A hybrid deep learning framework for estimating urban tree transpiration
- DOI
- 10.1016/j.jenvman.2026.130780
- Published
- 2026-09
- Container
- Journal of Environmental Management
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jenvman.2026.130780,
title = {A hybrid deep learning framework for estimating urban tree transpiration},
author = {Xiang Zhang and Xue Zhong and Jun-Ru Yan and Qi Li and Kai-Xin Liu and Ling-Ye Yao and Long-Hao Zhang and Astrid Moser-Reischl and Thomas Rötzer and Stephan Pauleit and Mohammad A. Rahman},
year = {2026},
journal = {Journal of Environmental Management},
doi = {10.1016/j.jenvman.2026.130780},
url = {https://doi.org/10.1016/j.jenvman.2026.130780}
}RIS
TY - JOUR TI - A hybrid deep learning framework for estimating urban tree transpiration AU - Xiang Zhang AU - Xue Zhong AU - Jun-Ru Yan AU - Qi Li AU - Kai-Xin Liu AU - Ling-Ye Yao AU - Long-Hao Zhang AU - Astrid Moser-Reischl AU - Thomas Rötzer AU - Stephan Pauleit AU - Mohammad A. Rahman PY - 2026 JO - Journal of Environmental Management DO - 10.1016/j.jenvman.2026.130780 UR - https://doi.org/10.1016/j.jenvman.2026.130780 ER -
APA
Zhang, X., Zhong, X., Yan, J., Li, Q., Liu, K., Yao, L., Zhang, L., Moser-Reischl, A., Rötzer, T., Pauleit, S., & Rahman, M. A. (2026). A hybrid deep learning framework for estimating urban tree transpiration. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2026.130780
Source records
- crossref · retrieved 2026-09-25T14:10:59.424Z