Abstract
The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on satellites, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and spatio-temporal data. These massive and information-rich datasets offer huge potential for understanding and predicting the behavior of the Earth’s ecosystem and for advancing the science of climate change.
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© 2010 Springer-Verlag Berlin Heidelberg
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Kumar, V. (2010). Discovery of Patterns in Global Earth Science Data Using Data Mining. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2010. Lecture Notes in Computer Science(), vol 6118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13657-3_2
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DOI: https://doi.org/10.1007/978-3-642-13657-3_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13656-6
Online ISBN: 978-3-642-13657-3
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