8 citations as recorded by crossref.

1. Potential of constructing all‐encompassing soil–plant‐atmosphere‐continuum stations and datasets from meteorological, flux, soil moisture station networks and plant‐relevant observations H. Shi 10.1002/hyp.15284
2. Satellite-based measurements of temporal and spatial variations in C fluxes of irrigated and rainfed cotton grown in India D. Blaise et al. 10.1016/j.rsase.2024.101365
3. Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing M. Xie et al. 10.1038/s41597-023-02473-9
4. Machine learning-based investigation of forest evapotranspiration, net ecosystem productivity, water use efficiency and their climate controls at meteorological station level H. Shi et al. 10.1016/j.jhydrol.2024.131811
5. Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis H. Shi et al. 10.5194/hess-26-4603-2022
6. Revisiting and attributing the global controls over terrestrial ecosystem functions of climate and plant traits at FLUXNET sites via causal graphical models H. Shi et al. 10.5194/bg-20-2727-2023
7. Extrapolability improvement of machine learning-based evapotranspiration models via domain-adversarial neural networks H. Shi & X. Cai 10.1016/j.envsoft.2025.106383
8. Spatiotemporal lagging of predictors improves machine learning estimates of atmosphere–forest CO2 exchange M. Kämäräinen et al. 10.5194/bg-20-897-2023