Tourists Preferred Streets Visualization Using Articulated GPS Trajectories Driven by Mobile Sensors
Tourists Preferred Streets Visualization Using Articulated GPS Trajectories Driven by Mobile Sensors
复制标题
游客更喜欢使用移动传感器驱动的铰接式 GPS 轨迹进行街道可视化
DOI：
10.1007/978-3-031-06245-2_4
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Ryo Sato and Akinori Takahashi
中科院分区：
文献类型：
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作者：
Iori Sasaki;Masatoshi Arikawa;Ryo Sato and Akinori Takahashi
虽然已经有很多关于GPS大数据分析的研究，以发现游客的首选景点和目的地，但发现首选街道对改善旅游内容和优化交通系统也起着重要作用。一般来说，GPS数据具有不准确性和冗余性，其密度偏向于特定位置。这导致很难通过使用基于密度的可视化（如热图）来使游客首选的街道脱颖而出。在这项研究中，我们试图应用一个移动的基于传感器的数据清洗方法，这是在终端用户设备上执行，从而均衡每个游客的轨迹数据的偏差。本文探讨了如何从这种轻量级和非不稳定的数据生成热图，以及它是否可以有效地可视化游客偏好的街道使用真实的旅游数据。通过在地理网格正方形上绘制GPS数据并关注密度值的四分位数来创建热图。结果与实际旅游线路的变化趋势基本一致。这项研究的贡献是，它不需要任何准备，如道路网络，并不需要大量的计算相比，传统的方法。
Although there has been a lot of research on GPS big data analysis to discover the preferred spots and destinations for tourists, discovering the preferred streets also plays an important role in improving tourism content and optimizing transportation systems. In general, GPS data has inaccuracies and redundancies, and its density is biased to specific locations. This causes difficulty making tourists preferred streets stand out by using density-based visualizations such as heatmaps. In this study, we attempted to apply a mobile sensor-based data cleaning method, which is executed at the end-user device, and thereby equalize the bias of each tourist’s trajectory data. This paper examines how to generate a heatmap from such lightweight and non-unstable data and whether it can effectively visualize tourists preferred streets using real tourism data. A heat map was created by plotting GPS data on a geographic grid square and focusing on the quartiles of density values. The results were almost consistent with the tendency of actual tourist routes. The contribution of this research is that it does not require any preparation such as a road network, and does not require a large amount of computation compared to conventional approaches.