Machine learning models for gully erosion susceptibility assessment in the Tensift catchment, Haouz Plain, Morocco for sustainable development

Author:

Bammou Youssef,Benzougagh Brahim,Abdessalam Ouallali,Brahim Igmoullan,Kader ShuraikORCID,Spalevic Velibor,Sestras Paul,Ercişli Sezai

Publisher

Elsevier BV

Reference83 articles.

1. Quantifying soil erosion and influential factors in Guwahati's urban watershed using statistical analysis, machine and deep learning;Ahmed;Remote Sens. Appl.: Society and Environment,2024

2. Modelling water erosion and mass movements (wet) by using GIS-based multi-hazard susceptibility assessment approaches: a case study—kratovska Reka Catchment (North Macedonia);Aleksova;Atmosphere,2023

3. Remote sensing and GIS-based machine learning models for spatial gully erosion prediction: a case study of Rdat watershed in Sebou basin, Morocco;Aouragh;Remote Sens. Appl.: Society and Environment,2023

4. Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms;Arabameri;Geomatics, Nat. Hazards Risk,2021

5. Morphometric analysis for soil erosion susceptibility mapping using novel GIS-based ensemble model;Arabameri;Rem. Sens.,2020

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