Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and mapping using three machine learning algorithms

• Published in: Geoderma Vol. 340; pp. 55 - 69
• Main Authors: Amiri, Mahdis, Pourghasemi, Hamid Reza, Ghanbarian, Gholam Abbas, Afzali, Sayed Fakhreddin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.04.2019
• Subjects: algorithms; artificial intelligence; Boruta algorithm; clay; computer software; data collection; drainage; Evidential belief function; geographic information systems; Gully erosion; Integrating GIS and R; Iran; land use; Machine learning; normalized difference vegetation index; prediction; rain; ravines; rivers; roads; sand; silt; soil properties; surveys; watershed management; watersheds; Iran; Integrating GIS and R; Evidential belief function; Boruta algorithm; Gully erosion; Machine learning

The Maharloo watershed has witnessed many gullies in the recent due to the specific topo-climatic conditions and man-made activities in that area. The present study is set out to address this issue by producing gully erosion prediction maps via three machine learning algorithms including RF, SVM and...