Discovery of Changes from the Global Carbon Cycle and Climate System Using Data Mining

نویسندگان

  • Vipin Kumar
  • Michael Steinbach
  • Pusheng Zhang
  • Shashi Shekhar
  • Pang-Ning Tan
  • Christopher Potter
  • Steven Klooster
چکیده

The goal of our NASA sponsored project, “Discovery of Changes from the Global Carbon Cycle and Climate System Using Data Mining,” is to better understand global scale patterns in biosphere processes, especially relationships between the global carbon cycle and the climate system. To that end, we have developed data mining techniques to efficiently find spatio-temporal patterns in large Earth Science data sets. One such technique finds ecosystem disturbances in long-term, nonstationary fractional photosynthetically active radiation (FPAR) time series data. A key contribution of this work, which was the subject of a recent NASA press release, is the development of an automated technique for detecting abrupt changes in FPAR that take into account the timing, location, and magnitude of such changes. Using this technique, scientists were able to estimate that nearly 9 Pg (peta-grams) of carbon have been lost from the terrestrial biosphere to the atmosphere as a result of large-scale ecosystem disturbance events over an 18-year time period. Also, a novel clustering technique was developed to identify regions of uniform behavior in spatio-temporal data. The clusters produced by these methods are useful in discovering climate indices because they identify significant regions of the ocean or atmosphere where the behavior is relatively uniform over the entire area. Some of the discovered clusters correspond to known climate indices while other clusters are variants of known indices that appear to provide better predictive power for some land areas and still other clusters may represent potentially new Earth science phenomena. Other contributions include visualization techniques for finding interesting associations using land cover information and a filter-and-refine approach for efficiently processing correlation-based queries. Such innovative data analysis tools and techniques can aid NASA scientists in analyzing the growing datasets generated by NASA’s global observing satellites and offer an unprecedented opportunity for predicting and preventing future ecological problems by managing the ecology and health of our planet.

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تاریخ انتشار 2004