Investigating pedestrian walkability using a multitude of Seoul data sources

Currently walking is a multidisciplinary and emerging point of attention for urban sustainability and for ensuring the quality of pedestrian environments. In order to understand pedestrian behaviour, walkability researches estimate the factors which affect the level of pedestrian satisfaction. Past studies focused on the relationship between environmental factors and pedestrian behavioural outcomes. In this study, we developed pedestrian satisfaction multinomial logit models using various data sets, examining the relative impact of five differently themed sets of attributes: personal, walk-facilities, land-use, pedestrian volumes, and weather-related variables. The results show that the personal variability attributes were selected as the most significant. We investigated the effects of personal variability, such as the spatial cognition level and travel purpose, and detailed effects of environmental features. In addition, crowdedness, land-use types, and residential information were investigated. The results from this study offer contributions by providing evidence of the importance of personal and contextual variables in influencing pedestrian walkability.