Rural Local Landscape Perception Evaluation: Integrating Street View Images and Machine Learning - Suning Gong; Lin Zhang; Jie Zhang; Yuxi Duan (ISPRS International Journal of Geo-Information, 2025)
Rural landscape perception is of great significance in understanding the emotional connection between people and rural local environments. Seeking to rectify the problem of incomplete or biased results owing to the separation of objective and subjective landscape perception in previous studies, this study took the village of Chongming District in Shanghai, China, as an example and built an evaluation model that integrated four dimensions and 20 indicators of objective and subjective landscape perception, and used machine learning technology to analyze street view images. Subjective perception has been influenced by landscape color, style, and element perception. Notable spatial disparities have been observed in the distribution of rural landscape indicators across Chongming. This study refines key subjective and objective factors affecting rural landscape perception, and the model provides a new method for the perception evaluation of complex landscapes, providing a theoretical basis and practical reference for rural landscape planning.