This study proposes and tests an innovative building information management framework for intelligent landscape design to address the limitations of traditional methods lacking real-time feedback and dynamic adaptability. It was undertaken to meet the growing demands of urbanization and sustainable development that require flexible, user-centered, and environmentally responsive landscapes. The research developed a model integrating 3D visualization with intelligent analysis and real-time sensor data, validated through comparative experiments and case studies across diverse urban spaces. Results showed significant improvements in design efficiency, feedback accuracy, and user satisfaction, with consistent performance across varied scenarios. This means the proposed approach offers a scalable, data-driven solution for modern landscape design, enabling continuous adaptation to real-world conditions and supporting smarter, more sustainable urban environments while laying a foundation for future research on integrating advanced analytics into planning workflows.
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Wang et al. (2025) studied this question.
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