A transferable machine learning framework integrating multi-dimensional vegetation thresholds to predict green infrastructure cooling efficacy in arid urban areas
- DOI
- 10.1038/s41598-026-59519-2
- Published
- 2026-07-08
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-59519-2,
title = {A transferable machine learning framework integrating multi-dimensional vegetation thresholds to predict green infrastructure cooling efficacy in arid urban areas},
author = {Abdulrahman Abdulaziz Majrashi and Faizah Mohammed Bashir and Mohammed Alzahrani and Nadia Hasen Rassas and Zahra Andleeb and Matusal Lamaro Lagebo and Yohannes Mehari Andiye},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-59519-2},
url = {https://doi.org/10.1038/s41598-026-59519-2}
}RIS
TY - JOUR TI - A transferable machine learning framework integrating multi-dimensional vegetation thresholds to predict green infrastructure cooling efficacy in arid urban areas AU - Abdulrahman Abdulaziz Majrashi AU - Faizah Mohammed Bashir AU - Mohammed Alzahrani AU - Nadia Hasen Rassas AU - Zahra Andleeb AU - Matusal Lamaro Lagebo AU - Yohannes Mehari Andiye PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-59519-2 UR - https://doi.org/10.1038/s41598-026-59519-2 ER -
APA
Majrashi, A. A., Bashir, F. M., Alzahrani, M., Rassas, N. H., Andleeb, Z., Lagebo, M. L., & Andiye, Y. M. (2026). A transferable machine learning framework integrating multi-dimensional vegetation thresholds to predict green infrastructure cooling efficacy in arid urban areas. Scientific Reports. https://doi.org/10.1038/s41598-026-59519-2
Source records
- crossref · retrieved 2026-11-11T04:13:15.557Z