Parks, as a major infrastructure that provide public service for urban residents, play a vital role in promoting urban livability and public health. Under the framework of spatial equity, more sophisticated accessibility methods were used on measuring urban park accessibility such as multi-mode 2SFCA. However, the accessibility of residential areas near parks was seriously underestimated by using the multi-mode 2SFCA method. Thus, this study aimed to propose an improved multi-mode 2SFCA method to measure urban park accessibility with a more appropriate approach, by taking residential areas of Tianjin central city as the spatial unit. The results indicate that all residential areas can obtain urban park accessibility, but the spatial distribution of urban park accessibility is heterogeneous. The numerical value of urban park accessibility decreases as the travel time from residential areas to urban parks increases; it is shown that the proposed method can provide a more realistic evaluation compared to the traditional multi-mode 2SFCA method. This study provides a comprehensive and realistic insight into acquainting with urban park accessibility and helps urban planners formulate effective policies and strategies to ease spatial imbalance.

Rainfall severely impacts human mobility in urban areas and creates significant challenges for traffic management and urban planning. There is an urgent need to understand the impact of rainfall on residents’ travels from multiple perspectives. Taxi GPS data contains a large amount of spatiotemporal information about human activities and mobility in urban areas. For this study, we selected the central area of Zhuhai as the study area and used taxi data from August 2020 for the investigation. Firstly, we divided the taxi data into four scenarios, i.e., weekdays with and without rainfall and weekends with and without rainfall and analyzed and compared the trip characteristics for the different scenarios. Then, using the traffic analysis zone (TAZ) as the node and taxi flow between TAZs as edges, we constructed a network and compared the network indicators under the different scenarios. Finally, we used the Leiden algorithm to detect communities in different scenarios and compared the network indicators of the communities. The results showed that on days with rainfall, taxi flow and its spatial and temporal distribution pattern changed significantly, which affected transportation supply and demand. These findings may provide useful references for the formulation of urban transport policies that can adapt to different weather conditions.

The frequent occurrence of extreme high temperature weather and heat waves has greatly affected human life. This paper analyzes population exposure and its influencing factors during a heat wave incident in Zhuhai from 6 to 12 September 2021 based on real-time mobile phone data and meteorological data. The results show that the most areas of Zhuhai are affected by high temperature during this heat wave incident. The hourly population exposure is directly proportional to hourly heat wave coverage. In terms of time dimension, the overall population exposure shows a trend of decreasing and then increasing. In terms of spatial dimensions, high population exposure is concentrated in areas such as primary and secondary schools, colleges and universities, office buildings, and residential areas. Low exposure is distributed in most of the mountainous areas along the southern coast. In addition, the leading factors that cause changes in population exposure in different periods of the heat wave cycle are different, which rely more on either climatic factors or population factors.