LandSAR: Visceralizing Landslide Data for Enhanced Situational Awareness in Immersive Analytics
Wong Kam-Kwai, Yi-Lin Ye, Wai Tong, Haobo Li, Kentaro Takahira, Aastha Bhatta, Sunil Poudyal, Charles Wang Wai Ng, Huamin Qu, Leni Yang

TL;DR
LandSAR is an immersive analytics system that visceralizes landslide data through simulations and tangible interfaces to improve situational awareness and facilitate real-time analysis.
Contribution
It introduces a novel visceralization approach combining 3D visualizations, tangible terrain models, and real-time simulations for landslide analysis.
Findings
Expert feedback indicates improved situational awareness.
Tangible interfaces enhance geographical perception.
System supports multi-perspective what-if analyses.
Abstract
Landslides pose a significant threat to public safety, but their dynamic processes are difficult to analyze from post-event observation alone. Computational simulation is therefore essential, but it generates vast, abstract datasets that create a cognitive gap between the analyst and the real-world, physical terrain. While Immersive Analytics (IA) begins to bridge this gap by visualizing data in 3D, we explore how these systems evolve beyond abstract data and integrate data visceralization to enhance Situational Awareness (SA). We present LandSAR, an immersive analytics system that enhances SA for landslide analysis by visceralizing landslide data through integrated simulations and visualizations. LandSAR supports real-time simulations of landslide dynamics, prevention strategies, and climate impacts, enabling multi-perspective what-if analyses. The system uses 3D-printed terrain models…
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