Comparative Analysis of TAG (Three-Dimensional Architectural Greening) Scenic Beauty Quantitative Techniques Based on Visual Perception

Three-dimensional architectural greening (TAG) enables the integration of ecological, economic, and social advantages via the effective use of multidimensional space in a variety of forms, making it a significant method for enhancing spatial quality in densely populated cities. TAG technology has expanded the scope and capabilities of urban greening. It has the ability to provide green space, improve urban ecology and aesthetics, and alleviate the conflict between limited land resources and rising demand for greening throughout the urbanization process. Currently, there is a lack of a systematic assessment approach that focuses on the public’s visual perception of TAG. It is critical to focus on advances in visual perception approaches and create a “people-oriented perception driven” evaluation system that serves as a scientific foundation for urban three-dimensional greening initiatives. First, this study created a database of 300 TAG cases and selected classic cases using screening, classification, and sampling. Second, three experiments were set up for the study, including the use of the semantic differential (SD) method, and scenic beauty estimation (SBE) for subjective evaluation, and the eye-tracking experiment for objective evaluation. Finally, this study compared subjective and objective evaluations and demonstrated that both two approaches had a certain amount of accuracy. It also investigated the relationship between spatial features and public visual perceptions using methods such as factor and correlation analysis. The three effective methods for evaluating the quality of TAG based on visual perception that are presented in this study—two subjective and one objective—use standardized images, are quick and simple to use, and make up for the drawbacks of conventional strategies like indirectness, inefficiency, and time-consuming data collection. They also form a solid foundation for the real-world application of categorization prediction. In addition to being adaptable to a wide range of application settings, these two assessment paths—subjective evaluation and objective evaluation—can be integrated to complement one another and provide scientific references for future TAG designs and spatial decision making.