IVMS: An immersive virtual meteorological sandbox based on WYSIWYG - Hao Hu; Song Wang; Yonghui Chen (Visual Informatics, 2023)
A novel approach to visually represent meteorological data has emerged with the maturation of Immersive Analytics (IA). We have proposed an immersive meteorological virtual sandbox as a solution to the limitations of 2D analysis in expressing and perceiving data. This innovative visual method enables users to interact directly with data through non-contact aerial gestures (NCAG). Referring to the “What you see is what you get” concept in scientific visualization, we proposed a novel approach for the visual exploration of meteorological data that aims to immerse users in the analysis process. We hope this approach can inspire immersive visualization techniques for other types of geographic data as well. Finally, we conducted a user questionnaire to evaluate our system and work. The evaluation results demonstrate that our system effectively reduces cognitive burden, alleviates mental workload, and enhances users’ retention of analysis findings.