Urban Street View Spatial Evaluation and Distribution of Residential Properties at Different Price Points

In residents' pursuit of quality living environments, the quality of the residential surroundings is becoming an important consideration when purchasing a house. Previous studies have paid little attention to the impact of urban street views on residential prices. This study utilizes street view data and the SAM model based on deep learning technology to extract the visual features of street spaces around residential areas, qualitatively analyzing the association between urban street view visual features and the distribution of residential properties at different price points. The results of this study indicate that using the SAM model for extracting visual features of urban street views is feasible. Urban street view evaluation has an impact on urban real estate prices, and computer technology assists in quantifying and visualizing this impact.