Special Section on Advances in Remote Sensing for Monitoring Global Environmental Changes

Case study of visualizing global user download patterns using Google Earth and NASA World Wind

[+] Author Affiliations
Ziliang Zong

Texas State University, Department of Computer Science, 601 University Drive, San Marcos, Texas 78666

Joshua Job

L3 Communication Inc., 640 North 2200 West, Salt Lake City, Utah 84116

Xuesong Zhang

Joint Global Change Research Institute, Pacific Northwest National Laboratory, 5825 University Research Court, Suite 3500, College Park, Maryland 20740

Mais Nijim

Texas A&M-Kingsville, Department of Electrical Engineering and Computer Science, 700 University Boulevard, Kingsville, Texas 78363

Xiao Qin

Auburn University, Department of Computer Science and Software Engineering, Auburn, Alabama 36849

J. Appl. Remote Sens. 6(1), 061703 (Oct 09, 2012). doi:10.1117/1.JRS.6.061703
History: Received February 23, 2012; Revised August 27, 2012; Accepted September 18, 2012
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Abstract.  Geo-visualization is significantly changing the way we view spatial data and discover information. On the one hand, a large number of spatial data are generated every day. On the other hand, these data are not well utilized due to the lack of free and easily used data-visualization tools. This becomes even worse when most of the spatial data remains in the form of plain text such as log files. This paper describes a way of visualizing massive plain-text spatial data at no cost by utilizing Google Earth and NASA World Wind. We illustrate our methods by visualizing over 170,000 global download requests for satellite images maintained by the Earth Resources Observation and Science (EROS) Center of U.S. Geological Survey (USGS). Our visualization results identify the most popular satellite images around the world and discover the global user download patterns. The benefits of this research are: 1. assisting in improving the satellite image downloading services provided by USGS, and 2. providing a proxy for analyzing the “hot spot” areas of research. Most importantly, our methods demonstrate an easy way to geo-visualize massive textual spatial data, which is highly applicable to mining spatially referenced data and information on a wide variety of research domains (e.g., hydrology, agriculture, atmospheric science, natural hazard, and global climate change).

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Ziliang Zong ; Joshua Job ; Xuesong Zhang ; Mais Nijim and Xiao Qin
"Case study of visualizing global user download patterns using Google Earth and NASA World Wind", J. Appl. Remote Sens. 6(1), 061703 (Oct 09, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.061703


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