9 October 2012 Case study of visualizing global user download patterns using Google Earth and NASA World Wind
Ziliang Zong, Joshua Job, Xuesong Zhang, Mais Nijim, Xiao Qin
Author Affiliations +
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).
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2012/$25.00 © 2012 SPIE
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," Journal of Applied Remote Sensing 6(1), 061703 (9 October 2012). https://doi.org/10.1117/1.JRS.6.061703
Published: 9 October 2012
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Visualization

Earth observing sensors

Satellites

Satellite imaging

Java

Landsat

Image processing

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