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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.

Evaluation of Artificial Neural Networks (ANNs) and Multivariate Adaptive Regression Splines (MARS) for Monthly Mean Land Surface Temperature (LST) Modelling– A Case Study of Aowin District, The Republic of Ghana

2025Journal of GeomaticsJournalOpen access

10.58825/jog.2025.19.1.185 Full text0 citations

Authors

4 authors across 3 institutions in 2 countries.

Michael Stanley PeprahFirst author
Edwin Kojo Larbı
- Council for Scientific and Industrial Research (GH)
as printed: Edwin Kojo Larbi
Prince Opoku Appau
Michael Angbang MwinSenior author
- University of Energy and Natural Resources (GH)

Fields

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

Remote Sensing and Land Uselevel 3 · 0.88
Remote-Sensing Image Classificationlevel 3 · 0.86
Neural Networks and Applicationslevel 3 · 0.83

Sources

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

openalexseen September 5, 2026
2025 · Journal of Geomatics · 0 citations
https://openalex.org/W4410134750

Evaluation of Artificial Neural Networks (ANNs) and Multivariate Adaptive Regression Splines (MARS) for Monthly Mean Land Surface Temperature (LST) Modelling– A Case Study of Aowin District, The Republic of Ghana · Sankore