Full metadata
Title
Spatiotemporal data mining, analysis, and visualization of human activity data
Description
This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and geovisualization techniques. Three different types of spatiotemporal activity data were collected through different data collection approaches: (1) crowd sourced geo-tagged digital photos, representing people's travel activity, were retrieved from the website Panoramio.com through information retrieval techniques; (2) the same techniques were used to crawl crowd sourced GPS trajectory data and related metadata of their daily activities from the website OpenStreetMap.org; and finally (3) preschool children's daily activities and interactions tagged with time and geographical location were collected with a novel TabletPC-based behavioral coding system. The proposed methodology is applied to these data to (1) automatically recommend optimal multi-day and multi-stay travel itineraries for travelers based on discovered attractions from geo-tagged photos, (2) automatically detect movement types of unknown moving objects from GPS trajectories, and (3) explore dynamic social and socio-spatial patterns of preschool children's behavior from both geographic and social perspectives.
Date Created
2012
Contributors
- Li, Xun (Author)
- Anselin, Luc (Thesis advisor)
- Koschinsky, Julia (Committee member)
- Maciejewski, Ross (Committee member)
- Rey, Sergio (Committee member)
- Griffin, William (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
x, 181 p. : ill. (some col.)
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.15915
Statement of Responsibility
by Xun Li
Description Source
Retrieved on Sept. 30, 2013
Level of coding
full
Note
thesis
Partial requirement for: Ph.D., Arizona State University, 2012
bibliography
Includes bibliographical references
Field of study: Geography
System Created
- 2013-01-17 06:36:50
System Modified
- 2021-08-30 01:44:03
- 3 years 2 months ago
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