Where Spatial Immersion Meets Diverse Experiences: Exploring Virtual Scenes through Gaussian Splatting and Parametric Iteration

Abstract

The expansion of spatial intelligence and generative technologies has advanced 3D representation, shifting digital creation toward user perception and challenging project-oriented design paradigms. Addressing the need to balance environmental realism with conceptual adaptability, this paper proposes a computational method that integrates Gaussian Splatting (GS) and parametric iteration for exploratory virtual scene design. The study examines an urban public green space, where GS is adopted for high-fidelity scene reproduction following image acquisition. Parametric spatial prototypes are developed in Grasshopper (GH) and linked to Unity to support real-time overlay, interaction, and virtual reality (VR) navigation. The results of the System Usability Scale (SUS) show that the synergy between GS and parametric iteration enhances spatial orientation and engagement through detailed visual references. Meanwhile, this workflow achieves design richness and experiential diversity without introducing negative effects on overall usability, proving particularly effective for design tasks requiring node tracking and observation. Overall, this research presents a replicable framework that demonstrates the value of combining realistic contexts with variation rules in early design stages.

Keywords: Spatial Representation, Virtual Scene, Gaussian Splatting (GS), Parametric Design, User Experience

DOI: 10.54941/ahfe1007303