Vote for the “Best Paper in Pedometrics 2014”

by · May 3, 2015

D G Rossiter, Chairman Pedometrics Awards Committee

e-mail: dgr2@cornell.edu

 

Dear fellow Pedometricians,

The Pedometrics Awards committee for the best paper award (Grunwald, McBratney, Oliver, Rossiter, Yang) received a god response to our call for nominations, namely 18 interesting and relevant papers. These were scored by the committee. and the top five are now presented for your reading pleasure and evaluation.

Although we received nominations for papers in eight journals, the five rated best by the committee were all from European Journal of Soil Science (2) and Geoderma (3). Two papers deal mainly with sampling, one with improving existing soil maps, one with 3D mapping of soil properties, and one on numerical soil classification.

There is a nice mix: geostatistics, sampling design, a pedometrics computation toolkit, spatial scaling, and numerical methods for spectroscopy. All are quite novel in their own way, and will surely stimulate and educate the reader – but of course many of you will have already read the papers when they appeared back in 2014.

The award will be presented at Pedometrics 2015, 14-18 September in Córdoba (E). Since many of you take some time off in August, please send in your votes by 31 July 2015. This gives you three months to rea these excellent papers.

Please rank the papers in the “instant runoff” system: first choice, second choice… 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 (https://en.wikipedia.org/wiki/Instant-runoff_voting) to determine the winner. A co-author may vote for her/his own paper(s).

The papers are listed here in order of DOI (so pedometrics is becoming bibliometric).

 

  1. Odgers, N. P., Sun, W., McBratney, A. B., Minasny, B., & Clifford, D. (2014). Disaggregating and harmonising soil map units through resampled classification trees. Geoderma, 214–215, 91–100. http://doi.org/10.1016/j.geoderma.2013.09.024

 

  1. Hughes, P. A., McBratney, A. B., Minasny, B., & Campbell, S. (2014). End members, end points and extragrades in numerical soil classification. Geoderma, 226–227, 365–375. http://doi.org/10.1016/j.geoderma.2014.03.010

 

  1. Poggio, L., & Gimona, A. (2014). National scale 3D modelling of soil organic carbon stocks with uncertainty propagation – An example from Scotland. Geoderma, 232, 284–299. http://doi.org/10.1016/j.geoderma.2014.05.004

 

  1. Brus, D. J. (2014). Statistical sampling approaches for soil monitoring. European Journal of Soil Science, 65(6), 779–791. http://doi.org/10.1111/ejss.12176

 

  1. Lark, R. M., Rawlins, B. G., Robinson, D. A., Lebron, I., & Tye, A. M. (2014). Implications of short-range spatial variation of soil bulk density for adequate field-sampling protocols: methodology and results from two contrasting soils. European Journal of Soil Science, 65(6), 803–814. http://doi.org/10.1111/ejss.12178

 

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