Visual Analysis of Urban Dynamics Based on Human Mobility Data

PhD Thesis Proposal Defence


Title: "Visual Analysis of Urban Dynamics Based on Human Mobility Data"

by

Mr. Wenchao WU


Abstract:

Without doubt, we are in the midst of a data explosion. A variety of data 
tracking human mobility, namely human mobility data, has been generated 
and collected within urban context, providing unprecedented opportunities 
to understand regional dynamics in urban area, which is of great social 
and business value in a variety of applications. However, due to large 
volumes and dynamic correlations of these data as well as high complexity 
of analytical tasks in real world applications, it is challenging for 
analysts to carry out in-depth analysis and extract valuable information. 
It often requires integrating human perception in the data exploration 
process, triggering a broad use of visual analytics. With visual 
analytics, we can include human perception in the data exploration process 
efficiently and combine the flexibility, creativity and domain knowledge 
of human beings with enormous storage capacity and computational power of 
today's computers.

In this thesis, we introduce three advanced visual analysis techniques for 
uncovering regional dynamics in urban area from different aspects based on 
heterogeneous human mobility data. In particular, we first study the 
subject matter of regional boundary change and present BoundarySeer. It is 
a visual analytics system consisting of four major viewers to facilitate 
the general analytical tasks dealing with boundary changes of a region in 
urban area. Secondly, a visual analytics system, TelCoVis, is presented to 
facilitate the exploration of co-occurrence in human mobility (i.e. people 
from two regions visit an urban place during the same time span) and 
hidden correlations based on telco data. The system integrates a novel 
contour-based treemap with extended visualization techniques to enhance 
analysts' perception for a comprehensive exploration of coordinated 
relationships among different regions and identify interesting patterns. 
The third study proposes a novel visual analysis approach to investigate 
people's activity patterns for an interactive region segmentation based on 
three types of heterogeneous mobility data (i.e. taxi trajectories, metro 
passenger RFID card records and telco data). Combining advanced 
visualization techniques (e.g. NMF-based method to capture latent activity 
patterns, as well as metric learning to calibrate and supervise the 
underlying analysis) with intuitive visual designs (e.g. a voronoi-based 
texture map with elliptical activity glyphs to summarize people's 
activities and enable a fast comparison), MobiSeg not only makes it easier 
for domain experts to perform a series of analyses on region segmentation, 
but also enables a new way to explore data from multiple levels and 
perspectives.

To the best of our knowledge, the above techniques are cutting-edge 
studies of visually analyzing regional dynamics in urban area based on 
heterogeneous human mobility data. To validate the effectiveness and 
usefulness of our study, all the proposed techniques and systems are 
deployed to analyze real-world datasets and evaluated by domain experts or 
target users.


Date:			Monday, 16 May 2016

Time:                  	1:00pm - 3:00pm

Venue:                  Room 4472
                         (lifts 25/26)

Committee Members:	Prof. Lionel Ni (Supervisor)
 			Prof. Huamin Qu (Supervisor)
  			Dr. Xiaojuan Ma (Chairperson)
 			Prof. Cunsheng Ding
  			Prof. Chiew-Lan Tai


**** ALL are Welcome ****