Kolloquium Geoinformatik Modelling Intra-urban Human Activity Patterns using Crowdsourcing and Geosocial Media Data

The way people live in cities forms human activity patterns, which affects how urban systems work and plays a key role in a variety of urban applications, such as urban planning, emergency response, transportation planning and epidemic prevention. Therefore, it is essential to understand human activity patterns, where precise prediction of human movements and mechanistic modelling of human activity patterns are the two keys. Most of existing work on prediction of human movements cannot deal with activity changes, leading to a negative impact on the predictive accuracy. Furthermore, the majority of current work on modelling human activity patterns are mainly researched from spatiotemporal perspectives, but the motivation behind is usually being neglected, which is crucial to understanding activity changes. In this presentation, I first introduce two of my PhD work: 1) a novel human mobility predictive model with consideration of human activity changes; and 2) a new approach of modeling human activity patterns, which enables to uncover human activity patterns not only from spatiotemporal dimensions but also considering the motivation behind. Then some ideas I am looking to further explore are proposed and discussed.