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Abstract
This research maps land susceptibility to wind erosion hazard in Isfahan province, Iran, using sixteen advanced regression-based machine learning methods. Thirteen factors influencing wind erosion were analyzed for multicollinearity, and model performance was assessed using RMSE, MAE, MBE, and Taylor diagrams. Five models (MMLPNN, SGAM, Cforest, BGAM, and SGB) showed high prediction accuracy, with DEM, precipitation, and vegetation (NDVI) identified as the most critical factors.
Publisher
Scientific Reports
Published On
Nov 24, 2020
Authors
Hamid Gholami, Aliakbar Mohammadifar, Dieu Tien Bui, Adrian L. Collins
Tags
wind erosion
machine learning
hazard mapping
regression analysis
Isfahan province
environmental factors
predictive modeling

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