Vote for Best Paper in Pedometrics 2019
The Awards Committee of the Pedometrics Commission has received nominations from an open call for the Best Paper 2019 competition. With nominations from the panel members a total of 20 papers were considered, and each committee member selected their top 10 in rank order. The top five papers in terms of support across the committee as a whole are to be put to an open vote, and they are listed below.
Votes should be received by Murray Lark at murray.lark( at )nottingham.ac.uk before midday, GMT on 30th November 2020.
- Please rank papers in order, with the first paper the one you regard as most deserving. You need not provide a rank for every paper nominated.
- Votes must be received from a traceable email address, and if I cannot verify their origin they will be discarded.
- Authors/co-authors should not vote for their own papers.
- Please use the subject line “Best Paper in Pedometrics, 2019” in your email.
Murray Lark on behalf of the Awards Committee (Sabine Grunwald, Gerard Heuvelink, Lin Yang, Uta Stockman, Alessandro Samuel-Rosa).
- Chen, S, Mulder VL, Martin MP, Walter C, Lacoste M, Richer-de-Forges AC, Saby NPA, Loiseau T, Hu B, Arrouays D. 2019. Probability mapping of soil thickness by random survival forest at a national scale. Geoderma, 344, 184 – 194. https://doi.org/10.1016/j.geoderma.2019.03.016
- Ng, W., Minasny, B., Montazerolghaem, M., Padarian, J., Ferguson, R., Bailey, S. and McBratney, A.B., 2019. Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra. Geoderma, 352, 251 – 267. https://www.sciencedirect.com/science/article/pii/S0016706119300588
- Tabatabai, S., Knadel, M., Thomsen, A., Greve, M.H. 2019. On-the-go sensor fusion for prediction of clay and organic carbon using pre-processing survey, different validation methods, and variable selection Soil Sci Soc Am J, 83, 300 – 310. https://doi.org/10.2136/sssaj2018.10.0377
- Wadoux, A.M.J.-C., Brus, D.J., Heuvelink, G.B.M. 2019. Sampling design optimization for soil mapping with random forest Geoderma 355, 113913 https://doi.org/10.1016/j.geoderma.2019.113913
- Yang, Y., Viscarra Rossel, R.A., Li, S., Bissett, A., Lee, J., Shi, Z., Behrens, T., Court, L., 2019. Soil bacterial abundance and diversity better explained and predicted with spectro-transfer functions. Soil Biology and Biochemistry 129, 29–38.