Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

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

Créateur:
YouBraOuaIgm
Éditeur:
Elsevier BV
Hôte:

Visit

doi.org

Licenses

https://www.elsevier.com/tdm/userlicense/1.0/http://creativecommons.org/licenses/by/4.0/

Similaires

Bivariate Based Susceptibility Mapping for Gully Erosion in Wanjoga River Catchment Upper Tana Basin, KenyaA Methodological Comparison of Three Models for Gully Erosion Susceptibility Mapping in the Rural Municipality of El Faid (Morocco)Performance Assessment of Machine Learning Techniques for Gully Erosion Mapping in South-East NigeriaMachine Learning and Remote Sensing for Gully Erosion Susceptibility Mapping in Southeast Nigeria: Progress, Challenges, and Research PrioritiesGully Erosion Susceptibility Mapping using Machine Learning Techniques in Ihioma Community, Imo State, NigeriaBekaluWeretaw/gully-erosion-susceptibility-tekeze

Bivariate Based Susceptibility Mapping for Gully Erosion in Wanjoga River Catchment Upper Tana Basin, Kenya

Gullies occur in semi-arid regions characterized by rainfall variability and seasonality, increased

A Methodological Comparison of Three Models for Gully Erosion Susceptibility Mapping in the Rural Municipality of El Faid (Morocco)

Erosion is the main threat to sustainable water and soil management in Morocco. Located in the Souss

Performance Assessment of Machine Learning Techniques for Gully Erosion Mapping in South-East Nigeria

Soil erosion is a serious environmental hazard affecting southeast Nigeria. The rate of erosion has

Machine Learning and Remote Sensing for Gully Erosion Susceptibility Mapping in Southeast Nigeria: Progress, Challenges, and Research Priorities

Gully erosion remains one of the most destructive forms of land degradation in tropical environments

Gully Erosion Susceptibility Mapping using Machine Learning Techniques in Ihioma Community, Imo State, Nigeria

Gully erosion poses significant environmental and socio-economic challenges in many regions worldwid

BekaluWeretaw/gully-erosion-susceptibility-tekeze

Code for: Integrated Machine Learning and Geospatial Approach for Gully Erosion Susceptibility Model