Summary statistics for mapping accuracy assessed using 5–fold cross-validation.

ME is the mean error, RMSE the root mean squared error, sg1km are the SoilGrids1km map, rf represents random forest model predictions and lm the linear model predictions (trend model predictions only). The t-test evaluates the difference between the mean errors of the rf and lm models with alternative hypothesis that the difference is greater than 0. The F-test evaluates the ratio between the residual variances of the rf and lm models with alternative hypothesis that the difference is greater than 1. Σ% indicates amount of variation explained by the prediction models and ΔRMSE% indicates improvement in RMSE in percentages compared to the lm model. The ‘⋆⋆⋆’ indicates significance at the 99% probability level. For all soil properties except PHIHOX, SNDPPT, SLTPPT, CLYPPT and BLD, the Σ%, the t-test, and the F-test have been calculated in log-transformed space. SP-SS are the predictions at Sentinel Sites produced using models fitted from AfSP data, SS-SP are the predictions at legacy soil profiles produced using AfSS data. See Table 1 for more details.