Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility Using ALOS/PALSAR Data

Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility Using ALOS/PALSAR Data

Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), a...

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Bibliographic Details
Main Authors: Shahab S. Band, Saeid Janizadeh, Sunil Saha, Kaustuv Mukherjee, Saeid Khosrobeigi Bozchaloei, Artemi Cerdà, Manouchehr Shokri, Amirhosein Mosavi
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Land
Subjects:
random forest
support vector machine
Bayesian generalized linear model (Bayesian GLM)
machine learning
susceptibility
spatial modeling
Online Access:https://www.mdpi.com/2073-445X/9/10/346

Internet

https://www.mdpi.com/2073-445X/9/10/346

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