Spatial prediction of major soil properties using Random Forest techniques - A case study in semi-arid tropics of South India

• Published in: Geoderma Regional Vol. 10; pp. 154 - 162
• Main Authors: Dharumarajan, S., Hegde, Rajendra, Singh, S.K.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2017
• Subjects: algorithms; carbon; case studies; data collection; Digital soil mapping; drainage; electrical conductivity; India; land use; landforms; landscapes; model validation; normalized difference vegetation index; Prediction; Random Forest model; remote sensing; Soil properties; surveys; topography; tropics; Validation; vegetation; India; Validation; Digital soil mapping; Soil properties; Random Forest model; Prediction

The purpose of the study is to map the spatial variation of major soil properties in Bukkarayasamudrum mandal of Anantapur district, India using Random Forest model. The study area is divided into different Physiographic Land Units (PLU) based on landform, landuse and slope. Random Forest model (RFM...