Human-AI Landscape Visualization Through 3D Gaussian Point Clouds: Investigating Interactive Environmental Reimagination Technology

This research investigates 3D Gaussian Splatting (3DGS) not merely as a rendering technique, but as a probabilistic medium for environmental visualization and “organological” imagination. As emerging technologies mediate our perception of natural environments, a rupture occurs between the logical rigidity of traditional data and the fluid, “alien” logic of neural networks. Drawing on Luciana Parisi’s theory of the “incomputable” and the “aleatory” in automated thinking (2013, 2015, 2016), this paper argues that the inherent artifacts and fragmentations of 3DGS offer a new aesthetic language for spatial cognition—one that moves from deductive reconstruction to inductive, probabilistic generation. The methodology focuses on the artistic workflow of the project Phantom Terrains. It unfolds in three phases: First, Hong Kong’s high-density public housing estates are documented via “defective” mobile scanning, generating fragmented video footage rather than solid geometry. Second, these data “splats”— translucent ellipsoids encoding spatial and temporal uncertainty—are processed as raw video signals within a TouchDesigner network. Third, an immersive interface utilizes MediaPipe hand tracking to map somatic gestures to signal degradation, empowering participants to co-create speculative “phantom terrains.” By foregrounding human agency within a responsive AI-assisted medium, this work demonstrates how Gaussian point clouds can serve as a generative canvas for collaborative environmental storytelling and offers design principles for future interactive art systems.