation. Then, we leverage the data‐driven modeling capabilities of a flow‐based neural network to achieve a highly latent representation of the data. Various computations and queries can be performed on the latent representation to improve querying efficiency. Our experiments demonstrate that our approach achieves competitive results in visually querying spatiotemporal data in terms of storage overhead and real‐time interaction efficiency.
通过基于流量的模型对潜空间密度图进行交互式可视化查询
时空数据的可视化查询已成为可视化分析领域的主流模式。以往的研究利用精心设计的数据结构来加快时空数据的查询速度。然而,在提高数据分布查询效率的同时减少存储开销仍然是一个重大挑战。我们提出了一种基于流的神经表示方法来实现高效的可视化查询。首先,我们通过核密度估计将时空数据转换为密度图。然后,我们利用基于流的神经网络的数据驱动建模能力,实现数据的高度潜隐表示。在潜表征上可以执行各种计算和查询,从而提高查询效率。我们的实验证明,我们的方法在可视化查询时空数据方面取得了在存储开销和实时交互效率方面具有竞争力的结果。
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来源期刊
Transactions in GIS
Transactions in GIS GEOGRAPHY-
CiteScore
4.60
自引率
8.30%
发文量
116
期刊介绍: Transactions in GIS is an international journal which provides a forum for high quality, original research articles, review articles, short notes and book reviews that focus on: - practical and theoretical issues influencing the development of GIS - the collection, analysis, modelling, interpretation and display of spatial data within GIS - the connections between GIS and related technologies - new GIS applications which help to solve problems affecting the natural or built environments, or business
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