The vitality of riverfront districts, as a crucial component of urban livability, is profoundly influenced by human visual perception of the surrounding environment. This study takes the Pearl River in Guangzhou as an example and explores the relationship between the visual perception of the urban riverfront core landscape area and the vitality of Riverfront Road. Employing subjective environment perception prediction methods and analyzing the riverfront landscape pictures captured by the research team, we quantified six essential perceptual dimensions. Furthermore, we evaluated the vitality of Riverfront Road through a four-step process: 1. measuring key visual indices of Riverfront Road, including the green view index (GVI), water view index (WVI), sky view index (SVI), and building view index (BVI); 2. evaluating the proximity of cultural landmarks to Riverfront Road; 3. calculating the convenience of driving, buses, and subways for Riverfront Road with the network analysis method; 4. deriving the vitality value of Riverfront Road through the combination of hotspot data from Baidu. With the application of random forest and result comparisons, we obtained a comprehensive analysis of the correlation between visual perception of the urban riverfront core landscape area and the vitality of Riverfront Road. The results reveal the significant correlation between these two factors and highlight that visual perception of the old city landscape area is superior to that of the new city, although the cultural landmarks and transportation convenience play essential roles in the improvement of vitality in Riverfront Road. It is evident that relying solely on visual design may fail to prominently boost vitality. Overall, spatial design should adopt a multidimensional approach, integrating various factors such as transportation convenience, social interaction venues, cultural activities, etc., to create a cohesive vitality network.

(1) Background: Urban villages in Guangzhou are high-density communities with challenging outdoor thermal environments, which significantly impact residents’ thermal comfort. Addressing these issues is crucial for improving the quality of life and mitigating heat stress in such environments. (2) Methods: This study utilized a validated ENVI-met microclimate model to explore the synergistic cooling effects of roof greening and facade greening. Three greening types—total greening, facade greening, and roof greening—were analyzed for their impacts on air temperature, mean radiant temperature, and physiologically equivalent temperature (PET) at a pedestrian height of 1.5 m under varying green coverage scenarios. (3) Results: The findings showed that total greening exhibited the greatest cooling potential, especially under high coverage (≥50%), reducing PET by approximately 2.5 °C, from 53.5 °C to 51.0 °C, during midday, and shifting the heat stress level from “extreme heat stress” to “strong heat stress”. Facade greening reduced PET by about 1.5 °C, while roof greening had a limited effect, reducing PET by 1.0 °C. Furthermore, under coverage exceeding 75%, total greening achieved maximum reductions of 3.0 °C in mean radiant temperature and 1.2 °C in air temperature. (4) Conclusions: This study provides scientific evidence supporting total greening as the most effective strategy for mitigating heat stress and improving thermal comfort in high-density urban villages, offering practical insights for optimizing green infrastructure.

This study explores the intricate relationship between urban amenities and the transformation of urban green spaces (UGS) in Guangzhou, China, over the decade from 2013 to 2022. Amid rapid urbanization, maintaining and expanding green spaces has become increasingly challenging, especially in densely populated urban centers. This research utilizes remote sensing data and Point of Interest (POI) data to assess how different types of urban amenities influence UGS dynamics based on geospatial analytics. The study focuses on the central districts of Guangzhou, a city facing significant urban development pressures, to provide a nuanced understanding of these interactions. Employing both Ordinary Least Squares (OLS) regression and Random Forest (RF) models, the analysis examines the impact of 23 categories of POIs on the spatial and temporal changes in UGS. Key findings reveal that amenities such as auto repair shops, shopping services, and transit facilities are negatively correlated with UGS, indicating that their presence may contribute to the reduction in green space. Conversely, amenities like scenic spots and life services show a positive correlation, suggesting they might support the preservation or expansion of green spaces. The results underscore the dual role of urban amenities in both supporting and constraining green space development, highlighting the need for carefully balanced urban planning strategies. This study provides valuable insights for policymakers and urban planners aiming to promote sustainable urban growth while preserving essential green spaces, ensuring that urban environments remain livable and ecologically resilient.