A Tracking Analyst for large 3D spatiotemporal data from multiple sources (case study: Tracking volcanic eruptions in the atmosphere). (February 2018)

• Record Type: Journal Article
• Authors: Gad, Mohamed A.; Elshehaly, Mai H.; Gračanin, Denis; Elmongui, Hicham G.
• Is Part Of: Computers & geosciences. Volume 111(2018)
• Page Start: 283
• Page End: 293
• Publication Date: 2018-02
• Subjects: Tracking Analyst -- Spatiotemporal -- Interpolation -- Data fusion -- Volcanic eruptions; Environmental policy -- Periodicals; 550.5
• DOI: 10.1016/j.cageo.2017.10.003
• Languages: English
• ISSNs: 0098-3004

Abstract

Abstract: 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. Highlights: A trajectory-based spatiotemporal interpolation method is developed. The method links multiple-sensor spatiotemporal data acquired in the flow field. The uses include correction of satellite data, data join, and plume simulation. An illustrative case study of volcanic eruptions in the atmosphere is presented. An efficient GPU-based visualization interface is developed for the method.