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Topology-based Analysis for Multimodal Atmospheric Data of Volcano Eruptions

Please always quote using this URN: urn:nbn:de:0297-zib-57043
  • Many scientific applications deal with data from a multitude of different sources, e.g., measurements, imaging and simulations. Each source provides an additional perspective on the phenomenon of interest, but also comes with specific limitations, e.g. regarding accuracy, spatial and temporal availability. Effectively combining and analyzing such multimodal and partially incomplete data of limited accuracy in an integrated way is challenging. In this work, we outline an approach for an integrated analysis and visualization of the atmospheric impact of volcano eruptions. The data sets comprise observation and imaging data from satellites as well as results from numerical particle simulations. To analyze the clouds from the volcano eruption in the spatiotemporal domain we apply topological methods. Extremal structures reveal structures in the data that support clustering and comparison. We further discuss the robustness of those methods with respect to different properties of the data and different parameter setups. Finally we outline open challenges for the effective integrated visualization using topological methods.

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Author:Alexander Kuhn, Wito Engelke, Markus Flatken, Hans-Christian HegeORCiDGND, Ingrid Hotz
Document Type:ZIB-Report
Tag:multi-modal, intergrated data analysis, topology
MSC-Classification:00-XX GENERAL
CCS-Classification:J. Computer Applications
PACS-Classification:00.00.00 GENERAL
Date of first Publication:2016/01/14
Series (Serial Number):ZIB-Report (16-03)
Published in:Appeared in: Carr H., Garth C., Weinkauf T. (eds) Topological Methods in Data Analysis and Visualization IV. TopoInVis 2015. Mathematics and Visualization. Springer, Cham, 2017. Pp. 35-50
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