Articles | Volume 6, issue 2
SOIL, 6, 359–369, 2020
SOIL, 6, 359–369, 2020

Original research article 06 Aug 2020

Original research article | 06 Aug 2020

Disaggregating a regional-extent digital soil map using Bayesian area-to-point regression kriging for farm-scale soil carbon assessment

Sanjeewani Nimalka Somarathna Pallegedara Dewage et al.

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Cited articles

Akpa, S., Odeh, I., Bishop, T., Hartemink, A., and Amapu, I.: Total soil organic carbon and carbon sequestration potential in Nigeria, Geoderma, 271, 202-215,, 2016. 
Arrouays, D., McBratney, A. B., Minasny, B., Hempel, J. W., Heuvelink, G. B. M., MacMillan, R. A., Hartemink, A. E., Lagacherie, P., and McKenzie, N. J.: The GlobalSoilMap project specifications, Glob. Basis Glob. Spat. Soil Inf. Syst., Taylor & Francis Group, London, 9–12, 2014. 
Brus, D., Orton, T., Walvoort, D., Reijneveld, J., and Oenema, O.: Disaggregation of soil testing data on organic matter by the summary statistics approach to area-to-point kriging, Geoderma, 226–227, 151–159,, 2014. 
Cheng, Q.: Modeling Local Scaling Properties for Multiscale Mapping, Vadose Zone J., 7, 525,, 2008. 
Cressie, N.: Statistics for spatial data, Wiley, New York, 1991. 
Short summary
Most soil management activities are implemented at farm scale, yet digital soil maps are commonly available at regional/national scales. This study proposes Bayesian area-to-point kriging to downscale regional-/national-scale soil property maps to farm scale. A regional soil carbon map with a resolution of 100 m (block support) was disaggregated to 10 m (point support) information for a farm in northern NSW, Australia. Results are presented with the uncertainty of the downscaling process.