Cluster analysis-based approaches for geospatiotemporal data mining of massive data sets for identification of forest threats
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filed under:
MODIS,
k-means clustering,
anomaly detection,
remote sensing,
high performance computing,
data mining,
NDVI
Cluster analysis-based approaches for geospatiotemporal data mining of massive data sets for identification of forest threats
Mills, R. T.
Hoffman, F. M.
Kumar, J.
Hargrove, W.
2011
Pgs 1612–1621 In: Proceedings of the International Conference on Computational Science (ICCS 2011), Volume 4 of Procedia Comput. Sci. M. Sato, S. Matsuoka, P.M. Sloot, G.D. van Albada, and J Dongarra, (Eds). Elsevier, Amsterdam
Cluster_analysis-based_approaches.pdf
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PDF document,
1779Kb
