Predictive soil parent material mapping at a regional-scale: a Random Forest approach.

266 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Flood hazard risk assessment model based on random forest (2015, methodology): “Eleven different values of k, five thousand samples created in the previous section, and four series of samples randomly sampled from the five thousand sample points were analysed by 5-fold cross validation (Heung et al., 2014).”
Machine learning for predicting soil classes in three semi-arid landscapes (2015, background): “For example, in other DSM studies, Heung et al. (2014) included 272 distance to the nearest stream/river and relative hydrological slope position.”