How weather impacts the citizens' activity patterns in southern China? Enlightenment from large-scale mobile phone signaling data of Guangzhou

In the realm of smart cities, understanding citizens' activity patterns is essential for effective urban planning and development. Weather condition plays a crucial role in shaping citizen's activities. This study investigates the impact of weather conditions on activity patterns by examining variations in visitor numbers at three types of sites in Guangzhou, China: parks, pedestrian streets and shopping malls, representing outdoor, semi-outdoor and indoor urban environment, respectively. Mobile phone signaling data and meteorological data were collected over two months, July and January 2022, representing the typical summer and winter conditions. With hourly visitor counts for the selected locations scaling to the magnitude of millions, the dataset offers significant representativeness. Our findings underscore that, predominantly temperature, exerts a marked influence on the choice of activities among Guangzhou's populace. As temperature rose, even during the hot summer month, the total number of visitors across the three types of locations increased. However, the frequency of park visitors exhibited heightened sensitivity to meteorological variations in comparison to their counterparts in pedestrian streets and shopping malls, with park visitor numbers in winter oscillating over a six-fold range due to climatic shifts. In contrast, the trend of visitor number to pedestrian streets and shopping malls tends to be less affected by weather conditions. Notably, the impact of weather on activity patterns varied among different groups. Males appeared more attuned to external conditions than females, with their presence in parks surging more noticeably with temperature increments-a gender ratio surpassing 1.7 in summer, further accentuating in winter. This starkly contrasts the gender ratios in pedestrian streets and malls, which aligned closely with the city's overall demographic distribution. Age emerged as another differentiating factor. Younger individuals (19-29 years) demonstrated a higher adaptability to the local high-temperature weather conditions, while during the winter season, a significant decrease in the number of visitors from this group was observed as the temperature dropped. Remarkably, within a narrow temperature bracket of 27 degrees C to 27.5 degrees C, the hourly count of visitors aged 19-29 on pedestrian streets experienced a six-fold variance, ranging from just over 0.1 million to nearly 0.7 million. This suggests that factors beyond weather play a significant role in influencing the mobility choices of young adults. In contrast, the 30-39 age bracket showcased more robust correlations with weather patterns. The number of older visitors remained relatively stable and did not change significantly with weather changes, especially those aged 60 and above. Drawing on robust evidence from large-scale mobile phone signaling data, this study can inform local policy-making in smart city development.