Authors: Jizhe Xia*,
Topics: Geographic Information Science and Systems
Keywords: Big Data, WebGIS, spatiotemporal optimization
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Marshall North, Marriott, Mezzanine Level
Presentation File: No File Uploaded
Learned from the GEOSS Clearinghouse operating experience, we summarized three Earth Observation (EO) Big Data access challenges: fast access, accurate access and global access, and two essential research questions: are there any spatiotemporal patterns when end users access to EO data, and how to utilize these spatiotemporal patterns to better facilitate EO Big Data access? To tackle two research questions, we conducted a two-year pattern analysis with 2+ million user access records. The spatial effect, temporal effect and spatiotemporal effect of user-data interactions were explored. For the second research question, we developed three spatiotemporal optimization strategies to respond three access challenges: a) spatiotemporal indexing to accelerate data access, b) spatiotemporal service modeling to improve data access accuracy and c) spatiotemporal cloud computing to enhance global access. This research is sort of a pioneering framework for spatiotemporal optimization on EO Big Data access and valuable for other multidisciplinary geographic data and information research.