Optimizing Environmental Comfort and Landscape Visibility in Traditional Villages via Digital Platforms: A Case Study of Dazhai Village, Chengbu County, Hunan

This study investigates the influence of environmental comfort and landscape visibility on node extraction and tour route optimization by integrating spatial data analysis with site design. Three algorithmic models—environmental comfort analysis, dynamic tour route analysis, and multidimensional plot value evaluation—were developed using Grasshopper (GH) combined with Python 3.12.0. These models comprehensively quantified the solar radiation and wind conditions in Dazhai Village, Chengbu County, simulated visitor perspectives to calculate landscape visibility, and derived a quantitative visual perception index. Analysis of 197 sampling points revealed superior environmental comfort and scenic views at the village’s peripheries and open areas. Based on annual comfort duration percentages and dynamic tour evaluation coefficients, 13 activity nodes with comfort duration rates exceeding 25.68% were identified, enabling the extraction of scientifically optimized tour routes. The planning scope was further refined by integrating the village’s visual perception index to account for multi-factor influences. Establishing a digital model for traditional village activity node extraction, tour route optimization, and plot value evaluation effectively enhances spatial analysis’s efficiency and scientific rigor. This approach enriches the design methodology system for environmental comfort and landscape visibility in traditional villages while offering new perspectives for their conservation research.