2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
UFLUX v2.0: A Process-Informed Machine Learning Framework for Efficient and Explainable Modelling of Terrestrial Carbon Uptake
Wenquan Dong, Songyan Zhu, Jian Xu +6
Gross Primary Productivity (GPP), the amount of carbon plants fixed by photosynthesis, is pivotal for understanding the global carbon cycle and ecosystem functioning. Process-based…
cs.CV2024★ 2 cited
Comparing remote sensing-based forest biomass mapping approaches using new forest inventory plots in contrasting forests in northeastern and southwestern China
Wenquan Dong, Edward T. A. Mitchard, Yuwei Chen +5
Large-scale high spatial resolution aboveground biomass (AGB) maps play a crucial role in determining forest carbon stocks and how they are changing, which is instrumental in under…
cs.CV2023★ 1 cited
Multimodal deep learning for mapping forest dominant height by fusing GEDI with earth observation data
Man Chen, Wenquan Dong, Hao Yu +5
The integration of multisource remote sensing data and deep learning models offers new possibilities for accurately mapping high spatial resolution forest height. We found that GED…