Unfolding the City: Spatial Preference Based on Individual Demographic Characteristics

Abstract

A city is shaped not only by its assembled infrastructures but also by the people living inside it. People with a wide range of individual demographic characteristics visit places at different weights and with different preferences, sculpting a city into a space of diverse spatial preferences. Due to the challenges in the collection and analysis of data considering multi-dimensional demographic characteristics, the daily movement of characterized individuals has been less studied. Therefore, we aim to develop a visual analytics system to better explore spatial preference based on individual demographic characteristics. We take a step forward and perform an online survey to collect individual profiles and movements from volunteers on a large-scale. Then, we design a visual analytic system to investigate the spatial preferences of groups by specifying demographic characteristics. To facilitate the identification of characterized groups, individuals are embedded in t-SNE projection for an abstract overview, and vivid graphics are drawn by a data-driven profile method for detailed examination. A 2.5D spatial visualization is proposed to maintain a compact multivariable analysis by relaxing the z-axis to encode information, such as visiting frequency, demands, and traveling distance. Together with a cross-filter and flexible 2.5D interactions, the effectiveness and usability of the system are demonstrated well by a study conducted in Shenzhen.