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.


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (02 Jun 2020) by Bas van Wesemael
AR by Lorena Grabowski on behalf of the Authors (19 Jun 2020)  Author's response
ED: Publish as is (22 Jun 2020) by Bas van Wesemael
ED: Publish as is (25 Jun 2020) by Kristof Van Oost(Executive Editor)
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.