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Immersive Visualization of Multilayered Geospatial Urban Data for Visual Analytics and Exploration

Abstract : Geospatial urban data encompasses a plethora of thematic layers, and spans geometric scales reaching from individual architectural elements to inter-regional transportation networks. This thesis examines how immersive environments can be utilized to effectively aid in visualizing this multilayered data simultaneously at various scales. For this, two distinct software prototypes were developed to implement the concepts of multiple coordinated views and focus+context, specifically taking full advantage of the affordances granted by modern virtual reality hardware, while also being suitable for augmented reality. Of the two novel methods introduced here, one — an optimized, vertical arrangement of map layers — was formally evaluated in a con- trolled user study, and the other — a geometric projection approach to create panoramic focus+context views — informally through feedback from domain experts who tested it. Both showed promising results, and especially the formal study yielded valuable insights into how user characteristics can influence the perceived usability of such visualization systems and their performance.
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Submitted on : Monday, May 16, 2022 - 5:17:50 PM
Last modification on : Tuesday, June 7, 2022 - 4:54:02 PM


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  • HAL Id : tel-03669606, version 1


Maxim Spur. Immersive Visualization of Multilayered Geospatial Urban Data for Visual Analytics and Exploration. Graphics [cs.GR]. Ecole Centrale de Nantes, 2021. English. ⟨tel-03669606v1⟩



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