GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran

GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran

In the present study, gully erosion susceptibility was evaluated for the area of the Robat Turk Watershed in Iran. The assessment of gully erosion susceptibility was performed using four state-of-the-art data mining techniques: random forest (RF), credal decision trees (CDTree), kernel logistic regr...

Full description

Bibliographic Details
Main Authors: Xinxiang Lei, Wei Chen, Mohammadtaghi Avand, Saeid Janizadeh, Narges Kariminejad, Hejar Shahabi, Romulus Costache, Himan Shahabi, Ataollah Shirzadi, Amir Mosavi
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Remote Sensing
Subjects:
machine learning
GIS
gully erosion
susceptibility mapping
head-cut erosion
Iran
Online Access:https://www.mdpi.com/2072-4292/12/15/2478

Internet

https://www.mdpi.com/2072-4292/12/15/2478

Similar Items