Divergence metrics for determining optimal training sample size in digital soil mapping

•We applied and compared divergence metrics for optimizing training sample size.•Feature space sampling was used to train random forest models of soil carbon.•We assessed sensitivity of divergence metrics to data binning and covariates.•We trained models across increasing sample sizes to optimize performance.•We related sample size from divergence metrics to optimal model performance.