Statistics – Applications
Scientific paper
Sep 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004esasp.553e...6k&link_type=abstract
Proceedings of ESA-EUSC 2004 - Theory and Applications of Knowledge-Driven Image Information Mining with Focus on Earth Observa
Statistics
Applications
Scientific paper
To address the environmental and economic challenges of the 21st century it is incumbent upon the global community to evolve and sustain a global observation network. These observations serve as the foundation for the models that are used to describe Earth processes and can be used to predict the effect of different forcings on the planet (natural and anthropogenic). As this observational data accumulates in global archives new opportunities become available for knowledge discovery about the Earth system. However, access to these observational data is optimized for the science teams for whom the instruments were launched and access by operational users may be problematic. Also, sensor fusion and data mining algorithms are generally not considered as necessary exploration modes of the archives. This paper will address the need for global observations from a variety of vantage points, some descriptions of global observation archives within the United States, recommendations for better access to image archives to facilitate image mining, and the research agenda for data archiving and distribution systems being developed by the IEEE Geoscience and Remote Sensing Society.
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