A data-driven framework for flood hazard mapping using integrated geospatial and multi-model machine learning approaches in a tropical mountainous region: insights from Aceh Jaya, Aceh Province, Indonesia.
- DOI
- 10.1007/s11356-026-38077-0
- Published
- 2026 Jun
- Container
- Environmental science and pollution research international
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s11356-026-38077-0,
title = {A data-driven framework for flood hazard mapping using integrated geospatial and multi-model machine learning approaches in a tropical mountainous region: insights from Aceh Jaya, Aceh Province, Indonesia.},
author = {Razi MH and Aulia N and Nugraha WC},
year = {2026},
journal = {Environmental science and pollution research international},
doi = {10.1007/s11356-026-38077-0},
url = {https://doi.org/10.1007/s11356-026-38077-0}
}RIS
TY - JOUR TI - A data-driven framework for flood hazard mapping using integrated geospatial and multi-model machine learning approaches in a tropical mountainous region: insights from Aceh Jaya, Aceh Province, Indonesia. AU - Razi MH AU - Aulia N AU - Nugraha WC PY - 2026 JO - Environmental science and pollution research international DO - 10.1007/s11356-026-38077-0 UR - https://doi.org/10.1007/s11356-026-38077-0 ER -
APA
MH, R., N, A., & WC, N. (2026). A data-driven framework for flood hazard mapping using integrated geospatial and multi-model machine learning approaches in a tropical mountainous region: insights from Aceh Jaya, Aceh Province, Indonesia.. Environmental science and pollution research international. https://doi.org/10.1007/s11356-026-38077-0
Source records
- pubmed · retrieved 2026-09-25T11:30:56.780Z