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1000
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Abstract/Summary
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Soil electrical conductivity (ECa) data derived from electromagnetic induction (EMI) is valuable for estimating peat thickness and soil organic carbon stocks (SOCstocks). However, generating ECa maps locally using geostatistics limits the coverage area. This study explores the use of digital soil mapping (DSM) with random forest (RF) and universal kriging (UK) to create high-resolution ECa maps from field survey EMI data. The objective is to enhance the predictive accuracy of SOCstocks models in peatlands by incorporating these ECa maps as environmental variables.
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