Prediction of Soil Properties Using Random Forest with Sparse Data in a Semi-Active Volcanic Mountain

Abstract

Understanding spatial variations of soil properties is necessary for the management of rangelands vegetation ecosystem. The present study aimed to assess the spatial variations of soil properties in the hillslope of the Taftan semi-active volcanic mountain, Sistan and Baluchestan Province, south-eastern Iran. The locations of 30 sampling points were determined using random - systematic method and soil samples were taken from two depths: 0–30 and 30–60 cm. Spatial distribution of soil properties and relationships between soil properties and covariates were investigated using Random forest method. Model validation was done through 10-fold cross-validation approach. Based on results elevation, channel network base level and vertical distance to channel network, were the most importance environmental variables in predicting of the some soil characteristics such as soil clay, silt, sand, SOC, and EC in two studied depths. The maps produced indicated higher clay at 30–60 depth in the higher elevations. EC amounts were increased in the lower parts of the mountain because of leaching. Furthermore, the highest map accuracy was related to EC map at both depths and clay at 30–60 depth. The prediction maps of other properties of soil had low accuracy.