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Towards an optimized paradigm: generative adversarial networks and 3D modeling in landscape design and generation

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  • Ming He

Abstract

Virtual reality (VR) integrates technologies like computer graphics, artificial intelligence, and multi-sensor systems, creating transformative tools for designers and users. This study proposes a novel urban landscape design method using 3D laser scanning combined with frame reorganization and texture mapping. Despite the advancements in VR-based landscape design, existing methods often suffer from inefficiencies in rendering time and suboptimal visual fidelity, limiting their practical application in large-scale urban projects. In the initial phase, we acquire the central pixel point of the images via a meticulous 3D scanning process, thus facilitating a three-dimensional stereo reorganization of urban architectural landscapes. This stage is succeeded by the application of a terahertz wave image segmentation strategy, grounded in the sophisticated utilization of adversarial generative networks and a structured texture mapping procedure. This technique permits the virtual reconstruction of the architectural blueprint, wherein each image layer is systematically traversed, engendering a dynamic representation of the urban landscape. The final step generates realistic urban landscape simulations using integrated 3D laser scanning. To ascertain the efficacy of the proposed methodology, we embarked upon a series of performance assessments across four disparate simulation design scenarios, yielding verifiable outcomes. Our empirical findings demonstrate that the proposed method reduces rendering times by up to 90% compared to traditional tools like SketchUp and 3D Studio Max, while achieving a significant improvement in visual fidelity, as evidenced by standard image quality metrics. These results attest to the formidable potential of this avant-garde approach within the VR landscape design milieu, significantly diminishing the time imperative while augmenting visual fidelity and fortifying automatic display proficiencies. By virtue of its robust analytical underpinnings and innovative approach, this research furnishes a substantial theoretical scaffolding for the evolving discourse in landscape space design, prompting a reevaluation of conventional methodologies while propelling the field towards a more efficient and visually immersive future.

Suggested Citation

  • Ming He, 2025. "Towards an optimized paradigm: generative adversarial networks and 3D modeling in landscape design and generation," PLOS ONE, Public Library of Science, vol. 20(11), pages 1-17, November.
  • Handle: RePEc:plo:pone00:0330095
    DOI: 10.1371/journal.pone.0330095
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