Emerging Location-Based Service Data on Perceiving and Measuring Multifunctionality of Rural Space: A Study of Suzhou, China

Abstract

Understanding how human mobilities reconstruct contemporary rural space is of great significance to multifunctional rural transition. However, conventional approaches adopted by social surveys have a technological restriction on collecting data of individual behavior, such as limited samples, subjective self-reported data, and time-consuming investigation. This study proposes a data-driven methodology to explore multifunctionality of rural space by employing the real-time Tencent user quantity (RTUQ) data to analyze the quantity and distribution of observables in rural space. Based on over 250,000 records of hourly RTUQ data during a one-week research period, we perceive spatiotemporal variation of human mobilities in three differentiated villages in Suzhou, China, as well as measure function of residence, employment and consumption on holidays, weekdays and weekends using original equations of function index. Results show that the RTUQ data is valid and reliable for perceiving dynamic patterns of human mobilities at village level, as well as offering new implication for transitional pathways of decision-making. The proposed method is proved to be suitable for distinguishing and comparing multifunctionality of rural space in various times and places, future research on exploring contemporary rural space towards multifunctionality with more geospatial big data is put forward.