Spatial Prediction and Mapping of Gully Erosion Susceptibility Using Machine Learning Techniques in a Degraded Semi-Arid Region of Kenya

Spatial Prediction and Mapping of Gully Erosion Susceptibility Using Machine Learning Techniques in a Degraded Semi-Arid Region of Kenya

This study aimed at (i) developing, evaluating and comparing the performance of support vector machines (SVM), boosted regression trees (BRT), random forest (RF) and logistic regression (LR) models in mapping gully erosion susceptibility, and (ii) determining the important gully erosion conditioning...

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Bibliographic Details
Main Authors: Kennedy Were, Syphyline Kebeney, Harrison Churu, James Mumo Mutio, Ruth Njoroge, Denis Mugaa, Boniface Alkamoi, Wilson Ng’etich, Bal Ram Singh
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Land
Subjects:
soil erosion
land degradation
sustainable land management
landscape restoration
spatial prediction
machine learning
Online Access:https://www.mdpi.com/2073-445X/12/4/890

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