3 citations · 9 across the 5 of their papers we have counts for
5 papers
SpecSAR-Former: A Lightweight Transformer-based Network for Global LULC Mapping Using Integrated Sentinel-1 and Sentinel-2
Hao Yu, Gen Li, Haoyu Liu +3
Recent approaches in remote sensing have increasingly focused on multimodal data, driven by the growing availability of diverse earth observation datasets. Integrating complementar…
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…
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…
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…
Forest aboveground biomass estimation using GEDI and earth observation data through attention-based deep learning
Wenquan Dong, Edward T. A. Mitchard, Hao Yu +2
Accurate quantification of forest aboveground biomass (AGB) is critical for understanding carbon accounting in the context of climate change. In this study, we presented a novel at…