Paper
11 November 1996 Emerging technology becomes an opportunity for EOS
Giulietta S. Fargion, Robert Harberts, Jeffrey G. Masek
Author Affiliations +
Abstract
During the last decade, we have seen an explosive growth in our ability to collect and generate data. When implemented, NASA's Earth observing system data information system (EOSDIS) will receive about 50 gigabytes of remotely sensed image data per hour. This will generate an urgent need for new techniques and tools that can automatically and intelligently assist in transforming this abundance of data into useful knowledge. Some emerging technologies that address these challenges include data mining and knowledge discovery in databases (KDD). The most basic data mining application is a content-based search (examples include finding images of particular meteorological phenomena or identifying data that have been previously mined or interpreted). In order that these technologies be effectively exploited for EOSDIS development, a better understanding of data mining and the requirements for using this technology is necessary. The authors are currently undertaking a project exploring the requirements and options of content-based search and data mining for use on EOSDIS. The scope of the project is to develop a prototype with which to investigate user interface concepts, requirements, and designs relevant for EOSDIS core system (ECS) subsystem utilizing these techniques. The goal is to identify a generic handling of these functions. This prototype will help identify opportunities which the earth science community and EOSDIS can use to meet the challenges of collecting, searching, retrieving, and interacting with abundant data resources in highly productive ways.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Giulietta S. Fargion, Robert Harberts, and Jeffrey G. Masek "Emerging technology becomes an opportunity for EOS", Proc. SPIE 2820, Earth Observing System, (11 November 1996); https://doi.org/10.1117/12.258111
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Cited by 2 scholarly publications.
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KEYWORDS
Data mining

Databases

Prototyping

Data modeling

Computing systems

Earth sciences

Machine learning

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