Digital Soil Mapping Using Random Forests Model in Abyek, Qazvin Province

Today, there is great demand for accurate soil information to determine the relationship between soil and landscape, and easy updating of soil maps has increasingly gained importance. Digital soil mapping techniques can be cost-effective solutions to obtain information dealing with the soil types over large areas. The objective of this study was to provide a digital soil map in the Abyek region of Qazvin province using random forest model for management purposes and sustainable land use planning. To this end, soil samples were collected based on cLHS. After the laboratory analysis, using random forest model and auxiliary variables derived from a digital elevation model with a spatial resolution of 30 m and Landsat 8 imagery, the modeling and preparation of regional soil maps were performed. Out of 7261 ha, the dominant soil was classified as Loamy-skeletal, mixed, superactive, thermic Typic Calcixerepts. The results showed that soil modeling using random forest algorithm could accurately predict (Kappa coefficient ~ 0. 83) soil classes in the region.