Feini Huang
Impact in
- Environmental Engineering top 5%
- Soil Moisture and Remote Sensing
- Hydrological Forecasting Using AI
- Global and Planetary Change top 10%
- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Hydrology and Drought Analysis
Papers in
-
- Soil Moisture and Remote Sensing 7
- Hydrological Forecasting Using AI 2
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- Hydrology and Drought Analysis 3
- Climate variability and models 2
- Co-authors
- Wei Shangguan (12 shared papers)Ye Zhang (8 shared papers)Qingliang Li (9 shared papers)Jianduo Li (4 shared papers)Lu Li (5 shared papers)Vahid Nourani (3 shared papers)Yongjiu Dai (3 shared papers)Xingjie Lu (2 shared papers)
In The Last Decade
Feini Huang
13 papers receiving 448 citations
Feini Huang's Hit Papers
Peers
Comparison fields: 5 of 53
- Environmental Engineering 195
- Global and Planetary Change 200
- Atmospheric Science 132
- Water Science and Technology 94
- Health Informatics 5
Countries citing papers authored by Feini Huang
This map shows the geographic impact of Feini Huang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Feini Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feini Huang more than expected).
Fields of papers citing papers by Feini Huang
This network shows the impact of papers produced by Feini Huang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Feini Huang. The network helps show where Feini Huang may publish in the future.
Co-authors
The 25 scholars most cited alongside Feini Huang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A 1 km daily soil moisture dataset over China using in situ measurement and machine learning Hit paper breakdown → | 2022 | 152 |
| 2 | How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences Hit paper breakdown → | 2024 | 79 |
| 3 | 2021 | 58 | |
| 4 | 2022 | 29 | |
| 5 | 2023 | 25 | |
| 6 | 2023 | 24 | |
| 7 | A China dataset of soil properties for land surface modelling (version 2, CSDLv2) Hit paper breakdown → | 2025 | 23 |
| 8 | 2022 | 18 | |
| 9 | 2023 | 17 | |
| 10 | 2023 | 15 | |
| 11 | 2025 | 9 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 2 |
About Feini Huang
Feini Huang is a scholar working on Environmental Engineering, Global and Planetary Change, Atmospheric Science, Management, Monitoring, Policy and Law and Water Science and Technology, having authored 13 papers that have together received 454 indexed citations. Recurring topics across this work include Soil Moisture and Remote Sensing (7 papers), Hydrology and Drought Analysis (3 papers), Hydrology and Watershed Management Studies (3 papers), Landslides and related hazards (3 papers), Soil and Unsaturated Flow (2 papers), Hydrological Forecasting Using AI (2 papers), Climate variability and models (2 papers) and Reservoir Engineering and Simulation Methods (2 papers). The work is most often cited by research in Environmental Engineering (195 citations), Global and Planetary Change (200 citations), Atmospheric Science (132 citations), Water Science and Technology (94 citations) and Health Informatics (5 citations). Feini Huang has collaborated with scholars based in China, Iran and Germany. Frequent co-authors include Wei Shangguan, Ye Zhang, Qingliang Li, Jianduo Li, Lu Li, Vahid Nourani, Yongjiu Dai, Xingjie Lu, Chunyan Wang and Dagang Wang. Their work appears in journals such as Earth system science data, Remote Sensing, Environmental Research Letters, Forests and Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.