Weather Effects on the Patterns of People's Everyday Activities: A Study Using GPS Traces of Mobile Phone Users

Abstract

This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people's regular activity patterns, certain weather conditions affected people's movements and activities noticeably at different times of the day. On cold days, people's activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people's activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM–1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people's accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics.

Testing time-sensitive influences of weather on street robbery

“…A cold winter wind appears to discourage outside activity. Indeed, wind has been found to be an important condition in perceptions of thermal comfort (Walton et al 2007), and high wind speeds lead to people staying indoors more (Horanont et al 2013). It is interesting that other weather variables do not show noteworthy associations, but this can be explained by the microclimate of the study area (i.e.…”

“…Numerous scholars have postulated that people are more likely to stay indoors in adverse weather and be outdoors when weather is pleasant (Brunsdon et al 2009;Hipp et al 2004;Lab & Hirschel 1988;LeBeau & Corcoran 1990;, and this is borne out by empirical findings in transport studies and public health (Böcker et al 2013;Horanont et al 2013;Tucker & Gilliland 2007). Outdoor activities usually peak in the summer months in temperate climates when the days are longer, whereas regions with harsh weather conditions in winter have a population used to staying at home for prolonged periods.…”

Event Detection Using Mobile Phone Mass GPS Data and Their Reliavility Verification by DMSP/Ols Night Light Image

“…Methods by Horanont (2010), Horanont et al (2013), and Akiyama et al (2014) were used for these calculations.…”

Evaluating the Human Damage of Tsunami at Each Time Frame in Aggregate Units Based on GPS data

“…The stay point defines that the representative point of a user remains a certain time and in a certain range. In this study, more than 15 minutes and the radius of 300m as a condition of stay, and the central point of maximum rectangle from the column of points of staying period to be the stay points (Horanont (2010); Horanont et al (2013);Hadano (2013)). Also this data holding time information of the arrival time and the departure time for each stay point.…”