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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Integrated flood susceptibility mapping using machine learning and geospatial techniques: a case study of Imo State, Southeastern Nigeria

2025Journal of African Earth SciencesJournal

10.1016/j.jafrearsci.2025.105872 Full text2 citations

Authors

8 authors across 5 institutions in 3 countries.

Emeka OkoliFirst author
- Federal University of Technology Owerri (NG)
as printed: Emeka Austin Okoli
Kawa Maximus Josephine
Chidiebere Charles AgohaCorresponding
- Federal University of Technology Owerri (NG)
Diugo Okereke Ikoro
- Federal University of Technology Owerri (NG)
Derrick Odondiri Oyinebielador
Ebenezer Aniyom
- Federal University of Technology Owerri (NG)
as printed: Ebenezer Ananiyom Aniyom
Jeremiah Toluwani Oladipupo
- Imo State University (NG)
Uzochukwu David EmenyonuSenior author
- Federal University of Technology Owerri (NG)

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Flood Risk Assessment and Managementlevel 3 · 1.00
Groundwater and Watershed Analysislevel 3 · 0.99
Hydrology and Watershed Management Studieslevel 3 · 0.98

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2025 · Journal of African Earth Sciences · 2 citations
https://openalex.org/W4414803679

Integrated flood susceptibility mapping using machine learning and geospatial techniques: a case study of Imo State, Southeastern Nigeria · Sankore