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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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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Identifying Landslide Hotspots Using Unsupervised Clustering: A Case Study

2024Journal of Future Artificial Intelligence and TechnologiesJournalOpen access

10.62411/faith.3048-3719-37 Full text3 citations

Authors

6 authors across 2 institutions in 2 countries.

Ikechukwu DanielFirst author
- Nnamdi Azikiwe University (NG)
Ikechukwu DanielFirst author
- Nnamdi Azikiwe University (NG)
Ikechukwu DanielFirst author
- Nnamdi Azikiwe University (NG)
Ikechukwu DanielFirst author
- Nnamdi Azikiwe University (NG)
Lateef A. Akinyemi
- University of South Africa (ZA)
as printed: Lateef Akinyemi
Obianuju UdekwuSenior author
- Nnamdi Azikiwe University (NG)

Fields

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

Landslides and related hazardslevel 3 · 1.00

Sources

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

openalexseen September 9, 2026
2024 · Journal of Future Artificial Intelligence and Technologies · 3 citations
https://openalex.org/W4404066435

Identifying Landslide Hotspots Using Unsupervised Clustering: A Case Study · Sankore