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  • High frequency soil sensor data for SOM input - Complex drivers of riparian soil oxygen variability revealed using self-organizing maps
  • Lancellotti, Brittany V; Postdoctoral Associate; Virgin Islands EPSCoR
    Underwood, Kristen L; Research Assistant Professor; University of Vermont
    Perdrial, Julia N; Associate Professor of Geochemistry; University of Vermont
    Adair, Carol E; Associate Professor; University of Vermont
    Schroth, Andrew W; Research Associate Professor; University of Vermont
    Roy, Eric D; Assistant Professor; University of Vermont
  • 2021-11-22
  • Lancellotti, B.V., K.L. Underwood, J.N. Perdrial, C.E. Adair, A.W. Schroth, and E.D. Roy. 2021. High frequency soil sensor data for SOM input - Complex drivers of riparian soil oxygen variability revealed using self-organizing maps ver 1. Environmental Data Initiative. https://doi.org/DOI_PLACE_HOLDER (Accessed 2024-12-27).

  • The provided datasets contain the original (non-normalized) high-frequency soil and meteorological observations that were fed to the Self-Organizing Map (SOM) in order to identify ranges of values associated with low and high soil O2 conditions. For the Champlain Valley (CV) site we used the natural breaks algorithm to subset the data into high and low O2 datasets. O2 values were consistently low at the Green Mountains (GM) site, so we ran a single SOM for all O2 values at this site. The original values were then range-normalized before they were fed to the SOM.

  • N: 44.993083      S: 44.67658      E: -72.440216      W: -73.251831
  • edi.549.1  (Uploaded 2021-11-22)  
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  • DOI PLACE HOLDER
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