LandSAR: Visceralizing Landslide Data for Enhanced Situational Awareness in Immersive Analytics
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 as tangible interfaces to facilitate haptic feedback and enable gesture-based exploration, allowing for intuitive geographical perception. Expert interviews and workshops demonstrate that LandSAR effectively improves SA and engagement.
Keywords
Cite
@article{arxiv.2604.09241,
title = {LandSAR: Visceralizing Landslide Data for Enhanced Situational Awareness in Immersive Analytics},
author = {Wong Kam-Kwai and Yi-Lin Ye and Wai Tong and Haobo Li and Kentaro Takahira and Aastha Bhatta and Sunil Poudyal and Charles Wang Wai Ng and Huamin Qu and Leni Yang},
journal= {arXiv preprint arXiv:2604.09241},
year = {2026}
}
Comments
11 pages. A preprint version accepted to PacificVis'26