Nominees for the “Best Paper in Pedometrics 2013”
D G Rossiter,
Chairman Pedometrics Awards Committee,
The committee received only nine nominations. These were all scored by the committee and the top five are now presented for your reading pleasure and evaluation. Following are the references, in first author alphabetic order, and abstracts. 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.
Now, Please vote for the 2013 Best Paper. The deadline for voting is end 2014. Please rank the papers in the “instant runoff” system (first choice, second choice… up till the last paper the voter is willing to vote for, i.e., the last paper that the voter thinks would deserve the award). Votes should then be sent to me (firstname.lastname@example.org) 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 vote for her/his own paper(s).
The Best Paper will be announced early next year and the award will be presented in Pedometrics 2015 (September) in Córdoba.
And the Nominees are:
1. Beaudette, D.E., Roudier, P., O’Geen, A.T., 2013. Algorithms for quantitative pedology: A toolkit for soil scientists. Computers & Geosciences 52, 258–268. doi:10.1016/j.cageo.2012.10.020 (OPEN ACCESS until end of 2014)
2. Lark, R.M., Lapworth, D.J., 2013. The offset correlation, a novel quality measure for planning geochemical surveys of the soil by kriging. Geoderma 197–198, 27–35. doi:10.1016/j.geoderma.2012.12.020. pdf available here
3. Malone, B.P., McBratney, A.B., Minasny, B., 2013. Spatial Scaling for Digital Soil Mapping. Soil Science Society of America Journal 77, 890-902. doi:10.2136/sssaj2012.0419 (OPEN ACCESS until end of 2014)
4. Meerschman, E., Van Meirvenne, M., Van De Vijver, E., De Smedt, P., Islam, M.M., Saey, T., 2013. Mapping complex soil patterns with multiple-point geostatistics. European Journal of Soil Science 64, 183–191. doi:10.1111/ejss.12033
5. Mulder, V.L., Plötze, M., de Bruin, S., Schaepman, M.E., Mavris, C., Kokaly, R.F., Egli, M., 2013. Quantifying mineral abundances of complex mixtures by coupling spectral deconvolution of SWIR spectra (2.1–2.4 μm) and regression tree analysis. Geoderma 207–208, 279–290. doi:10.1016/j.geoderma.2013.05.011. pdf available here