As an essential structural indicator of buildings, sky view factor (SVF) is one of the most critical factors affecting the urban thermal environment. However, the relationship between SVF and the thermal environment at the neighborhood scale has not been adequately studied. Therefore, this paper investigates the relationship between SVF and air temperature in different building scenarios based on the Local Climate Zone (LCZ) classification framework. Firstly, the study is based on multi-source urban data and the Open Street Map (OSM) to map the local climate zones in Beijing. Then, a simulation model with different LCZs was constructed based on realistic scenarios using the microclimate simulation software ENVI-met, and the thermal environment was simulated in 24 h on a single day in summer. Finally, the SVF and air temperature relationship under different LCZ scenarios was calculated and analyzed. The results show that (1) the SVF values of LCZ 1, LCZ 2, and LCZ 5 show a more apparent positive correlation with air temperature than other categories, and the SVF values of LCZ 6–9 show a negative and then positive correlation with air temperature; (2) in the morning, the dense building areas show a weak correlation with air temperature, and the differences in air temperature corresponding to the SVF values in different zones are greater; (3) in the morning, the air temperature in the dense building areas showed a weak correlation, the difference between the SVF values and the air temperature in different intervals was different, and when the SVF was larger or smaller, the air temperature change was smaller and concentrated, and the correlation between the air temperature and the SVF in the open building areas was not obvious; (4) with 12:00 as the dividing line, the SVF and the air temperature in all categories showed a weak positive correlation after this time. This study can provide guidance on optimizing building layouts and mitigating the impacts of urban heat on human health.

Public sub-health has emerged as a pressing concern in densely populated urban areas. The urban environment, with its innate ability to modulate public emotions, harbors a precious resource in the form of urban rivers, which provide a serene and verdant space. This study focuses on the Liangma River in Chaoyang District, Beijing, selecting two rivers with diverse landscape features as the subjects of research. By employing physiological feedback data in conjunction with a subjective questionnaire, the emotional impact of high-density urban riverside spaces on individuals is quantitatively analyzed. Electrocardiogram (ECG) data, eye movement data, and the positive–negative emotion scale (PANAS) are subjected to data analysis. The study reveals the following key findings: (1) The riverside landscape in high-density urban areas exerts a positive influence on emotional well-being. Individuals in more natural river settings experience greater levels of contentment and relaxation, while those in areas with a higher proportion of artificial elements exhibit increased excitement and happiness. Moreover, scenes characterized by a greater degree of greening have a more pronounced soothing effect on mood. (2) A specific correlation between visual characteristics and emotional fluctuations is observed. The waterfront side of the trail exerts a stronger spatial attraction, and a higher proportion of blue and green spaces significantly contributes to stress relief. (3) The utilization of human-induced engineering technology, which captures emotional changes through physiological feedback, demonstrates a higher level of accuracy and is well-suited for small-scale studies. These findings highlight the potential of arranging diverse types of waterfront footpath landscapes in high-density urban areas and approaching waterfront landscape design and transformation from a novel perspective centered on health intervention. Such efforts hold promise for alleviating the daily pressures faced by the general public and fostering the development of a “healthy city”.

The COVID-19 outbreak directly and severely threatens global public health. Non-drug interventions in response to the COVID-19 pandemic have significantly altered urban socioeconomic activity. Understanding the different levels of city resilience to the impact of COVID-19 on urban human activities is essential. In this paper, 35 large cities in China were selected as research areas, and based on NPP-VIIRS night light images, the spatial pattern changes in human activities during the epidemic period from the end of December 2019 to December 2022 were explored. The results are as follows: (1) In the first two months of the epidemic, the luminous value of large cities showed an extensive range of decline, and the decline in different urban functional places was different. (2) There is a significant positive correlation between the urban population and the luminous change value. The closer the relationship between urban places and human activities, the stronger the correlation between the population and the luminous change value of urban places. (3) In the middle and later stages of the epidemic, the night light value of all cities showed an upward trend, but there was a difference. (4) The increase in the number of confirmed cases in the middle and later stages of the epidemic could hardly lead to a significant decrease in the value of night light on a monthly scale unless the city had a relatively large area and a relatively strict lockdown policy in that month. This study will help inform future strategies and decisions to effectively combat epidemics and the construction of resilient cities.