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Peer-reviewedCC BY-NC-ND 4.0Scientific Reports

A machine learning model for early season wildfire risk in Ghana’s Guinea savannah assessing discrimination, operational prevalence, spatial transferability, and CMIP6 climate scenarios

  • Wallelgn Melese Tema
  • Stephen Bradshaw
  • Emet Arya
  • Bright Wiredu Nuakoh
  • Yaw Kwaafo Awuah-Mensah
  • Wei Hong Tan
  • Francky Fouedjio
  • Ebenezer Afrifa-Yamoah
Open at sourcePDFDOICite

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Cite

BibTeXRIS
BibTeX
@article{tema2026machine,
  title = {{A machine learning model for early season wildfire risk in Ghana’s Guinea savannah assessing discrimination, operational prevalence, spatial transferability, and CMIP6 climate scenarios}},
  author = {Wallelgn Melese Tema and Stephen Bradshaw and Emet Arya and Bright Wiredu Nuakoh and Yaw Kwaafo Awuah-Mensah and Wei Hong Tan and Francky Fouedjio and Ebenezer Afrifa-Yamoah},
  journal = {Scientific Reports},
  year = {2026},
  month = oct,
  doi = {10.1038/s41598-026-73176-5},
  url = {https://www.nature.com/articles/s41598-026-73176-5},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - A machine learning model for early season wildfire risk in Ghana’s Guinea savannah assessing discrimination, operational prevalence, spatial transferability, and CMIP6 climate scenarios
AU  - Wallelgn Melese Tema
AU  - Stephen Bradshaw
AU  - Emet Arya
AU  - Bright Wiredu Nuakoh
AU  - Yaw Kwaafo Awuah-Mensah
AU  - Wei Hong Tan
AU  - Francky Fouedjio
AU  - Ebenezer Afrifa-Yamoah
PY  - 2026
DA  - 2026/10/20
JO  - Scientific Reports
DO  - 10.1038/s41598-026-73176-5
UR  - https://www.nature.com/articles/s41598-026-73176-5
SN  - 2045-2322
ER  -