Non-Spatial and Spatial Statistics for Analysing Human Perception of the Built Environment

Abstract

The world is rapidly urbanising, which makes the liveability of cities an important issue in our times. New sources of data on urban citizens including social media, video footage, and even fitness data, are also becoming increasingly available. This study is motivated by these two trends. We analyse data gathered in a Virtual Reality experiment to find correlations between features of the urban environment and people’s perceptions of this environment. In particular, the aim is to further our knowledge of which kinds of environments are perceived positively or negatively by people. The analysis is made up of a non-spatial, a spatial as well as a qualitative section. We find that neither human perceptions nor spatial features are distributed randomly in space. Of ten features measured, pedestrian congestion is found to be most reliably correlated with positive perceptions of the urban environment. This study contributes to the existing work in the field by suggesting new environmental variables to be included in future work, as well as by exploring which types of data analysis techniques are most appropriate for architectural and urban planning research.