In China,traditional village layouts are dynamic,harmoniously integrated with the natural environment,and rich in unique cultural characteristics.However,rapidly constructed villages often lack professional design,res...In China,traditional village layouts are dynamic,harmoniously integrated with the natural environment,and rich in unique cultural characteristics.However,rapidly constructed villages often lack professional design,resulting in overly simple layouts and causing the villages to lose their traditional characteristics.Artiflcial intelligence holds the potential to alleviate this speciflc challenge.This study employs CGAN to generate comprehensive village layouts based on archetypal traditional villages,while also exploring parameters and network architectures to enhance result quality.The research address on traditional villages in southwestern Hubei,reflning generative factors,introducing image-based geographic scales,and employing machine vision to address data scarcity.The key flndings of this study includes:1)The research explores a class of AI-generated evaluation metrics suitable for village layout generation.2)It conflrms that the combination of the Unet_256 generator with the LSGAN architecture yields the best results in image generation.3)It is observed that the optimal generation results are achieved when the equivalent geographic scale of the image is 150 m×150 m.The study validates that GANs can be effectively applied in the village layout,producing layout results that incorporate traditional local experiences.This provides a novel approach to village layout.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51978295)。
文摘In China,traditional village layouts are dynamic,harmoniously integrated with the natural environment,and rich in unique cultural characteristics.However,rapidly constructed villages often lack professional design,resulting in overly simple layouts and causing the villages to lose their traditional characteristics.Artiflcial intelligence holds the potential to alleviate this speciflc challenge.This study employs CGAN to generate comprehensive village layouts based on archetypal traditional villages,while also exploring parameters and network architectures to enhance result quality.The research address on traditional villages in southwestern Hubei,reflning generative factors,introducing image-based geographic scales,and employing machine vision to address data scarcity.The key flndings of this study includes:1)The research explores a class of AI-generated evaluation metrics suitable for village layout generation.2)It conflrms that the combination of the Unet_256 generator with the LSGAN architecture yields the best results in image generation.3)It is observed that the optimal generation results are achieved when the equivalent geographic scale of the image is 150 m×150 m.The study validates that GANs can be effectively applied in the village layout,producing layout results that incorporate traditional local experiences.This provides a novel approach to village layout.
