Vote for the Best Paper in Pedometrics 2015

by · September 17, 2016

D G Rossiter, Chairman Pedometrics Awards Committee
Pedometrics commission of the International Union of Soil Sciences
e-mail: dgr2 AT cornell.edu

 

Dear fellow Pedometricians,

The Pedometrics Awards committee for the best paper award (Grunwald, McBratney, Oliver, Rossiter, Yang) received a strong response to our call for nominations, namely 21 interesting and relevant papers spread over nine journals. These were scored by the committee; the top five, from three journals, are now presented for your reading pleasure and evaluation.

Both the 2015 and 2016 awards will be presented at Pedometrics 2017 (25th anniversary of the first Pedometrics conference) in Wageningen (NL) 26 June- 1 July 2017; you are encouraged to attend (see information at http://www.pedometrics2017.org).

Please send in your votes for the best paper 2015 by 15-December-2016. We will repeat this process for the best paper in pedometrics 2016 beginning at the beginning of March (when you will have had a chance to digest all the papers from 2016) and ending just before Pedometrics 2017.

Please rank the papers in the “instant runoff” system: first choice, second choice, etc. up till the last paper you are willing to vote for, i.e., the last paper that you think would deserve the award. Votes should then be sent to me from a traceable e-mail address (to prevent over-voting). I will apply the instant runoff system to determine the winner. A co-author may not vote for her/his own paper(s), but may vote for any paper(s) where s/he is not a co-author.

The papers are listed here in order of DOI.

  1. Lark, R. M., & Knights, K. V. (2015). The implicit loss function for errors in soil information. Geoderma, 251–252, 24–32. http://doi.org/10.1016/j.geoderma.2015.03.014
  2. Brus, D. J. (2015). Balanced sampling: A versatile sampling approach for statistical soil surveys. Geoderma, 253, 111–121. http://doi.org/10.1016/j.geoderma.2015.04.009
  3. Orton, T. G., Pringle, M. J., & Bishop, T. F. A. (2016). A one-step approach for modelling and mapping soil properties based on profile data sampled over varying depth intervals. Geoderma, 262, 174–186. http://doi.org/10.1016/j.geoderma.2015.08.013
  4. Gasch, C. K., Hengl, T., Gräler, B., Meyer, H., Magney, T. S., & Brown, D. J. (2015). Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D + T: The Cook Agronomy Farm data set.
    Spatial Statistics, 14, Part A, 70–90. http://doi.org/10.1016/j.spasta.2015.04.001
  5. De Gruijter, J. J., Minasny, B., & McBratney, A. B. (2015). Optimizing stratification and allocation for design-based estimation of spatial means using predictions with error. Journal of Survey Statistics and Methodology, 3, 19–42. http://doi.org/10.1093/jssam/smu024

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