2014/08 - present, Assistant Professor, Department of Geography, Texas State University, TX, USA
2014/08 - present, Faculty Scholar, Texas Center for Geographic Information Science, Texas State University, TX, USA
2012/04-2013/12, Visiting Researcher (Academic Guest) , Institute of Cartography and Geoinformation, ETH Zurich, Switzerland
- Exploring human mobility from social network usage - a cross country and cross-cultural study (in progress)
The continued development of social networking websites like Twitter, Flickr and Facebook provides ever-increasing opportunities to explore activity patterns of population groups in diverse geographic environments, social statuses and cultural backgrounds. These sites can be used to gain insight into human activity in an effort to analyze long term choices such as where one lives; medium term choices such as the purchase of cars; and shorter term choices such as activity scheduling on a weekly or daily scale. Despite of potential issues such as low sampling resolution, previous studies have demonstrated the effectiveness of these datasets to construct a more powerful mobility model. However, most existing research focuses only on travel distances and the overall distribution of human mobility without looking into various aspects of human activities. Additionally, there is a deficit in research on how these datasets can be utilized in a cross-country and/or cross-cultural setting. Hence, the proposed research concentrates on characterizing human activities in various cities and countries based on social media data (with a focus on China, which is considered as one of the most rapidly-developing countries globally).
- Characterizing human mobility from mobile phone usage (completed)
This project was funded by the Swiss national science fundation (SNSF) (PI: M.Raubal) and US Department of Transportation (PI: M.Raubal, Co-PI: Y.Yuan).
Our mobile information society depends increasingly on the use of Information and Communication Technologies (ICTs) such as mobile phones. People’s usage of these technologies impacts many aspects of their lives but the relationship between ICT and human activities is not fully known. An understanding of this relationship will help in predicting people’s mobility patterns and provide important guidelines for maintaining sustainable transportation, updating environmental policies, and designing early warning and emergency response systems. The goal of this project is to develop a framework for extracting and characterizing human mobility patterns from georeferenced mobile phone datasets. We analyze the different types of information that can be stored in mobile phone datasets, and develop human mobility models and data mining methodologies for spatio-temporal knowledge discovery. These models provide the basis for investigating and quantifying the relationship between human physical travel, communication travel, and environmental structure. Our research also addresses issues of uncertainty, which arise from the natural variability of human mobility, the inaccuracy and imprecision of recorded trajectories, and the imperfection of the underlying models. In order to evaluate the developed models and the relationship between human mobility patterns, spatial structure, and mobile phone usage, we will utilize a large dataset of northeast China. This research will enhance our understanding of the relationship between human mobility and ICT in general, and between human mobility patterns and mobile phone usage in particular. We will advance conventional geographic knowledge discovery by focusing on knowledge extraction from sparse datasets with low resolution and individual attributes. The case study from northeast China allows us to examine the influence of mobile phone usage in a highly populated and rapidly developing country.
Figure 1. Trajectory of an example user
Figure 2. Mobility clustering at different time of a day
- Place name searching method and system based on context (completed)
With the development of World Wide Web (WWW), unstructured or semi-structured documents that contain place names have been recognized as one important component of modern geographical information. This project designed and implemented of a geographical knowledge-informed digital gazetteer service, KIDGS (funded by the Chinese National Science Foundation, PI: Y. Liu). It provided a standard web service which enabled XML-based access interfaces for various applications. At present, many digital gazetteer systems are implemented directly based on relational databases. However, several components in geographical knowledge, such as category and relation information, should also be explicitly represented to support various queries. KIDGS adopted OWL(Protégé) and PostGIS to implement the conceptual level and engineering level of geographic knowledge.
Figure 1. The framework of KIDGS