A Tracking Analyst for large 3D spatiotemporal data from multiple sources (case study: Tracking volcanic eruptions in the atmosphere)

作者：Gad Mohamed A^*; Elshehaly Mai H; Gracanin Denis; Elmongui Hicham G

来源：Computers & Geosciences, 2018, 111: 283-293.

DOI：10.1016/j.cageo.2017.10.003

• Tracking Analyst
• Spatiotemporal
• Interpolation
• Data fusion
• Volcanic eruptions

This research presents a novel Trajectory-based Tracking Analyst (TTA) that can track and link spatiotemporally variable data from multiple sources. The proposed technique uses trajectory information to determine the positions of time-enabled and spatially variable scatter data at any given time through a combination of along trajectory adjustment and spatial interpolation. The TTA is applied in this research to track large spatiotemporal data of volcanic eruptions (acquired using multi-sensors) in the unsteady flow field of the atmosphere. The TTA enables tracking injections into the atmospheric flow field, the reconstruction of the spatiotemporally variable data at any desired time, and the spatiotemporal join of attribute data from multiple sources. In addition, we were able to create a smooth animation of the volcanic ash plume at interactive rates. The initial results indicate that the TTA can be applied to a wide range of multiple-source data.

• 出版日期2018-2
• 单位美国弗吉尼亚理工大学(Virginia Tech)