Gully erosion studies using artificial intelligence approaches: A systematic review
• Data-backed identification of the best performing AI models in gully erosion studies • Development of framework for accuracy metrics • Development of hierarchical framework for semantic-segmentation • Identification of the most important conditioning factors in gully erosion studies • Influence of climate and soil type on gully erosion conditioning factors
Authors
- Esdras Ngezahayo (ORCID: https://orcid.org/0000-0002-6856-4756)
- Ian Jefferson (ORCID: https://orcid.org/0000-0001-6437-101X)
- Obinna Uzodimma Ubani (ORCID: https://orcid.org/0000-0002-6421-5524)
Institutions
- University of Birmingham (GB)
Publication Details
- Journal
- CATENA
- Published
- 2026-05-23
- DOI
- https://doi.org/10.1016/j.catena.2026.110249
- Primary Topic
- Soil erosion and sediment transport
- Type
- article
- Field-Weighted Citation Impact
- 0.00