How to Enhancing Urban Space Renewal Through Visual Landscape Perception? An Approach From Street View Image Recognition

Urban space renewal is crucial for addressing urban issues but faces challenges including funding shortages, complex planning, and resource waste. To enhance its efficacy, this study introduces a new comprehensive framework to evaluate the renewal potential of urban spatial through visual landscape perception (VLP). Based on expert evaluation of panoramic street view images, it adopts entropy-weighted comprehensive evaluation, kernel density estimation, spatial correlation, and GWR methods to depict VLP at the 500-m GIS grid level. By selecting Jinan, a city with a rich history and rapid development in China, as the study area, the findings reveal: (1) Overall VLP of Jinan is low, with considerable variation across grids, indicating pronounced urban landscape imbalances from the city center to its external areas. (2) Significant spatial clustering is observed in VLP, particularly with lower values concentrated on the outskirts of the city, emphasizing the importance of prioritizing urban renewal efforts in these areas. (3) Varied factors influence urban landscape perception across grid cities, with urban intensity and ecological space proportions impacting the center, while economic factors affect the periphery. Utilizing grid-based evaluations of urban landscape perception can enhance urban spatial renewal by pinpointing challenges, prioritizing renewal areas, and crafting tailored strategies based on influential factors.