An algorithm for clustering profile data and its application to near-surface ice content data from wet coastal tundra soils near Barrow, Alaska

An algorithm to cluster profile data into groups that minimize the sum of the intra-group variances was applied to near-surface soil ice content data collected near Barrow, Alaska, in wet tundra terrain. When the algorithm was requested to produce 2–5 groups and group mean profiles, the results were...

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Bibliographic Details
Published in:Journal of the International Association for Mathematical Geology
Main Authors: Estabrook, George F., Outcalt, Samuel I.
Other Authors: The University of Michigan Herbarium, and Division of Biological Sciences, 48109, Ann Arbor, Michigan, USA, Department of Geological Sciences, University of Michigan, 48109, Ann Arbor, Michigan, USA, Ann Arbor
Format: Article in Journal/Newspaper
Language:English
Published: Kluwer Academic Publishers-Plenum Publishers; Plenum Publishing Corporation 1984
Subjects:
Ice
Online Access:https://hdl.handle.net/2027.42/43194
https://doi.org/10.1007/BF01032216
Description
Summary:An algorithm to cluster profile data into groups that minimize the sum of the intra-group variances was applied to near-surface soil ice content data collected near Barrow, Alaska, in wet tundra terrain. When the algorithm was requested to produce 2–5 groups and group mean profiles, the results were consistant with the modern theory of ice segregation. This process produces much of the variability of near surface soil ice stratigraphy in nature. These results strengthen the case for employing the algorithm on other profile data sets as an aid in hypothesis formulation. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/43194/1/11004_2005_Article_BF01032216.pdf